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SAO/NASA Astrophysics Data System 13

2020AandA...633A.163C__Aalto_et_al._2015_Instance_2

By using the RADEX2 dense cloud models developed by Aalto et al. (2015) to reproduce the HCN(3–2)/(1–0) line luminosity ratios in the outflow of Mrk 231, we can attempt to find a combination of XHCN, XCN, Tkin, and nH2 solutions that can also fit the CN/HCN and CN spin doublet line ratios (Table 2). We assume that the HCN and CN line emissions arise from the same dense cloud population, while the low-J CO line emission is due to a different, more diffuse phase of the outflow. We recall that in these models (see also Aalto et al. 2015), the dense clouds can be either self-gravitating virialised clouds, which implies that their internal velocity dispersion (Δvsg) is locked to their mass (Mvir) and size (R) through Δvsg = (GMvir/G)1/2, or unbound clouds, for which Δv ≫ Δvsg. We explored CN and HCN abundances in the range between 10−8 and 10−6. We find that depending on whether the clouds are self-gravitating or unbound, the models produce very different values for the absolute CN and HCN abundances, hence XCN and XHCN remain quantitatively unconstrained for the outflow with current data. However, all possible solutions that fit the observed line ratios consistently require XCN >  XHCN, with a CN abundance that is at least a factor of three higher than the HCN abundance. Gas densities for this outflow phase (traced by the CN and HCN emissions) are nH2 ∼ 105 − 106 cm−3, with temperatures not much higher than Tkin ∼ 20 K. Because CN is a well-known PDR tracer (see also Sect. 1), these results strongly suggest that the whole dense cloud population in outflow is affected by UV radiation. We should mention that high CN abundances may also be due to cosmic rays (e.g. see work done on the Galactic centre by Harada et al. 2015), which are known to permeate the outflow of Mrk 231, as inferred by González-Alfonso et al. (2018) based on the high OH+ abundance. However, it is not clear whether a cosmic-ray chemistry would also explain XCN >  XHCN.

2019MNRAS.486..360K__Nättilä_&_Pihajoki_2018_Instance_1

We have presented the principles and framework for calculating the radio signal from a PSR in an EMRB. We restrict our study to the extreme mass ratio of EMRB systems and so do not consider PSRs in stellar-mass BH binaries with finite mass ratios (e.g. Blanchet 2014; Liu et al. 2014). We account for both relativistic and astrophysical effects and the convolution between the two. This includes gravitational and relativistic time dilation and energy shift, gravitational light bending, complex orbital dynamics induced by spin couplings, temporal variation and distortion of the pulse profile due to spin axis precession and relativistic aberration, second-order pulses due to gravitational bending, and dispersions (temporal and spatial) induced by the material along the line of sight. We have demonstrated that within our framework we are able to determine the time–frequency behaviour accounting for all these effects. The framework also applies for any orbital configuration, e.g. we are not restricted to orbital motion in the equatorial plane or beaming confined to the orbital plane. The methods used are entirely covariant and general relativistic, rather than working under any post-Newtonian approximation and so are inherently more accurate. Indeed, the post-Newtonian method is an explicitly weak-field method, and the validity of its application to strong-field dynamical regimes is unclear (Will 2011). Whilst working explicitly in the Kerr metric means that we are unable to independently probe either alternative gravitational theories or extensions to Kerr (e.g. Kerr space–time with an arbitrary mass quadrupole; see Bini et al. 2009), our framework provides the basis for a theoretical timing model that can then be compared with observations for tests of strong field GR. We approximate the PSR body as a perfect sphere. However, due to the spin of the PSR the true shape is more oblate. This will ultimately influence the pitch angle of the ray with the neutron star surface. This effect is considered to be minor, but the method could easily be extended to account for this oblateness (see Nättilä & Pihajoki 2018). We neglect the effects of hydrodynamic drag due to the plasma that surrounds that BH since at compact radii (≲ 104rg) the gravitational and relativistic effects dominate (Psaltis 2012). We also do not take account of any potential Newtonian perturbations on the motion of the pulsar (e.g. Merritt et al. 2011) due to the presence of other masses (e.g. stars, other compact objects etc.) since these factors are likely negligible for the orbital periods considered in this work (≲0.3 yr; Liu et al. 2012). Indeed, the potential for external perturbations to hamper tests of strong-field GR necessitates that an ideal PSR–EMRB systems should have orbital periods on the order of 0.1 yr (or better), or else observations should be taken close to periapsis (see discussion in Psaltis, Wex & Kramer 2016). These are precisely the regions where the space–time curvature and orbital acceleration is greatest, further stressing the importance of a strong-field timing model. We also neglect any influence of gravitational radiation on the orbit or the ray trajectory. The neglect of gravitational radiation is justified since in the extreme mass ratio limit, the time-scale for orbital decay due to gravitational wave emission is (Misner, Thorne & Wheeler 1973) (45) \begin{eqnarray*} \tau _{\mathrm{ GW}} \sim \frac{5 r^4}{96mM(m+M)} f(e)^{-1} \ , \end{eqnarray*} where M is the mass of the BH, m the pulsar mass, and r the orbital separation. The eccentricity function is (46) \begin{eqnarray*} f(e) = (1-e^2)^{-7/2} \left(1 + \frac{73}{24} e^2 + \frac{37}{96} e^4\right) \ . \end{eqnarray*} If we take the PSR orbital period P to be Keplerian, then for a pulsar with mass $1.4 \, \mathrm{M}_{\odot }$ on an eccentric (e = 0.8), P = 0.1 yr orbit around a BH with mass $4.3 \times 10^6 \, \mathrm{M}_{\odot }$(47) \begin{eqnarray*} \frac{\tau _{\mathrm{ GW}}}{P} \sim 10^9 \gt \gt 1 \ , \end{eqnarray*} and so the effects of gravitational radiation can be neglected. Even for smaller radii and more eccentric orbits the space–time is well approximated as stationary (e.g. τGW/P  ∼ 105 for e = 0.9, r = 100 M). Whilst the effects of gravitational radiation are then not important for a single orbit, for observations over longer periods of time the effect of gravitational emission on the orbit and hence the timing solution will need to be considered. The PSR may also emit a gravitational wave burst during passage through periastron (Berry & Gair 2013a,b). The influence of this gravitational radiation on both the PSR trajectory and the photon ToA is highly non-trivial and not considered here.

2018ApJ...866L...1S__Pecharromán_et_al._1999_Instance_6

It was found that the complex dielectric function from Pecharromán et al. (1999) for the sample obtained by heating bayerite at 1273 K, assuming a spheroid with depolarization parameters of (0.35, 0.003), produced an opacity with 11, 20, 28, and 32 μm features, so this component was included in the models. However, with only this component, the observed 20 μm features in the residual spectra were found to be wider than those in the models. By adding the opacity of the sample obtained by heating boehmite at 1173 K, the width of the 20 μm feature could be matched. This was done using the complex dielectric function for the sample obtained by heating boehmite at 1173 K from Pecharromán et al. (1999), assuming a spheroid with depolarization parameters of (0.35, 0.035). The complex dielectric functions of the samples obtained by heating bayerite and boehmite to various temperatures (Pecharromán et al. 1999) were derived by modeling the reflectance spectra of pellets obtained by pressing powders of these materials under great pressure. This method required Pecharromán et al. (1999) to assume an effective medium theory, such that a pellet is a mixture of one of their samples with a matrix of air. Pecharromán et al. (1999) noted that heating bayerite at 500°C eliminates the XRD pattern of bayerite, and they note that at 700°C, the infrared reflectance spectrum of the boehmite sample no longer shows OH− stretching bands. This must mean that the samples obtained from heating bayerite at 1273 K and from heating boehmite at 1173 K are no longer bayerite or boehmite, respectively. XRD performed by Pecharromán et al. (1999) of the sample of bayerite prepared at 1273 K suggests only θ-alumina was present, and their infrared and NMR spectroscopy confirms this. XRD of their sample obtained from heating boehmite to 1173 K (Pecharromán et al. 1999) suggests δ-alumina to be present, though some amounts of θ-alumina and α-alumina are present, as they deduce from XRD and infrared and NMR spectroscopy.

2022AandA...667A..97A__Xiong_(1986)_Instance_1

The temperature gradient of the 3-equation model is comparable to results of different TCM approaches (Xiong & Deng 2001; Li & Yang 2007) for the base of the solar convective envelope. Both Zhang & Li (2012; their Figs. 6 and 7) and Xiong & Deng (2001; their Fig. 8) find a temperature gradient that transitions gradually from the adiabatic to the radiative value. They also find a Deardorff layer with a degree of sub-adiabaticity at the formal Schwarzschild boundary comparable to our findings. From the convective flux as presented in Xiong (1986) one also would expect a similar temperature gradient in the overshooting zone. Furthermore, the shape of the model temperature gradient is also in qualitative agreement with the discussion in Viallet et al. (2015). They argue that under the physical conditions in convective cores, in regions of overshooting efficient chemical mixing and a gradually transitioning temperature gradient are expected. In the 3-equation non-local model, the extent of the nearly adiabatic overshooting zone is controlled by the shape of the negative convective flux in the overshooting zone. For smaller (more negative) values of the convective flux (i.e. more efficient buoyancy braking) the temperature gradient is expected to be closer to the adiabatic value, while for larger (less negative) values it will be closer to the radiative temperature gradient. In Eq. (1) the negative convective flux and the dissipation term act as sink terms in the overshooting zone. Hence, the behaviour of the dissipation term will impact also on the convective flux and in turn on the value of the temperature gradient in the overshooting zone. In computations with the 1-equation non-local version of the theory, the negative convective flux is the dominant sink term for the TKE and the actual dissipation term is negligible (Fig. 8 of Paper I). This leads to more negative values of the convective flux and thus to a mostly adiabatic temperature gradient in the overshooting zone. We discuss this in more detail in Sect. 5.1 (we also refer to Fig. 10).

2022MNRAS.514.2010M__Feng_&_Holder_2018_Instance_2

In the last few years, several experiments have reported upper limits on the power spectrum of 21-cm fluctuations during reionization (Parsons et al. 2014; Patil et al. 2017; Barry et al. 2019; Mertens et al. 2020; The HERA Collaboration 2021b) and the earlier cosmic-dawn era (Eastwood et al. 2019; Gehlot et al. 2019, 2020; Garsden et al. 2021; Yoshiura et al. 2021). Scenarios in which the bulk IGM is still colder than the cosmic microwave background (CMB) during reionization give rise to the strongest fluctuations and so will be the first models to be tested as upper limits continue to improve (e.g. Parsons et al. 2014; Pober et al. 2015; Greig, Mesinger & Pober 2016). Similarly, stronger-than-expected 21-cm signals can arise if the cosmic radio background has contributions other than the CMB (Feng & Holder 2018), e.g. synchrotron emission from accreting black holes (Ewall-Wice et al. 2018), star-forming galaxies (Mirocha & Furlanetto 2019), or from decaying particles (Fraser et al. 2018; Pospelov et al. 2018). Indeed, constraints from MWA, HERA, and LoFAR disfavour models with negligible X-ray heating at z ∼ 8–9 or very strong radio backgrounds (Ghara et al. 2020, 2021; Mondal et al. 2020; Greig et al. 2021a, b; The HERA Collaboration 2021a). Of course, the recent report of an absorption signal in the sky-averaged spectrum at z ∼ 17 from EDGES (Bowman et al. 2018) requires an even colder IGM (Barkana 2018; Boddy et al. 2018; Fialkov, Barkana & Cohen 2018; Kovetz et al. 2018; Muñoz & Loeb 2018) or a brighter background (Ewall-Wice et al. 2018; Feng & Holder 2018; Fialkov & Barkana 2019; Mirocha & Furlanetto 2019) than models in ΛCDM cosmologies generally predict. However, the most stringent power spectrum upper limits from The HERA Collaboration (2021b) are derived at sufficiently low redshifts relative to EDGES (z ≲ 10 versus z ≃ 18) that they cannot yet directly address the EDGES controversy (Hills et al. 2018; Bradley et al. 2019; Singh & Subrahmanyan 2019; Sims & Pober 2020; Tauscher, Rapetti & Burns 2020; Singh et al. 2021).

2022AandA...659A...5Y__Mills_et_al._2018_Instance_1

Since its discovery more than five decades ago (Cheung et al. 1968), ammonia (NH3) has been a most valuable molecule for investigating the physical properties of molecular clouds (e.g., Ho & Townes 1983). While thermally excited transitions in the centimeter-wavelength inversion transitions of ammonia are regarded as a reliable thermometer of molecular clouds (e.g., Walmsley & Ungerechts 1983; Danby et al. 1988), ammonia masers have attracted attention since the first detection of maser action in the (J, K) = (3,3) metastable (J = K) line toward the massive star-forming region W33 (Wilson et al. 1982). Subsequent observations have led to the detection of new metastable ammonia masers, including 15NH3 (3,3) (Mauersberger et al. 1986), NH3 (1,1) (Gaume et al. 1996), NH3 (2,2) (Mills et al. 2018), NH3 (5,5) (Cesaroni et al. 1992), NH3 (6,6) (Beuther et al. 2007), NH3 (7,7), NH3 (9,9), and NH3 (12,12) (Henkel et al. 2013). These have led to the discovery of metastable maser lines in 22 different regions (Mauersberger et al. 1986, 1987; Wilson & Henkel 1988; Wilson et al. 1990; Pratap et al. 1991; Cesaroni et al. 1992; Wilson & Schilke 1993; Mangum & Wootten 1994; Kraemer & Jackson 1995; Zhang & Ho 1995; Zhang et al. 1999; Walsh et al. 2007; Hunter et al. 2008; Galván-Madrid et al. 2009; Brogan et al. 2011; Urquhart et al. 2011; Walsh et al. 2011; Wang et al. 2012; Henkel et al. 2013; Hoffman & Joyce 2014; McEwen et al. 2016; Mills et al. 2018; Hogge et al. 2019; Mei et al. 2020; Towner et al. 2021). Compared with the metastable ammonia masers, detected non-metastable (J > K) ammonia maser transitions are more numerous. The first highly excited non-metastable ammonia maser was detected by Madden et al. (1986) in the (J, K) = (9,6) and (6,3) lines. Thereafter, many other NH3 non-metastable inversion transition lines have been identified as masers, including the (5,3), (5,4), (6,1), (6,2), (6,4), (6,5), (7,3), (7,4), (7,5) (7,6), (8,3), (8,4), (8,5), (8,6), (9,3), (9,4), (9,5), (9,7), (9,8), (10,7), (10,8), (10,9), and (11,9) transitions (e.g., Mauersberger et al. 1987, 1988; Walsh et al. 2007; Henkel et al. 2013; Mei et al. 2020). Except for the NH3 (3,3) masersproposed to be associated with four supernova remnants (McEwen et al. 2016), almost all the other ammonia masers are detected in high-mass star-forming regions (HMSFRs). However, while many HMSFRs host water (H2O), hydroxyl (OH), or methanol (CH3OH) masers, ammonia masers are quite rare in these sources, and the role that the environment of a young high-mass star plays in their excitation remains unclear. Therefore, dedicated searches for ammonia masers in HMSFRs are indispensable in regard to their overall incidence and association with different environments, which can provide additional constraints on the pumping mechanism of ammonia masers.

2019AandA...622A.106M__Herranz_et_al._2009_Instance_1

The standard single-frequency detection methods for point sources in the CMB and far IR are based on wavelet techniques (Vielva et al. 2003; Barnard et al. 2004; González-Nuevo et al. 2006) or on the matched filter (or MF hereafter, Tegmark & de Oliveira-Costa 1998; Herranz et al. 2002; Barreiro et al. 2003; López-Caniego et al. 2006, see also Herranz & Vielva 2010 for a review.). Wavelets are well suited for the detection of compact sources due to their good position-scale determination properties, whereas the MF is the optimal linear detector-estimator because it provides the maximum signal-to-noise (S/N) amplification for a source with a known shape (usually the point-spread function, or PSF hereafter, of the telescope) embedded in statistically homogeneous and spatially correlated noise. By default, these techniques are applicable only to single-frequency sky images: even for multiwavelength observatories such as the Herschel Space Observatory (Pilbratt et al. 2010) or Planck (Tauber et al. 2010), the standard detection pipelines have produced individual source catalogs for each frequency band (see e.g., Planck Collaboration VII 2011; Planck Collaboration XXVIII 2014; Planck Collaboration XXVI 2016; Maddox et al. 2018). The next logical step is to boost the signal of faint sources by combining the different bands into a single detection, that is, “multifrequency detection”. Most of the blind component separation algorithms that are used for diffuse components in microwave and far IR astronomy can not deal with the high diversity of spectral behaviors associated to the different populations of extragalactic compact sources (see for example Leach et al. 2008). However, over the last few years a number of multifrequency compact source detection techniques have been proposed in the literature (Herranz & Sanz 2008; Herranz et al. 2009; Lanz et al. 2010, 2013; Planck Collaboration Int. LIV 2018). A review on the topic can be found in Herranz et al. (2012). In particular, if the spatial profile and the spectral energy distribution (SED) of the sources are known, and if the cross-power spectrum is known, or can be estimated from the data, the optimal linear detection method is the matched multifilter (or MMF hereafter, Herranz et al. 2002). Lanz et al. (2010) also showed that the MMF can be generalized for the case where the SED of the sources is not known. This generalization outperforms the single-frequency MF in terms of S/N and can be used to infer the spectral index of synchrotron-dominated radio sources, as shown in Lanz et al. (2013). However, in this paper we will incorporate a specific SED to the MMF in order to derive a photometric redshift estimation of dusty galaxies and high-redshift star forming galaxies detected in the IR part of the spectrum1. We will do so by applying the multifrequency MMF filter to the first and second data releases of the Herschel Astrophysical Terahertz Large Area Survey (the Herschel-ATLAS or H-ATLAS, Eales et al. 2010), the largest single key project carried out in open time with the Herschel Space Observatory. We restrict our multifrequency analysis to the three wavelength bands covered by the SPIRE instrument aboard Herschel (Griffin et al. 2010), centered around 250, 350 and 500 μm. As discussed in Hopwood et al. (2010), Lapi et al. (2011), González-Nuevo et al. (2012), Pearson et al. (2013) and Donevski et al. (2018), the SPIRE bands are ideal for capturing the peak in the SED corresponding to dust emission of star-forming galaxies at z ∼ 2, that is redshifted from its rest-frame wavelength around 70–100 μm to the SPIRE wavelengths: This is the redshift range where galaxies have formed most of their stars. At higher redshifts, dusty star-forming galaxies (DSFGs) occupy the most massive halos and are among the most luminous objects found at z ≳ 4 (Michałowski et al. 2014; Oteo et al. 2016; Ikarashi et al. 2017). These high-redshift DSFGs have markedly red colors as seen by SPIRE, with rising flux densities from 250 to 500 μm (the so-called “500 μm-risers”), and have received a great deal of attention in the recent years (see for example Ivison et al. 2016; Negrello et al. 2017; Strandet et al. 2017). The DSFGs, and particularly the 500 μm risers uncovered by Herschel, are providing much insight into the early star forming history of the universe. However, sensitivity and limited angular resolution severely constrain the power of this type of objects as astrophysical probes. The sensitivity of SPIRE allows for the direct detection of only the brightest, and thus rarest objects, at the bright end of the luminosity function. By means of our multifrequency MMF technique, we intend to enhance the detectability and statistical significance of very faint red objects in the H-ATLAS source catalog and so expand the list of reliable 500 μm-riser candidates.

2019AandA...629A..93Y__Hopkins_2018_Instance_1

The evolution of galaxies sensitively depends on the stellar initial mass function (IMF). The understanding of the IMF has changed rapidly in the past decade. Despite a direct conflict (Kroupa et al. 2013) with the theoretical expectation that the IMF should vary as the star-forming environment alters (e.g. ambient gas temperature, metallicity, density, and pressure dependence, as argued by Adams & Fatuzzo 1996; Larson 1998; Elmegreen 2004; Dib et al. 2007; Papadopoulos 2010) the observed IMFs of star clusters in the local Universe are consistent with no variation (Kroupa 2001, 2002; Bastian et al. 2010; Offner et al. 2014; Hopkins 2018). Thus, the universal and invariant canonical IMF assumption was widely applied. The more recent observations, which are able to probe physical regimes further from the solar and Galactic neighbourhood, have been consistently suggesting a variation of the galaxy-wide IMF (gwIMF1). For the distribution of low-mass stars, a bottom-heavy IMF (excess in the number of low-mass stars) in the inner regions of massive metal-rich elliptical galaxies is indicated by the galaxy mass-to-light ratio (Li et al. 2017), spectral analysis of stellar-mass sensitive features (Vazdekis et al. 1997, 2003; Cenarro et al. 2003; van Dokkum & Conroy 2010; Conroy & van Dokkum 2012; Ferreras et al. 2013; Martín-Navarro et al. 2015; La Barbera et al. 2017; Parikh et al. 2018) and lensing studies (Auger et al. 2010; Oldham & Auger 2018)2. For the distribution of massive stars, independent evidence strongly indicates a systematically varying IMF (galaxy photometry: Hoversten & Glazebrook 2008; Meurer et al. 2009; Lee et al. 2009; Gunawardhana et al. 2011, metal abundance of galaxy clusters: Renzini & Andreon 2014; Urban et al. 2017, isotope abundance: Romano et al. 2017; Zhang et al. 2018), being top-heavy (more massive stars than predicted when assuming the canonical IMF) when the SFR is high and/or when the metallicity is low, as summarized by Kroupa et al. (2013), Yan et al. (2017), and Jeřábková et al. (2018). We note that the IMF can be bottom-heavy and top-heavy at the same time (see Jeřábková et al. 2018).

2017MNRAS.470.1442C__Hurley_et_al._2002_Instance_1

We then allow the synthetic single or binary system to evolve until present time, adopting for our reference model a thin disc age of 10 Gyr (Cojocaru et al. 2014) and a thick disc age of 12 Gyr. This is motivated by the findings of Feltzing & Bensby (2009), who presented a sample of very likely thick disc candidates with ages, on average, well above 10 Gyr and of Ak et al. (2013), who found that thick disc cataclysmic variables have ages up to 13 Gyr. If the synthetic star is single and has time to become a white dwarf, it evolves following the cooling tracks detailed in the following section. If that is the case, the mass of the white dwarf is obtained from the initial-to-final mass relation (IFMR) according to the prescription from Hurley, Tout & Pols (2002). If the object is member of a binary system and the primary star has time to become a white dwarf, then the pair can evolve through two different scenarios. In the first scenario, the binary evolves without mass transfer interactions as a detached system and the primary star evolves into a white dwarf that subsequently cools down following the cooling sequences described in the next section. In this case, the mass of the white dwarf is also calculated from the IMFR of Hurley et al. (2002). The second scenario involves mass transfer episodes and the evolution of the binary is obtained following the prescriptions of the bse package (Hurley et al. 2002), following the parameter assumptions detailed in Camacho et al. (2014). If the system evolves though the common envelope phase, we use the α-formalism as described in Tout et al. (1997), with αCE being the efficiency in converting orbital energy into kinetic energy to eject the envelope (assumed to be 0.3 in our reference model). This implementation also takes into account the αint parameter (assumed to be 0.0 in our reference model), first presented in Han, Podsiadlowski & Eggleton (1995), describing the fraction of the internal energy (thermal, radiation and recombination energy) used to eject the envelope. As described in Camacho et al. (2014), the αint parameter is used to include the effects of the internal energy in the binding energy parameter λ, which is thus not taken as a constant, but computed using a specific algorithm (Claeys et al. 2014) in bse. In the current version of the code, provided that a positive value is used, the parameter αint represents the fraction of recombination energy that contributes to eject the envelope. It is important to note that the thermal energy of the envelope is always taken into account (using the virial theorem) even if αint is set to zero. For a more detailed discussion on how this is implemented in the latest version of BSE and important comments on the correct use of BSE and the notations used in the code itself, we direct the reader to Zorotovic, Schreiber & Parsons (2014a), mentioning that the notations αint or αrec are, in our case, equivalent.

2021ApJ...920...89C__Aragón-Calvo_et_al._2007_Instance_1

As mentioned in Section 1, once the sample of matching halos between the twin N-body simulations is established, we can study the halo−LSS correlations. We employ the Hessian matrix method used in many previous articles (e.g., Hahn et al. 2007a, 2007b; Zhang et al. 2009; Kang & Wang 2015) to define the matrix as: 4 H ij = ∂ 2 ρ s x ∂ x j ∂ x i . This method is based on the smoothed density field ρ s x at the halo position (based on a more accurate and improved algorithm by Wang et al. 2020), which can be given by the Cloud-in-Cell (CIC) technique (MacNeice 1995). The smoothing length Rs is the only parameter of the CIC, which can be regarded as the typical scale of a halo LSS environment identified by the Hessian matrix method. Many previous works (e.g., Aragón-Calvo et al. 2007; Hahn et al. 2007a; Zhang et al. 2009; Codis et al. 2012; Hoffman et al. 2012; Libeskind et al. 2013; Trowland et al. 2013, but see also Libeskind et al. 2014) used a constant smoothing length. To determine which Rs value should be chosen, we test some LSS properties (e.g., the environment and eigenvectors) of matching halos for three fixed Rs: 2.5, 5, and 10 h−1 Mpc. We find that the halo−LSS correlation, as well as other main conclusions we make below, become stronger as Rs decreases, which is a reasonable result according to our previous discussions. Consequently Rs = 2.5 h−1 Mpc is chosen hereafter. The three eigenvalues of the Hessian matrix are marked as λ1, λ2, and λ3, with corresponding eigenvectors e1, e2, and e3. Eigenvalues λi can be used to define the LSS environment of dark matter halos according to the number of positive eigenvalues (Zel’Dovich 1970; Hahn et al. 2007a, 2007b; Libeskind et al. 2018; Zhang & Yang 2019); i.e., 1. void: 0 λ1 λ2 λ3 2. wall: λ1 0 λ2 λ3 3. filament: λ1 λ2 0 λ3 4. cluster: λ1 λ2 λ3 0 and the eigenvectors ei stand for the three compressed directions of the smoothed density field. The e3 vector indicates the least compressed direction, which is a robust and universal definition of the LSS. In this work, we will focus on the alignment of halo spin and shape with the e3 vector; i.e., cos θ 3 = a · e 3 , where a is the halo spin or major-axis vector.

2020AandA...635A..81P__simulations,_Georgobiani_et_al._(2003)_Instance_2

Furthermore, Duvall et al. (1993) noticed an inversion of the sense of asymmetry between spectrometric and photometric measurements, with line profiles in the velocity spectrum featuring more power in their low-frequency wing than in their high-frequency wing and vice-versa for line profiles in the intensity spectrum. Since intensity perturbations were expected to be proportional to velocity perturbations, one would have expected the asymmetries to be the same. Many hypotheses were posited to explain this puzzling result. Duvall et al. (1993) suggested that it was due to non-adiabatic effects lifting the proportionality relationship between the two kinds of perturbations (fluid displacement and temperature) but this hypothesis was later contradicted by Rast & Bogdan (1998). Non-adiabaticity was brought up again later on by Georgobiani et al. (2003) who suggested that the explanation resided in radiative transfer between the mode and the medium. Indeed, the observed radiation temperature corresponds to the gas temperature at local optical depth τ = 1. But optical depth depends on opacity, which non-linearly depends on temperature. Therefore, the temperature fluctuations due to the oscillating mode entails opacity fluctuations, which in turn impacts the “observed” radiation temperature. Given the non-linear nature of the κ − T relation, this modulation decreases the observed temperature fluctuations more significantly in the low-frequency wing of the mode than in its high-frequency wing. Since this radiative transfer does not impact the velocity measurements, this could explain the asymmetry reversal between velocity and intensity spectra. Using 3D simulations, Georgobiani et al. (2003) computed mode line profiles in both the velocity and the intensity power spectrum alternatively at mean unity optical depth and instantaneous unity optical depth. Their results indeed show that the modulation of the “observed” intensity fluctuations due to radiative transfer could be significant enough to reverse the sense of mode asymmetry. One of the hypothesis enjoying the most support for asymmetry reversal, however, is based on the effect of turbulent perturbations partially correlated with the mode, which thus impact its line profile (Nigam et al. 1998; Roxburgh & Vorontsov 1997; Rast & Bogdan 1998; Kumar & Basu 1999). Indeed, a part of these perturbations is coherent with the mode and, thus, leads to interference. This interference term may be constructive or destructive, depending on the phase difference between the mode and the coherent turbulent perturbations. For frequencies at which the interference is constructive, the power spectral density is slightly elevated, whereas it drops slightly for frequencies at which it is destructive. Typically, in the vicinity of a resonant mode, the dependence of the phase difference between mode and turbulent perturbation is such that the interference term is constructive for frequencies located in one wing of the mode and destructive in the other. Therefore, as a result of this interference behaviour, one of the wings falls off more slowly and the other more rapidly, leading to mode asymmetry. It has been suggested that the degree of correlation between the turbulent perturbations and the oscillation it excites is higher in intensity than in velocity, so that it changes the sign of mode asymmetry only in the intensity spectrum. While it is widely accepted that correlated turbulent perturbations must be taken into account to explain asymmetries in the intensity spectrum, the question of whether it has a significant impact on the velocity spectrum remains an open issue (see e.g. Jefferies et al. 2003).

2016MNRAS.458.1504S__Wang_et_al._2012_Instance_1

The energy levels calculated by Fritzsche, Fischer & Fricke (1998) with grasp92 code are more closer to the NIST values as compared with other calculations within 3.6 per cent for the levels in the ground configurations. Our calculated MCDF energies agree well with NIST data within 6.8 per cent and the maximum error appears for ground state configuration (3s23p3) levels. The average percentage difference between our grasp1 energies and the measured values is 1.9 per cent. For the lowest 41 energy levels, we see that our calculated energies and previous fac energies (Landi & Bhatia 2010; Wang et al. 2012) belonging to the n = 3 complex in Ni xiv agree well with each other and both set of calculation are of the same accuracy. However, our calculated ground state configuration levels show better agreement with measured energies in comparison to those of fac calculations (7.2 per cent). When compared to MCDF calculations performed by Aggarrwal, Keenan & Msezane (2003) with grasp Dyall et al. (1989) code using a model of 14 configurations, our grasp1 levels in the excited configurations lie closer to the NIST ones. In the case of four energy levels (2D5/2,3/2,4P5/2,3/2), our calculated energy levels are more closer to NIST than those of Aggarrwal et al. (2003). The average percentage difference of these grasp energies with NIST values is 2.2 per cent, and the maximum error of 6.3 per cent appears for the first excited state (2D3/2) of ground configuration. For more accurate target states we adopt a model of 13 electronic configurations which yields target-states energies as closer to NIST values as possible. For instance, our calculated energy levels 2D3/2,5/2 associated with the configuration 3s3p4 lie more closer to the observed values as compared to existing calculations. The remaining set of energy levels are almost of the same accuracy as those of previous data when compared to experimental energies. From this comparison it is evident that present grasp1 calculated N-electron target wavefunctions demonstrate good agreement with experimental values, which is necessary for more accurate PI cross-sections of Ni xiii.

2018AandA...618A..24V__Reeth_et_al._2015_Instance_1

Gamma Doradus (γ Dor) stars, with 1.4 M⊙ ≲ M* ≲ 2.0 M⊙, and slowly-pulsating B-type (SPB) stars, with 2.5 M⊙ ≲ M* ≲ 8 M⊙, exhibit high-order gravity-mode (g-mode) pulsations, gravito-inertial pulsations (Van Reeth et al. 2016), and/or purely inertial pulsations, such as r-modes (Saio et al. 2018). The restoring forces for gravity-modes and purely inertial pulsation modes are buoyancy and the Coriolis force, respectively. In the case of gravito-inertial pulsation modes, both forces contribute. As predicted by asymptotic theory, the pulsation periods for γ Dor and SPB stars were observed to form period spacing patterns (e.g. Chapellier et al. 2012; Chapellier & Mathias 2013; Kurtz et al. 2014; Bedding et al. 2015; Saio et al. 2015; Van Reeth et al. 2015; Ouazzani et al. 2017). The pulsation periods are equidistant in the asymptotic regime (with radial order n ≫ spherical degree l) for a non-rotating chemically homogeneous star (Tassoul 1980). Chemical gradients in the deep stellar interior cause pulsation mode trapping, which introduces non-uniform variations in the spacings (Miglio et al. 2008). On the other hand, the stellar rotation leads to shifts in the observed pulsation mode frequencies (Bouabid et al. 2013; Salmon et al. 2014; Van Reeth et al. 2015; Moravveji et al. 2016). For slowly rotating stars, the observed pulsation modes are split into frequency multiplets that depend on the mode identification. For moderate to fast rotators, that is, with rotation in the order of or more than 20% of the critical rotation rate, the observed period spacing patterns have a clear slope (e.g. Van Reeth et al. 2016; Ouazzani et al. 2017). Prograde (azimuthal order m > 0) and zonal modes have a downward slope, that is, the spacing between consecutive pulsation periods decreases with increasing pulsation period, i.e. radial order n. The period spacing patterns of retrograde modes (with m 0) mostly have an upward slope. For stars with detected period spacing patterns, this has been exploited to derive the near-core stellar rotation (e.g. Kurtz et al. 2014; Saio et al. 2015, 2018; Triana et al. 2015; Murphy et al. 2016; Schmid & Aerts 2016; Van Reeth et al. 2016; Ouazzani et al. 2017).

2017MNRAS.469.2720G__Maoz_et_al._2005_Instance_1

With all this in mind, our last question is: What powers soft X-rays and [O III] in LINERs? This has no clear answer, but both are not tracing the same mechanism, since none of them match in morphologies. This is a clear difference between type-2 Seyferts and LINERs. In favour of the soft X-ray emission being originated by AGN photoionization, the RGS spectra studied by Gonzalez-Martin et al. (2010b) showed that in at least 30 per cent of their sample, a contribution of photoionization by the AGNs is required due to the presence of radiative recombination continua (RRC) from CV emission line. However, this does not guarantee a dominance of this emission mechanism. Moreover, cone-like morphologies at soft X-rays in some objects in this study point out again to the photoionization by the AGNs being responsible for the soft X-ray emission. Nevertheless, this assumes that we are seing LINERs with an LOS perpendicular to the accretion disc, which might not be the case. Indeed, the ultraviolet and X-ray variability detected for many of these LINERs (Maoz et al. 2005; Hernández-García et al. 2015) is in favour of a direct view of the AGNs (i.e. perpendicular to the disc under the UM). This is consistent with the fact that most of the [O III] morphologies found for LINERs are spheroids, if we assume that the [O III] traces the NLR. In addition, the fact that we detected a clear correspondence between soft X-ray and [O III] morphologies only in objects with log (LHX)>40, and also that all the objects where soft X-rays and [O III] match their morphologies seem to better follow the previously found relation between the size of the region and the hard X-ray luminosity (see Fig. 2 and Section 5.2), may argue in favour of the scenario in which the AGNs do not have enough thrust to ionize in the low-luminosity regime (Elitzur & Shlosman 2006; Elitzur & Ho 2009), ruling out photoionization by the AGNs at both soft X-ray and [O III] emissions. In this case, the most reasonable explanation for the [O III] is the host galaxy emission, which, anyhow, could also be on top of the AGNs, preventing its detection and erasing the connection (González-Martín et al. 2014). The host galaxy can contribute either as star formation or shocks to the total [O III] emission. Regarding the soft X-ray origin, Mingo et al. (2014) confirmed that jets are the main responsible for soft X-ray emission from their sources. In our sample, jets are identified in NGC 1052 (Kadler et al. 2004), where the jet position angle would be consistent with the extended soft X-ray emission shown here.

2018AandA...615A..57M__Remillard_&_McClintock_2006_Instance_1

A huge amount of data at all wavelengths has been collected in the past 20 years on black hole X-ray binaries, hereafter XrBs (for a global review see Dunn et al. 2010). These objects spend most of their time in quiescence at very low accretion rates, but occasionally, they produce outbursts that last from a few months to a year. Their flux then rises by several orders of magnitude across the whole electromagnetic spectrum (see, e.g., Corbel et al. 2004, Fender et al. 2006; Remillard & McClintock 2006; Done et al. 2007, for recent reviews). During an outburst, XrBs show very different spectral and temporal states that can be easily distinguished in a hardness-intensity diagram (HID) where the X-ray luminosity is plotted versus the hardness ratio of the X-ray spectrum (see, e.g., Homan et al. 2001; Fender et al. 2004). The evolutionary track produces a typical q-shaped figure that reveals a hysteresis: outbursting XrBs have two distinct spectra with the same X-ray luminosity above 1–2% Eddington luminosity. At the beginning of the outburst, the system is in the so-called hard state: the spectrum has a hard power-law shape up to a few tens to hundreds of keV, requiring a very hot, optically thin plasma (referred to as the “corona”). Then, when the system reaches high luminosities (up to a few tens of the Eddington luminosity), it transits within a few days through a bright intermediate state into the so-called soft state (referred to as the “cold disk”). In this state, the spectrum is dominated by strong and soft X-ray emission, which is commonly interpreted as thermal emission from an optically thick geometrically thin accretion flow. In the latter state, the luminosity starts to decrease and the system returns to the hard state, transiting through a faint intermediate state. The luminosities at which a system transits from hard to soft states are several times higher than the luminosity of the reverse transition (see Appendix in Dunn et al. 2010).

2021MNRAS.501.2897G__Pribulla_&_Rucinski_2006_Instance_2

EE Cet (ADS 2163 B) is the southern (slightly fainter) component of the visual binary WDS 02499+0856 (Mason et al. 2001). It was discovered by the HIPPARCOS mission (Perryman et al. 1997), by noticing the variability of the combined light of both visual components. Lampens et al. (2001) performed photometric measurements of the visual pair and gave (but only for one epoch) the following values V(A) = 9.47 mag and V(B) = 9.83 mag. Pribulla & Rucinski (2006) lists the orbital parameters (orientation and separation) of WDS 02499+0856 and gave θ = 194°, ρ = 5.66 arcsec and magnitude difference ΔV = 0.07 mag (the magnitude difference can be as large as ΔV = 0.36 mag, due to photometric variability of the eclipsing binary). WDS 02499+0856 turned out to be a quadruple system, when the northern component was found to be a double-lined (SB2) binary from the DDO spectroscopic observations (Pribulla & Rucinski 2006). D’Angelo et al. (2006) re-confirmed the multiplicity of the system, and listed it among the contact binaries with additional components. Radial velocity observations from Rucinski et al. (2002) resulted in a well-defined circular orbit of the contact binary, with K1 = 84.05 km s−1, K2 = 266.92 km s−1 (q = 0.315), and an F8V spectral type. Karami & Mohebi (2007) using their own velocity curve analysis method, arrived at almost identical results for the mass ratio. Djurašević et al. (2006) presented the first model, resulting in orbital inclination of i = 78.5° and a fill-out factor of f = 32.69 per cent, T2 = 6314 K, and T1 = 6095 K, when spots were added. Their no-spot model resulted in very close value for the fill-out factor but slightly different geometrical and orbital parameters. The physical parameters derived in this study were: M1 = 1.37 M⊙, M2 = 0.43 M⊙, and mean radii R1 = 1.35 R⊙, R2 = 0.82 R⊙. It is worth noting here that the light curves analysed by these authors included the visual component in the photometric aperture with a contamination of about 54 per cent.

2016ApJ...833..216G__Gopalswamy_et_al._2014a_Instance_1

SEP events with gigaelectronvolt particles are generally rare. Typically about a dozen events occur during each solar cycle, although only two GLEs were reported in cycle 24, probably due to the change in the state of the heliosphere (Gopalswamy et al. 2013a, 2014a; Thakur et al. 2014). It appears that the 2012 July 23 event would have been another GLE event if it had occurred on the front side of the Sun. The purpose of this paper is to examine the event from the perspectives of CME kinematics, SEP intensity and spectrum, and radio-burst association to see if the 2012 July 23 event can be considered as an extreme particle event. The reason for considering these properties is clear from the following facts. Particles up to gigaelectronvolt energies are accelerated by strong shocks driven by CMEs of very high speeds (∼2000 km s−1) and intense, soft X-ray flares (see Gopalswamy et al. 2010, 2012b). The high speed is typically attained very close to the Sun, so the density and magnetic field in the corona are high for efficient particle acceleration (e.g., Mewaldt et al. 2012; Gopalswamy et al. 2014a). The high CME speed implies that a fast-mode MHD shock forms close to the Sun, as indicated by the onset of metric type II radio bursts, typically at heights 1.5 solar radii (Rs). CMEs attaining high speeds near the Sun have to accelerate impulsively, so these events are characterized by high initial acceleration (∼2 km s−2, see Gopalswamy et al. 2012b). This is in contrast to slowly accelerating CMEs (from filament regions outside active regions) that form shocks at large distances from the Sun and do not accelerate particles to energies more than a few tens of megaelectronvolts (Gopalswamy et al. 2015a, 2015d). Accordingly, the SEP spectra of such events are very soft, as opposed to the hard spectra of GLE events. Whether an event has a soft or hard spectrum is important information because the hard-spectrum events have stronger space weather impacts (see, e.g., Reames 2013). SEP events with gigaelectronvolt components are accompanied by type II radio bursts from meter (m) wavelengths to kilometer (km) wavelengths (Gopalswamy et al. 2005b, 2010). Type II bursts occurring at such wide-ranging wavelengths imply strong shocks throughout the inner heliosphere (Gopalswamy et al. 2005a).

2016ApJ...833..216G___2010_Instance_2

SEP events with gigaelectronvolt particles are generally rare. Typically about a dozen events occur during each solar cycle, although only two GLEs were reported in cycle 24, probably due to the change in the state of the heliosphere (Gopalswamy et al. 2013a, 2014a; Thakur et al. 2014). It appears that the 2012 July 23 event would have been another GLE event if it had occurred on the front side of the Sun. The purpose of this paper is to examine the event from the perspectives of CME kinematics, SEP intensity and spectrum, and radio-burst association to see if the 2012 July 23 event can be considered as an extreme particle event. The reason for considering these properties is clear from the following facts. Particles up to gigaelectronvolt energies are accelerated by strong shocks driven by CMEs of very high speeds (∼2000 km s−1) and intense, soft X-ray flares (see Gopalswamy et al. 2010, 2012b). The high speed is typically attained very close to the Sun, so the density and magnetic field in the corona are high for efficient particle acceleration (e.g., Mewaldt et al. 2012; Gopalswamy et al. 2014a). The high CME speed implies that a fast-mode MHD shock forms close to the Sun, as indicated by the onset of metric type II radio bursts, typically at heights 1.5 solar radii (Rs). CMEs attaining high speeds near the Sun have to accelerate impulsively, so these events are characterized by high initial acceleration (∼2 km s−2, see Gopalswamy et al. 2012b). This is in contrast to slowly accelerating CMEs (from filament regions outside active regions) that form shocks at large distances from the Sun and do not accelerate particles to energies more than a few tens of megaelectronvolts (Gopalswamy et al. 2015a, 2015d). Accordingly, the SEP spectra of such events are very soft, as opposed to the hard spectra of GLE events. Whether an event has a soft or hard spectrum is important information because the hard-spectrum events have stronger space weather impacts (see, e.g., Reames 2013). SEP events with gigaelectronvolt components are accompanied by type II radio bursts from meter (m) wavelengths to kilometer (km) wavelengths (Gopalswamy et al. 2005b, 2010). Type II bursts occurring at such wide-ranging wavelengths imply strong shocks throughout the inner heliosphere (Gopalswamy et al. 2005a).

2022MNRAS.516.2500C__Lin_et_al._2009_Instance_2

Neutron star X-ray binaries are an important class of low-mass X-ray binaries to understand the radiative and dynamical configuration of the inner region of an accretion disc. Though from previous studies especially based on RXTE (Rossi X-ray Timing Explorer) data of Z sources, it was known that there must exist a corona/comptonization region to explain the observed hardtail in their X-ray spectra but the exact location and how it changes across the intensity variation is not yet properly understood. Among the two primary categories i.e. Z and Atoll sources, Z sources emit close to the Eddington luminosity (0.5–1.0 LEdd; Done, Gierliński & Kubota 2007a) and they exhibit ‘Z’ and ‘C’ shape intensity variation in the hardness intensity diagram (HID) or colour–colour diagrams (CCDs; Hasinger & Van der Klis 1989; Van der Klis 2006). The Z shape variation constitutes a horizontal branch (HB) at the top, a flaring branch (FB) at the bottom, and a normal branch (NB) connecting them diagonally. These are further classified into two broad groups, namely Sco and Cyg-like sources, due to their different appearance exhibited by the HB and FB i.e. less vertical orientation of HB and a weaker FB is seen among Cyg-like sources than in Sco-like (Kuulkers et al. 1994). The hybrid source XTE J1701–462 occupies a special place among NS LMXBs and is considered to be a remarkable source, as it displays all the characteristics exhibited by both Z and atoll sources (Homan et al. 2010, 2007; Lin et al. 2009). At the brightest state, the intensity variations were associated with HB, NB, and FB of Cyg-like and exhibited Sco-like variation at relatively lower brightness. During the decay phase, the variation closely resembles the soft state of an atoll source and later transits to the hard state of the atoll source just before going to the quiescent state. Many important results were noticed based on the spectral fitting of RXTE data of this source. The mass accretion rate was found to be constant along with the Z phase in Sco-like variation and different mechanisms were proposed to explain the spectral and timing variations during the Z phase variations (Lin et al. 2009). It was also found that mass accretion rate is the important driving parameter during the Z and all along with the atoll phases variation. Z sources are unique probes in the sense they provide a platform to understand the structure of accretion disc emitting close to Eddington luminosity because due to the radiation pressure the structure of the inner region of accretion is affected. The previous studies suggested that the interplay between the accretion disc and comptonization region mutually varies to produce the observed tracks in the HID. However, other physical components like a boundary layer (Popham & Sunyaev 2001) or a transition layer (TL) (Osherovich & Titarchuk 1999a, b; Titarchuk & Osherovich 1999) cannot be ruled out. The comptonization region can be in the form of a quasi-spherical cloud or it could be a base of a jet that causes the observed hard continuum in the X-ray spectrum (Migliari et al. 2007). But its association with dynamical features like various branch oscillations or band-limited noises is not known. The spectra of Z sources can also be explained by a structure known as the boundary layer over the NS surface but again, its association to the observed HBO, NBO, etc., is not properly understood (Popham & Sunyaev 2001; Gilfanov, Revnivtsev & Molkov 2003; Revnivtsev & Gilfanov 2006). Based on the detailed spectral modelling of GX 17 + 2, BL occupies a smaller area at the lower vertex (i.e. bottom of NB) in comparison to its area in other branches (Lin et al. 2012) and the comptonization dominates at the HB branch that fades away as source traverse to the FB. The inner disc radius was found to be moving towards the NS, as the Z track evolves from HB to FB. All these structural and radiative variations are found to be occurring at an almost constant mass accretion rate (Lin et al. 2009, 2012).

2022MNRAS.515.1276C__Regály_et_al._2012_Instance_1

Vortex formation in protoplanetary discs has been shown to proceed through various mechanisms. Klahr & Bodenheimer (2003) demonstrated that in discs with a radial entropy gradient, azimuthal perturbations are baroclinically unstable and can lead to the formation of vortices. The most commonly invoked mechanism to form a large-scale vortex in a protoplanetary disc is the Rossby wave instability (RWI). The RWI can be triggered at steep radial density gradients (Lovelace et al. 1999; Li et al. 2000, 2001); such a gradient may be generated at the viscosity transition between regions in which the magnetorotational instability can operate (e.g. Varnière & Tagger 2006; Lyra et al. 2009b; Lyra & Mac Low 2012; Regály et al. 2012). Steep radial density gradients are also found at the outer edge of a gap carved in the disc by a giant planet. Indeed, hydrodynamics simulations of protoplanetary discs containing a giant planet have successfully produced large-scale vortices (e.g. Li et al. 2005; Masset et al. 2006; de Val-Borro et al. 2007; Meheut et al. 2010; Lin & Papaloizou 2011; Lin 2012), and Regály, Juhász & Nehéz (2017) presented a comparison of vortices formed at a gap edge to those formed at a viscosity transition. However, Hammer, Kratter & Lin (2017) pointed out that the short growth time-scales of the giant planet prescribed in these simulations result in unphysically large perturbations that are capable of setting up the RWI-unstable density gradient at the gap’s outer edge. When the giant planet is grown over more realistic time-scales, vortex production is significantly suppressed because viscosity has time to smooth out any steep gradients and the planetary torque itself can reshape the gap edge. Under the most favourable conditions for vortex formation, vortex lifetimes were found to be limited. One may then argue that if these asymmetries are indeed vortices formed through the RWI triggered by giant planets, we must be seeing them just after the planet has formed. However, if a RWI-generated vortex typically survives for ∼103 orbits and discs are ∼105 orbits old, observing the vortex so soon after its formation is unlikely. It is therefore uncertain whether the non-axisymmetric substructures seen in observations can be explained by this mechanism.

2021AandA...646L...4I__Zheng_et_al._2014_Instance_1

Our initial sample comprised all 40 stars of the MMT-HVS survey that were revised by Kreuzer et al. (2020), together with 30 runaway stars from the collection of Silva & Napiwotzki (2011) for which we were able to obtain spectra. This covers the majority of objects with high ejection velocities in that compilation. This group was complemented by the prototype hyper-runaway star HD 271791 (Heber et al. 2008), the potential hyper-runaway stars SDSS J013655.91+242546.0 (J0136+2425 for short, Tillich et al. 2009) and HIP 60350 (Irrgang et al. 2010), the extreme disk-runaway star PG 1610+062 (Irrgang et al. 2019), the four candidate HVSs from the LAMOST survey (Zheng et al. 2014; Huang et al. 2017; Li et al. 2018), and the probable Hills star S5-HVS 1 (Koposov et al. 2020). Based on proper motions from Gaia EDR3, we then carried out spectroscopic and kinematic analyses (see Sects. 3 and 4 for details) of all members of this initial sample to filter out those with both a high ejection velocity and a relatively well-constrained origin within the Galactic disk. In order to account for the fact that massive stars are typically ejected at lower velocity, we chose a mass-dependent threshold for the deduced 1σ upper limit of the ejection velocity, that is, 400 km s−1 or 320 km s−1 for stars with masses below or above 5 M⊙, respectively. The first cut applies to almost all stars from the MMT-HVS survey, while most of the others fall into the second category. The chosen thresholds roughly represent the limits for the classical ejection scenarios (see, e.g., Tauris 2015; Irrgang et al. 2018a, and references therein). A disk origin was granted when the 1σ lower limit of the inferred galactocentric plane-crossing radius was below 25 kpc (motivated by Xu et al. 2015), while visual inspection was used to judge whether the origin was sufficiently well constrained. These criteria left us with 14 stars from the MMT-HVS survey, 7 stars from the Silva & Napiwotzki (2011) sample, all 4 stars from the LAMOST survey, and the 5 individual targets mentioned above, yielding a final sample of 30 program stars, the names of which are listed in Table 1.

2020ApJ...899..147F__Venot_et_al._2015_Instance_1

The C/O ratio varies across exoplanets’ host star populations (Delgado Mena et al. 2010; Brewer & Fischer 2016; Brewer et al. 2017), and this variation is likely to be reflected in the composition of exoplanet atmospheres, assuming that they are formed with the same materials as their stars. Moreover, various processes in the protoplanetary disks and the planet formation process can affect the exoplanet compositions and have a significant impact on the final C/O ratio (Öberg et al. 2011; Mordasini et al. 2016; Espinoza et al. 2017; Madhusudhan et al. 2017). For these reasons, it is necessary to consider the effects of the C/O ratio on the atmospheric chemistry and the formation of aerosols. Numerous studies have been performed using chemical models (Madhusudhan 2012; Moses et al. 2013; Venot et al. 2015; Tsai et al. 2017; Heng & Lyons 2016; Goyal et al. 2018; Drummond et al. 2019), but corresponding laboratory experiments are still largely nonexistent. Laboratory investigations can provide essential insight into the effects of the C/O ratio on the atmospheric photochemistry and the formation of aerosols. In a previous work, we performed the first laboratory experiments dedicated to the study of the chemistry in hot Jupiter atmospheres (Fleury et al. 2019). This work focused on the chemistry in atmospheres with T > 1000 K and a C/O ratio of 1 (representing C enhancement compared to the solar value of 0.54), because chemical models predict that the abundances of hydrocarbon and nitrile species increase by several orders of magnitude in these atmospheres compared to atmospheres with a low C/O ratio (Venot et al. 2015). Therefore, they can be considered as better candidates for the formation of complex organic molecules with longer carbon chains. This first study revealed that photochemical aerosols could be produced at temperatures as high as 1500 K and that water could be efficiently formed through photochemical channels. In the present work, we performed new experiments to study the chemistry in hot Jupiter atmospheres at similar temperatures (1173–1473 K) but with lower C/O ratios. We used a gas mixture of H2, H2O, and CO that represents the simplest plausible atmosphere for a hot Jupiter with a C/O ratio 1. This new study, compared with our previous work, allows us to assess the evolution of the chemistry in hot Jupiter atmospheres as a function of the C/O ratio and atmospheric composition.

2019AandA...632A.104G__Hirabayashi_et_al._2016_Instance_3

Finally, our observations are consistent with the bilobate shape of the nucleus of comet 8P/Tuttle. As noted in Sect. 1, this shape is likely common among comets because it was found for four out of the six comets for which we have spatially resolved images. This is also the case of the trans-Neptunian object 2014 MU69 (Ultima Thule) observed by the New Horizon spacecraft (Stern et al. 2019). This binary configuration has some implications for the formation and evolution of 8P/Tuttle. A contact binary could result from (i) the accretion at low velocity of two primordial objects (Massironi et al. 2015; Davidsson et al. 2016), (ii) the disruption of a monolithic object due to excessive spin-up resulting from non-gravitational forces or YORP5 effect followed by a reaccretion (Boehnhardt 2004; Ćuk 2007; Hirabayashi et al. 2016), or (iii) the catastrophic disruption of a monolithic object by a collision followed by a re-accretion (Jutzi & Benz 2017; Schwartz et al. 2018). On the one hand, with a low thermal inertia compared with NEAs, the YORP effect is low for comets, in particular for NIC, which have an elongated orbit and spend most of their time far from the Sun, and it may not be sufficient to increase the spin rate of the nucleus to the point where centrifugal exceed gravitational forces. On the other hand, comet 8P/Tuttle has been on a very stable orbit for centuries, and it is likely an evolved comet, as suggested by its low activity, so that it could have been much more active in the past. For cometary nuclei, the primary cause for spin-up is torques caused by outgassing, therefore it is possible that 8P/Tuttle formed as a monolithic body and became a contact binary after its injection into the inner Solar System as a result of excessive spin-up resulting from non-gravitational forces. This scenario has been proposed for comet 67P/Churyumov-Gerasimenko by Hirabayashi et al. (2016). Alternatively, if the binary nature of comet 8P/Tuttle is the result of a primordial accretion or a catastrophic collision in the early Solar Sytem, it could have persisted until now. Similar examples are offered by some binary asteroids that can be stable over the age of the Solar System (Chauvineau et al. 1991), or as proposed by Davidsson et al. (2016) for comet 67P/Churyumov-Gerasimenko. For comet 8P/Tuttle, it is however not possible to distinguish the solution of a binary nucleus that formed in the first billion years of our Solar System (e.g., Matonti et al. 2019) from a more recent origin following its injection into the inner Solar System (e.g., Hirabayashi et al. 2016).

2020AandA...643A.178T__Friesen_et_al._(2016)_Instance_1

Most of the clumps analyzed in this study lie in the optimal range of precise Tkin determination when using NH3 (1,1) and (2,2) lines (see Sects. 1 and 3.3). Figure 8 indicates that there is a large number of cold clumps with Tkin 20 K. The gas and dust are expected to be coupled at densities above about 104.5 or 105 cm−3 (Goldsmith 2001; Young et al. 2004). The temperatures derived from dust and gas are often in agreement in the active and dense clumps of Galactic disk clouds (Dunham et al. 2010; Giannetti et al. 2013; Battersby et al. 2014; Merello et al. 2019). This is also the case for Serpens South. Low gas temperatures are associated with Serpens South ranging from 8.9 to 16.8 K with an average of 12.3 ± 1.7 K, which is consistent with the mean value of 11 ± 1 K found by Friesen et al. (2016). The gas and dust temperatures (mean and standard deviations Tgas,avg ~ 12.3 ± 1.7 K versus Tdust,avg ~ 13.4 ± 0.9 K) scatter in Serpens South, but agree reasonably well as can be most directly seen in the right panel of Fig. 8 (blue points). However, in the HMSF region W 40, we find that the measured gas kinetic temperatures are higher than the dust temperatures (mean and standard deviations Tgas,avg ~ 25.1 ± 4.9 K versus Tdust,avg ~ 19.1 ± 2.2 K), which indicates that the gas and dust are not well-coupled in W 40 and that the dust can cool more efficiently than the gas. This is consistent with the relatively weak NH3 lines associated with the core region of W 40, indicating the presence of only small amounts of dense gas. This illustrates that the interplay between gas and dust cooling and heating is not uniform in the area covered by our observations. Such a difference between Tgas and Tdust is also seen in other regions and appears to be an often encountered property of massive-star formation regions. Battersby et al. (2014) and Koumpia et al. (2015) compare gas and dust temperatures in the massive-star-forming infrared dark cloud G32.02+0.05 and the high-mass-star-forming PDR S140, respectively, and find similar discrepancies between gas and dust temperatures. This likely indicates a lack of coupling between the gas and dust (Battersby et al. 2014) or could be due to the clouds beingclumpy (Koumpia et al. 2015). These may be potential mechanisms relevant to W 40, where the gas temperature is higher than the dust temperature.

2021MNRAS.500.3083C__Lupi_&_Bovino_2020_Instance_1

Previous theorethical studies have outlined that the [C ii] emission originates from the cold (with temperatures of a few 100 K) neutral medium and from photo-dissociation regions (PDR, Vallini et al. 2013). This seems to suggest that its presence closely traces star formation sites, resulting in a linear relation, as found by De Looze et al. (2014) and Herrera-Camus et al. (2015). While at low-redshift and close to solar metallicity such a relation is well established, as shown by several observations (De Looze et al. 2014; Herrera-Camus et al. 2018) and also numerical simulations (see, e.g. Lupi & Bovino 2020), significant deviations can arise in different ISM conditions, like at lower metallicity or in presence of a strong ionizations field, that are more typically found in the high-redshift Universe. To address the impact of such conditions, several studies have analysed the [C ii] emission from typical high-redshift galaxies, by post-processing hydrodynamic zoom-in cosmological simulations with cloudy (Ferland et al. 2017; see, e.g. Olsen et al. 2017; Pallottini et al. 2017, 2019; Katz et al. 2019), or via ad-hoc methods, as in Arata et al. (2020), or also via on-the-fly non-equilibrium chemistry (Lupi et al. 2020). The main conclusion in all these studies is that a [C ii] deficit exists at high redshift, most likely due to the starbursting nature of these galaxies rather than their metallicity, since most of these systems are close to solar (see, e.g. Vallini et al. 2015; Lupi & Bovino 2020). Other studies have evidenced a weak dependence of [C ii] on metallicity. Harikane et al. (2020) showed that the L[C ii]/SFR ratio does not show a strong dependence on metallicity, which to first approximation was interpreted as the result of the proportionality between C abundance and metallicity Z and an inverse proportionality between PDR column density and Z in a dust-dominated shielding regime (Kaufman, Wolfir & Hollenbach 2006). In this framework, if PDR give a large conribution to the [C ii] emissivity, the [C ii] luminosity is not expected to strongly depend on Z (see also Ferrara et al. 2019; Pallottini et al. 2019).

2018ApJ...856...65W__Betoule_et_al._2014_Instance_1

Improvements in cosmological measurement in recent years have been said to hail an era of “precision cosmology,” with observations of the cosmic microwave background (CMB) temperature anisotropies (Hinshaw et al. 2013; Planck Collaboration et al. 2016a, 2016b), baryon acoustic oscillation (BAO) wiggles in the galaxy power spectrum (Beutler et al. 2011; Anderson et al. 2014; Ross et al. 2015), luminosity distance–redshift relation of Type Ia supernovae (SNIa; Riess et al. 2004, 2007; Kowalski et al. 2008; Betoule et al. 2014), local distance ladder (Riess et al. 2016), galaxy clustering and weak lensing (DES Collaboration et al. 2017), and direct detection of gravitational waves (Abbott et al. 2017), providing constraints on cosmological model parameters at percent, or subpercent, level precision. Since the discovery of the accelerated expansion of the universe, these observations have cemented the emergence of the flat ΛCDM model as the standard model of cosmology, in which global spatial curvature is zero, and the energy budget of the universe is dominated by “dark energy” in the form of a cosmological constant, Λ. However, beyond the ΛCDM paradigm, there is a large number of dark energy models aimed at explaining the accelerated expansion of the universe (see reviews by Li et al. 2011 and Joyce et al. 2015, and references therein), and so understanding the nature of dark energy remains one of the central pursuits in modern cosmology. To this end, it has become common observational practice to constrain the dark energy equation of state, w(z), and check for deviations from the ΛCDM value of w = const. = −1. While observational probes do not indicate any significant departure from ΛCDM (Huterer & Shafer 2017), there is still room to tighten constraints and thereby rule out competing alternatives for dark energy. In particular, by tuning the parameters of alternative theories of dark energy, one can recover the behavior of the ΛCDM model at both the background expansion and perturbation levels (Li et al. 2011; Joyce et al. 2015).

2020ApJ...898...25T__Pavlovskii_et_al._2017_Instance_1

Recent detections of gravitational waves (GWs) have shown evidence for a high rate of black hole (BH)–BH and neutron star (NS)–NS mergers in the universe (Abbott et al. 2016a, 2016b, 2017a, 2017b, 2017c, 2019a; Zackay et al. 2019, 2020; Venumadhav et al. 2020). However, the proposed astrophysical pathways to mergers remain highly debated. Possible compact-object merger pathways include isolated binary evolution (Dominik et al. 2012; Kinugawa et al. 2014; Belczynski et al. 2016, 2017; Breivik et al. 2016; Giacobbo et al. 2018; Bavera et al. 2019; Spera et al. 2019) accompanied by mass transfer (Inayoshi et al. 2017a; Pavlovskii et al. 2017; van den Heuvel et al. 2017), common-envelope ejection (e.g., Paczynski 1976; Ivanova et al. 2013), envelope expansion (Tagawa et al. 2018), or chemically homogeneous evolution in a tidally distorted binary (de Mink & Mandel 2016; Mandel & de Mink 2016; Marchant et al. 2016), evolution of triple or quadruple systems (Antonini et al. 2017; Liu & Lai 2017, 2018, 2019; Silsbee & Tremaine 2017; Arca-Sedda et al. 2018; Hoang et al. 2018b; Randall & Xianyu 2018; Fragione & Kocsis 2019; Fragione et al. 2019; Michaely & Perets 2019), gravitational capture (O’Leary et al. 2009; Kocsis & Levin 2012; Gondán et al. 2018b; Rodriguez et al. 2018; Rasskazov & Kocsis 2019; Zevin et al. 2019; Samsing et al. 2020), dynamical evolution in open clusters (Banerjee 2017, 2018a, 2018b; Bouffanais et al. 2019; Kumamoto et al. 2019; Rastello et al. 2019) and dense star clusters (e.g., Portegies Zwart & McMillan 2000; O’Leary et al. 2006, 2016; Samsing et al. 2014; Ziosi et al. 2014; Mapelli 2016; Rodriguez et al. 2016a, 2016b; Askar et al. 2017; Fujii et al. 2017; di Carlo et al. 2019; Zevin et al. 2019; Zhang et al. 2019), and dynamical interaction in gas-rich nuclear regions (McKernan et al. 2012, 2014, 2018; Bellovary et al. 2016; Bartos et al. 2017; Stone et al. 2017; Leigh et al. 2018; Tagawa & Umemura 2018; Yi et al. 2018; Secunda et al. 2019; Yang et al. 2019a, 2019b; Gayathri et al. 2020; McKernan et al. 2020; Tagawa et al. 2020).

2020AandA...640L..11B__Segretain_1996_Instance_3

Another possibly important cooling delay may arise from the phase separation of 22Ne during crystallization (Isern et al. 1991; Althaus et al. 2010). Our current best understanding is that at the small 22Ne concentrations typical of C/O white dwarfs (∼1% by number), the presence of 22Ne should not affect the phase diagram, except near the azeotropic point of the C/O/Ne phase diagram. Thus, the crystallization of the C/O core initially proceeds as in the case without 22Ne with no redistribution of neon ions between the solid and liquid phases. After a significant fraction of the core has crystallized, the temperature approaches the azeotropic point and the existing calculations indicate that the liquid phase is enriched in 22Ne relative to the solid (Segretain 1996; García-Berro et al. 2008). The 22Ne-poor solid is lighter than the surrounding liquid and floats upward where it eventually melts. This gradually displaces the 22Ne-rich liquid downward toward the solid–liquid interface until the azeotropic composition is reached, thereby releasing a considerable amount of gravitational energy. Given our very limited knowledge of the ternary C/O/Ne phase diagram (Segretain 1996; Hughto et al. 2012), this effect cannot be quantitatively implemented in our evolution models. However, we note that our current understanding of 22Ne phase separation is remarkably consistent with the missing cooling delay. In Fig. 2 we show the luminosity function obtained by adding an artificial 0.6 Gyr delay when 60% of the core is crystallized. These parameters are entirely consistent with those found in preliminary studies (Segretain 1996; García-Berro et al. 2008) and yield an excellent fit to the crystallization pile-up3. Based on the current (albeit limited) knowledge of the C/O/Ne phase diagram, we propose that the phase separation of 22Ne in the advanced stage of crystallization significantly contributes to the pile-up in the luminosity function of 0.9−1.1 M⊙ white dwarfs (Fig. 2).

2021MNRAS.503.1319G__Kochanek_1992_Instance_1

Independent of the traditional redshift surveys, in this work, we constrain the VDF of ETGs using the statistics of strong gravitational lensing systems (Turner et al. 1984; Biesiada 2006; Cao et al. 2012b,c). Assuming the concordance cosmological model (ΛCDM), several efforts have been made to include the distribution of lensed image separations in the study of the galaxy mass profiles and the evolution history of galaxies. Based on the CLASS and PANELS lens sample, the first attempt to constrain the redshift evolution of galaxies (since redshift z ∼ 1) was presented in Chae & Mao (2003). This study was then extended to the study of the shape of the VDF and the characteristic velocity dispersion (Chae 2005). However, the sample size of the data available at that time did not allowed for a firm determination of the galaxy VDF. Here, we present a new approach to derive the VDF based on the lens redshift distribution (Kochanek 1992) and to constrain its evolution out to z ∼ 1, given its strong dependency on the dynamical properties of galaxies (i.e. stellar velocity dispersion) and the number density of gravitational lenses (i.e. galaxy evolution). Compared with the previous works focusing on image separation distributions, constraining a VDF through lens redshift test is unique and promising, since it does not require the knowledge of the total lensing probability and the magnification bias in the sample (Ofek, Rix & Maoz 2003). The advantages of the lens redshift test have been extensively discussed in Matsumoto & Furamase (2008), Koopmans et al. (2009), Oguri et al. (2012), and Cao et al. (2012a). Therefore, it will be rewarding to investigate the VDF and evolution of the lensing galaxies by adopting the cosmological parameters determined by Planck and using a new lens sample better representing the distribution of the galaxy properties. In this work, we focus on a newly compiled sample of 157 galaxy-scale strong lensing systems, which are all early-type lenses (E or S0 morphologies) without significant substructures or close companion galaxies (Chen, Li & Shu 2019). Throughout the paper, we assume the concordance cosmology by adopting the cosmological parameters determined by the Planck 2016 data (Ade et al. 2016).

2022AandA...663A..44K__Blundell_et_al._1999_Instance_1

The remarkably bright nature of radio-jetted active galactic nuclei (AGNs) allows us to observe them at extreme redshifts and thus use their properties as an observational tracer of cosmological principles (Wang et al. 2021). Blazars, in particular, benefit from increased apparent luminosities due to relativistic boosting effects (Cohen et al. 2007b), and can thus be detected over a wide range of the electromagnetic spectrum, although at the cost of being observationally compact objects with small angles between their jets and the line of sight. Conversely, AGNs with radio jets that are at a larger angle to the line of sight are harder to detect with increasing distance. Because they can be observed over such a wide range of redshifts, they provide a unique insight into cosmology, galaxy evolution, and the evolution of AGNs (Dunlop & Peacock 1990; Georgakakis et al. 2017). In addition to probing the universe by observing targets at different redshifts, one should also account for differences in their evolutionary stage, the environment they are embedded in at that time, and their interactions with that environment. Many radio surveys have already been performed to investigate radio-loud AGN populations (e.g. Becker et al. 1995; Condon et al. 1998; Cohen et al. 2007a; Intema et al. 2017) and most find self-consistent relative number ratios of radio galaxies and blazars up to a redshift of ~3 (Volonteri et al. 2011). Beyond this redshift, matters are complicated by uncertainties about the density evolution and the build-up of high black hole masses in the early universe (Blundell et al. 1999; Shankar et al. 2008). However, there seems to be a consensus that there is a relative lack of higher redshift radio galaxies even when accounting for evolutionary effects and detection limits (e.g. Wu et al. 2017; Hodges-Kluck et al. 2021, and references therein). The reason for the deficit is still not fully understood. The currently favoured explanation was suggested by Ghisellini et al. (2015): interaction of the extended radio emission with the cosmic microwave background (CMB) could efficiently quench the brightness of the extended radio lobes. Morabito & Harwood (2018) find evidence to support this model based on a comparison of simulations and observational data. In this scenario the CMB energy density dominates over the magnetic energy density at very high redshifts, so that the jet electrons interact with the CMB photons by inverse Compton (IC) scattering to cool, while the synchrotron radiation is suppressed. Although quenched, the steep-spectrum isotropic radiation of the extended structures could nevertheless be detected by telescopes operating in the long wavelength radio regime, which can test and guide the theoretical models. Ghisellini et al. (2015) proposed a number of suitable blazars to spotlight this issue, and published expected radio fluxes for different model parameters. The International LOFAR Telescope (ILT) (van Haarlem et al. 2013) offers the resolution, sensitivity, and observing wavelengths necessary to detect the extended emission from these blazars and to address the questions associated with its possible suppression. For this study, we processed and analysed one ILT observation of GB 1508+5714 at z = 4.30 (Hook et al. 1995), which is one of the most distant quasars with a detected X-ray jet (Yuan et al. 2003; Siemiginowska et al. 2003). Throughout the paper we use the following cosmological parameters: H0 = 71 km s−1 Mpc−1, Ωm = 0.27, and ΩΛ = 0.73, hence a luminosity distance of 39.8 Gpc and a conversion scale where 1″ is about 6.9 kpc for the given source.

2016AandA...585A..48G__Mostardi_et_al._(2013)_Instance_2

On the same SSA22 field, Nestor et al. (2011) and Nestor et al. (2013) show nine LBGs and 20 Lyman-α emitters (LAEs) with LyC detection out of a sample of 41 LBGs and 91 LAEs (all spectroscopically confirmed). They started from a different narrowband image centred at ~3640 Å, which is deeper than that used by Iwata et al. (2009), at ~3590 Å. A careful analysis of their LBG detections, however, shows that even in this case the LyC emission for many z ~ 3 sources is offset by 0.4–1.0 arcsec. The observed ratio between the 900 and 1500 Å rest-frame emission is difficult to reconcile with that expected by standard stellar populations (Vanzella et al. 2012a). The HST images in I814W filter available for a few of them show the presence of clearly separated galaxies, sometimes fainter at 1500 Å than in the ionizing continuum (i.e. their C16 object), with a resulting escape fraction well exceeding 1000% if estimated in the LyC position. For the majority of them, no HST imaging is available but even ground-based images often show the presence of slightly offset emission in LyC, w.r.t. the non-ionizing continuum. Similar conclusions can be reached for the Mostardi et al. (2013) sample where they adopt the same analysis as in Nestor et al. (2013). At z ~ 2.8, they found four LyC emitters out of 49 LBG galaxies and seven LyC emitters out of 91 LAEs. In this case the lack of high spatial resolution data from HST for the majority of the sample prevents any detailed analysis about possible contamination by interlopers/foregrounds. These conclusions have been strengthened by recent observations by Siana et al. (2015), who found no convincing detection in their deep HST imaging with WFC3-UVIS of five LyC emitters extracted from the sample of Nestor et al. (2011), or by Mostardi et al. (2015), who only found one robust LyC emitter after a reanalysis of a sample of 16 galaxies by Mostardi et al. (2013). More interestingly, the only robust candidate LyC emitter by Mostardi et al. (2015), the galaxy MD5b, has an observed ratio FUV/FLyC = 4.0 ± 2.0, equivalent to a relative escape fraction of 75%, when assuming complete transmission of the IGM. Instead, if a mean value of ⟨ exp(−τIGM) ⟩ = 0.4 at z ~ 3.1 is adopted, following Inoue et al. (2014), the relative escape fraction of MD5b turns out to be 188%. Imposing the constraint of a physical value for the relative escape fraction of \hbox{$f^{\rm rel}_{\rm esc}<100\%$}fescrel100%, the LoS of MD5b must be very transparent, exp(−τIGM) > 0.75, which corresponds to a probability 10-4, according to Inoue et al. (2014). This could be an indication that this galaxy is also a low-z contaminant, similar to the other cases studied by Mostardi et al. (2015).

2019MNRAS.488.4638L__Drabek-Maunder_et_al._2016_Instance_2

In Fig. 10, we plot the variation of the ratio of the outflow contribution to the FWHM and turbulent energy. The ratio of the outflow contribution = 1 – ‘non-outflow contribution’/‘all contributions’. We observe that the outflow has a contribution in the FWHM: about 20 per cent in the local region at the H ii region (non-outflow contribution is about 81 per cent) and about 10 per cent even in the clumps. According to Eturb = (3/16 ln 2)Mcloud × FWHM2, outflow has a contribution in the turbulent energy up to 35 per cent in the local region at the H ii region (1 − 0.812). It has a contribution of at least 15 per cent in the clump at early stages of massive star formation, which is lower than that reported in previous studies (e.g. Bally 2016; Drabek-Maunder et al. 2016). The outflow contribution decreases with time once the outflow action stops. This indicates that the outflows do not have a significant cumulative impact on the turbulent levels during the occurrence of several outflow actions. Thus, the outflow energy contribution to turbulent energy increases insignificantly with the evolutionary stages. Our results suggest that the outflow energy is large enough to maintain the turbulent energy in the clumps and that the outflow has some (not significant) effect on the turbulent energy. However, there is a better correlation between the outflow energy and turbulent energy (see Fig. 5). Therefore, we could not determine if the outflow significantly contributes to the turbulent energy in the clumps. This is consistent with the study conducted by Maud et al. (2015). They also reported that there is a better correlation between the outflow energy and turbulent energy, but the core turbulence is not driven by the local input from the outflows. However, Drabek-Maunder et al. (2016) and Yang et al. (2018) reported that there is no correlation between the turbulent and outflow energies. Urquhart et al. (2018) found that the clump mass and evolutionary stage are uncorrelated. For similar mass of massive star, it is likely that we can observe the obvious difference of turbulent energy between clump without and with outflow. However, for statistics, the mass parameter of turbulent energy is less constrained for each evolutionary stage. All these findings imply that the outflow action has some impact on the local environment and cloud itself, but the contribution from outflow does not mainly drive turbulence. This observation is consistent with several other studies that suggest that turbulence is mostly driven by large-scale mechanisms (Ossenkopf & Mac Low 2002; Brunt, Heyer & Mac Low 2009; Padoan et al. 2009; Arce et al. 2010; Mottram & Brunt 2012; Plunkett et al. 2015; Drabek-Maunder et al. 2016).

2021MNRAS.500.3083C__Meneghetti_et_al._2017_Instance_1

A natural help in observational studies of particularly faint objects is provided by strong gravitational lensing. In the last few years, much progress in this field has been driven by deep observations of massive galaxy clusters, carried out in the context of large Hubble Space Telescope programmes, in particular the Hubble Frontier Fields (HFF) survey (Lotz et al. 2017). Robust lens models of galaxy clusters are built thanks to the identification of large numbers of multiply lensed sources, which can span a large redshift range (Meneghetti et al. 2017; Bergamini et al. 2019). Thanks to strong-lensing effects produced by massive clusters of galaxies located along the line of sight, sources can be magnified by large factors (ranging from μ of the order of a few up to ∼100), allowing faint, compact objects to be studied with very high spatial resolution and signal-to-noise ratios (SNR) (and suprequent recurrencies) and in some cases, to probe their structural parameters down to scales of a few ∼10 pc. In this context, the determination of the redshift of the images is a key problem. In many cases, photometric redshift estimates are accessible, but a safe determination of the redshift generally has to rely upon a spectroscopic detection, achievable only with deep observations. In this regard, in recent times considerable, further progress was possible thanks to the significant use of powerful instruments such as the Multi Unit Spectroscopic Explorer (MUSE, Bacon et al. 2015) mounted on the VLT, which has enabled the spectroscopic confirmation of hundreds of multiple images at high redshift (z > 3, e.g. Caminha et al. 2017; Lagattuta et al. 2019). This has enhanced the production of highly accurate lens models, significantly mitigating systematic uncertainties in the computation of magnification maps in lensed fields. This recent progress has allowed one to determine absolute physical quantities such as luminosities, sizes, stellar mass values and SFRs of new objects, which before were impossible to study in non-lensed fields.

2020ApJ...904...91V__Zanon_et_al._2018_Instance_1

When in a rotation-powered state, many spiders exhibit a nonthermal (synchrotron radiation; SR) orbitally modulated emission component in the X-ray band, attributed to particle acceleration in an intrabinary pulsar wind termination shock (IBS) and Doppler boosting of a bulk flow along the shock tangent (e.g., Wadiasingh et al. 2015, 2017; Romani & Sanchez 2016). This type of geometry/radation picture was identified over two decades ago for the BW system involving the MSP B1957+20 (Arons & Tavani 1993) and later for the gamma-ray-emitting PSR B1259-63/Be star binary system (Tavani & Arons 1997). The existence of a shock is also indicated by orbital-phase- and frequency-dependent radio eclipses of the MSP (since plasma structures at the shock attenuates the radio), where in RBs the eclipse fraction can be >50% (e.g., Archibald et al. 2009, 2013; Broderick et al. 2016; Miraval Zanon et al. 2018) of the orbital phase (while the MSP remains largely uneclipsed at inferior conjunction of the pulsar). The hard power laws inferred in X-rays imply emission due to an energetic electron population. The X-ray spectra may furthermore extend to at least ≳50 keV with no suggestion of spectral cutoffs (e.g., Tendulkar et al. 2014; Kong et al. 2017b; Al Noori et al. 2018), constraining the shock magnetic field to Bsh ≳ 1 G (Wadiasingh et al. 2017). For a given pulsar spin-down power erg s−1, the magnetic field Bsh at the shock can be bounded using the Poynting flux for a magnetic field Bw ∝ R−1 in the striped wind outside the light cylinder. The flux can be integrated over a spherical surface of area at the shock radius Rsh to yield an isotropic electromagnetic luminosity . One therefore arrives at the constraint , which is detailed in Equation (1), being generally less than 100 G. This may be recast as a condition that the ratio of electromagnetic energy density to particle pressure, σ, is less than unity, i.e., that is dominated by the plasma wind contribution. As will be apparent in due course (see Section 3), if the particle acceleration is as fast and efficient (attaining the synchrotron burn-off limit) as in pulsar wind nebulae, MeV synchrotron components may be observable by future medium-energy, gamma-ray Compton/pair telescopes, such as e-ASTROGAM (De Angelis et al. 2017) and AMEGO.8 8 AMEGO: https://asd.gsfc.nasa.gov/amego/index.html (McEnery et al. 2019).

2015MNRAS.454.3134M__Wilkinson_&_Uttley_2009_Instance_1

In order to study the behaviour of the soft residuals and attempt to distinguish between possible origins, we require a source that evolves across a dynamic range in spectral hardness; as can be seen from fig. 8 and tables 2 and 3 of M15, the ideal source for such a study is NGC 1313 X-1. However, both the inferred (deabsorbed) hardness ratio and our ability to reliably characterize the residuals is sensitive to the modelling of the continuum. M15 show, via use of covariance spectra (see Wilkinson & Uttley 2009; Uttley et al. 2014 for a review of the technique), that the ULX continuum emission originates from at least two components that cross at ∼1 keV. Mismodelling of the continuum will therefore have an adverse effect on detecting atomic features imprinted between 0.7 and 2 keV, whilst an inability to separate out the components in the time-averaged spectrum can lead to misleading hardness ratios. To better address this problem we model each of the observations (using both PN and MOS data) using the continuum described above (and including a normalization offset to account for differing responses, typically within ∼10 per cent of unity), finding that in five out of the available 11 observations we cannot distinguish between a solution where the soft component is intrinsically strong or weak. Middleton et al. (2015) show, through use of the covariance spectrum, that the variability is entirely contained within the hard component but that a soft excess must still be present (see also Middleton et al. 2011) whilst the highest S/N data clearly show that the soft component dominates over the hard component below ∼1 keV. Whilst we can force the spectra for the five observations into what we believe to be a more appropriate deconvolution (namely by fixing the normalization of the soft component – see M15), accurate modelling of the residuals requires the normalizations to be free to vary and so we exclude these observations from our subsequent analysis.

2016ApJ...826..134D__Wiedenbeck_et_al._2013_Instance_1

Solar energetic particle (SEP) events as can be observed in the Earth’s orbit are determined by a combination of the underlying acceleration, injection and transport conditions, and therefore carry fundamental information on these processes. In the classical picture introduced by Reames (1999), SEP events are separated into two groups according to their characteristics: impulsive and gradual. Impulsive events, which are electron and 3He-rich, are believed to be flare-associated and therefore show a narrow angular spread in interplanetary space. These events have an impulsive increase and a shorter decay. Gradual events, on the other hand, show much broader angular SEP spreads because of their association to extended shock fronts. The gradual increase is caused by the continuous acceleration by the coronal mass ejection (CME)-driven shock front. Gradual events are usually observed in protons and heavy ions, which can be efficiently accelerated by shocks. Recent observations during the STEREO era, however, question this simple picture, especially since the nature of events showing wide longitudinal SEP spreads appears to be more complicated. It was found that 3He-rich events extend over more than 130° in longitude (Wiedenbeck et al. 2013), and that near-relativistic electron events can spread up to almost all around the Sun. Dresing et al. (2012) suggested that a strong perpendicular transport may cause the wide SEP distribution. On the other hand, it is also possible that the injection of SEPs at the Sun can be much wider than expected from a flare-like point source. The driver of such extended injection regions may be of a different nature. Diverging magnetic field lines below the source surface (e.g., Klein et al. 2008) as well as the presence of a coronal shock may play a role. The importance of EIT-waves intersecting the magnetic footpoints of far separated spacecraft are also under discussion (Rouillard et al. 2012; Park et al. 2013; Lario et al. 2014). Statistical analyses of multi-spacecraft SEP events (e.g., Lario et al. 2013) show that event characteristics, such as peak intensities, onset delays, rise times, and anisotropies, show strongly varying longitudinal dependencies from event to event. The lack of a clear correlation to a single mechanism, such as the CME speed or width as a representative of the shock strength or extent (Richardson et al. 2014), as well as varying event characteristics suggests that there is not a single process providing these wide SEP distributions (Dresing et al. 2014). Therefore, when describing an SEP event, a possible mixture of different processes as well as a varying strength of these mechanisms must be taken into account.

2022MNRAS.516.5618P__Helton_et_al._2021_Instance_1

At present, direct detection of the CGM in emission poses an observational challenge due to its diffuse nature (with hydrogen densities of the order of nH 0.1 cm−3). Cosmological hydrodynamical simulations concur that the emission signal is faint by current observational standards (Augustin et al. 2019; Péroux et al. 2019; Corlies et al. 2020; Wijers, Schaye & Oppenheimer 2020; Byrohl et al. 2021; Nelson et al. 2021; Wijers & Schaye 2021). For these reasons, detections in emission at high-redshifts are currently limited to deep fields (Wisotzki et al. 2016; Leclercq et al. 2017; Wisotzki et al. 2018; Leclercq et al. 2020, 2022) or regions around bright quasars (Cantalupo et al. 2005; Arrigoni Battaia et al. 2015; Farina et al. 2019; Lusso et al. 2019; Mackenzie et al. 2021) while detections at z1 are now becoming available (Epinat et al. 2018; Johnson et al. 2018; Chen et al. 2019; Rupke et al. 2019; Burchett et al. 2021; Helton et al. 2021; Zabl et al. 2021). Given this limitation, absorption lines detected against bright background quasars at UV and optical wavelengths provide the most compelling way to study the distribution, kinematics and chemical properties of CGM atomic gas to date. In these quasar absorbers, the minimum column density (which is tightly correlated to the volumic gas density, see Rahmati et al. 2013) that can be detected is set by the apparent brightness of the background sources and thus the detection efficiency is independent of the redshift of the foreground absorber host galaxy. In addition, absorption line-based metallicity measurements are independent of excitation conditions (Kewley, Nicholls & Sutherland 2019; Maiolino & Mannucci 2019). In fact, unlike emission lines metallicity estimates, they are largely insensitive to density or temperature and high column density systems tracing neutral gas require no assumption on a local source of excitation (Vladilo et al. 2001; Dessauges-Zavadsky et al. 2003). Importantly, multiple state-of-the-art cosmological hydrodynamical simulations and early observational results indicate that the chemical properties of the CGM gas probed in absorption show an inhomogeneous metal distribution around galaxies with indication of a trend with galaxy orientation (Péroux & Howk 2020; Wendt et al. 2021).

2015MNRAS.450.3840C__Dunn_et_al._2010_Instance_1

In order to understand the uniqueness of the recurrence of the 4U 1630–472 outbursts and to correlate this with the lack of high-energy emission, we investigated the ASM and BAT light curves of some of the brightest and active transient black hole X-ray binaries (BHXRBs) during the seven years (2005–2011) in which both instruments were operational. Many studies of the outburst evolution of these sources have been reported in the literature (e.g. Yu & Yan 2009; Capitanio et al. 2010; Dunn et al. 2010, and references therein); the various outbursts observed do not have any detectable recurrence period and, in addition, show a complex behaviour in both soft and hard energy ranges and very different luminosities. The only exception is H 1743–322; this BHC has shown only for some years outbursts equally spaced in time, as reported by Capitanio et al. (2010). In analogy with 4U 1630–472, the outburst of H 1743–322 that occurred in 2007 has a 2–12 keV behaviour mostly identical to some of the subsequent periodical outbursts but showing a fainter hard X-ray emission; the H 1743–322 ASM 2007 peak flux (1–12 keV) is ∼250 mCrab and the BAT 2007 peak flux (15–50 keV) is ∼60 mCrab. The subsequent H 1743–322 outburst (2008–2010) presents a similar 1–12 keV flux but with a 15–50 keV flux of ∼200 mCrab. As Fig. 10 shows, the difference in the ratio between the BAT HS–HSS transition luminosity and the ASM peak flux of H 1743–322 is not enough to bring the outburst totally out of the correlation reported by Yu & Yan (2009) as in the case of the 2006 and 2008 outbursts of 4U 1630–472. However, as reported by Corbel & Tzioumis (2008), the HS–HSS transition occurred before the peak of the hard X-ray emission and thus it is only an upper limit. For the 2007 and 2008–2010 outbursts of H 1743–322, the relation between the hard X-ray luminosity peak and the outburst waiting time is also not respected. In contrast, during the subsequent outbursts, a similar waiting time corresponds to a similar peak luminosity in the 15–50 keV energy range.

2021ApJ...923..233G__Carlton_et_al._2011_Instance_1

One major difficulty afflicts the study of SNRs to learn about their supernovae: separating ejected material from swept-up surrounding unmodified interstellar medium (ISM) or modified CSM. Abundance clues are powerful but have limitations. Ideally, one would observe the youngest possible remnant that is large enough for adequate spatial resolution. That remnant appears to be the youngest Galactic SNR, G1.9+0.3 (Reynolds et al. 2008; see Figure 1). This object is about 100′′ in diameter, the smallest angular size of any confirmed Galactic SNR. Unfortunately, it is very highly absorbed, with an X-ray column density of about 5 × 1022 cm−2 (Reynolds et al. 2009), implying A V ∼ 23 m , so radio and X-rays are the only useful observational channels. The angular expansion rate of 0.64 arcsec yr−1 obtained from comparing X-ray images from 2007 and 2009 (Carlton et al. 2011) gives an upper limit for the age of about 160 yr, less if (as is almost certainly the case) deceleration has occurred; spatial variations in expansion rate (Borkowski et al. 2014) are consistent with an age of about 100 yr, or a date of around 1900. The high extinction would have rendered it unobservable in optical telescopes of that era. Furthermore, its X-ray spectrum is almost entirely synchrotron emission, making it a member of the small class of X-ray synchrotron–dominated SNRs. However, long observations with Chandra have allowed the detection of thermal emission from small regions (Borkowski et al. 2011, 2013b), with spectroscopic widths of ∼14,000 km s−1 confirming the large expansion proper motion, refined with a second Chandra observation (Carlton et al. 2011). The distance is still uncertain; the high column—higher than the entire Galactic column along nearby sight lines—suggests an association with the Galactic center, and a provisional distance of order 8.5 kpc has been assumed. Nearer would be very unlikely in view of the high absorption, but too much farther would make the expansion proper motion unreasonably large. An H i observation with the Giant Metrewave Radio Telescope (Roy & Pal 2014) has been used to set a lower limit of 10 kpc, certainly consistent with the known properties of G1.9+0.3.

2020AandA...644A..97C__Leroy_et_al._2013_Instance_1

Major nearby galaxy cold gas mapping surveys (Regan et al. 2001; Wilson et al. 2009; Rahman et al. 2011; Leroy et al. 2009; Donovan Meyer et al. 2013; Bolatto et al. 2017; Sorai et al. 2019; Sun et al. 2018) have focused on observations of the molecular gas (through CO lines). Despite a few notable exceptions (e.g. Alatalo et al. 2013; Saintonge et al. 2017), these surveys observed mainly spiral or infrared-bright galaxies (i.e. galaxies with significant star formation) and have furthered our understanding of how star formation happens, rather than how it stops. This boils down to quantifying the relation between molecular gas and star formation rate (SFR), which appears nearly linear in nearby discs (Kennicutt 1998; Bigiel et al. 2008; Leroy et al. 2013; Lin et al. 2019). This relationship is often parametrised via the ratio between the SFR and the molecular gas mass (Mmol), which is called the molecular star formation efficiency (SFE = SFR/Mmol = 1∕τdep), where the inverse of the SFE is the depletion time, τdep. The depletion time indicates how much time is necessary to convert all the available molecular gas into stars at the current star formation rate. On kpc scales and in the discs of nearby star-forming galaxies, τdep is approximately constant around 1–2 Gyr (Bigiel et al. 2011; Rahman et al. 2012; Leroy et al. 2013; Utomo et al. 2017), and it appears to weakly correlate with many galactic properties such as stellar mass surface density or environmental hydrostatic pressure (Leroy et al. 2008; Rahman et al. 2012). Nevertheless, small but important deviations for a constant SFE have been noticed, which can be the first hints of star formation quenching. In some galaxies, the depletion time in the centres appear shorter (Leroy et al. 2013; Utomo et al. 2017) or longer (Utomo et al. 2017) with respectto their discs. These differences may correlate with the presence of a bar or with galaxy mergers (Utomo et al. 2017; see also Muraoka et al. 2019) and do not seem to be related to unaccounted variation in the CO-to-H2 conversion factor (Leroy et al. 2013; Utomo et al. 2017). Spiral arm streaming motions have also been observed to lengthen depletion times (Meidt et al. 2013; Leroy et al. 2015).

2015MNRAS.451.2610H__Hinshaw_et_al._2013_Instance_1

The ability to test the hypothesis that a set of data samples is drawn from some general n-dimensional probability distribution $f(\boldsymbol {x})$ has an interesting application in the validation of Bayesian inference analyses (indeed this application provided our original motivation for seeking to extend the K–S test to multiple dimensions). Bayesian methods are now pervasive across all branches of science and engineering, from cognitive neuroscience (Doya et al. 2007) and machine learning (Bishop 2006) to spam filtering (Sahami et al. 1998) and geographic profiling (Collins, Gao & Carin 1999; Le Comber & Stevenson 2012). In precision cosmology, Bayesian inference is the main tool for setting constraints on cosmological parameters (Hinshaw et al. 2013; Planck Collaboration XVI 2014), but very few attempts have been made to assess whether the derived posterior probability distributions are a truthful representation of the actual parameter constraints one can infer from the data in the context of a given physical model. This lack of validation has been highlighted by several authors, with the strong dependence of the inference results on the priors being of particular concern (Efstathiou 2008; Linder & Miquel 2008). There have been attempts to address this issue, ranging from the approach of Cook, Gelman & Rubin (2006), which was designed with software validation solely in mind, to a method based on the inverse probability integral transform (Smirnov transform) applied to posterior distributions that extends to spaces of higher dimensionality via marginalization (Dorn, Oppermann & Enßlin 2013). Also, validation of the Bayesian source-finding algorithm of Carvalho et al. (2012) was performed in Planck Collaboration XXIX (2014), but only point estimates deduced from the posterior distributions were actually verified. Our method for addressing this problem is based on our applying our multidimensional extension of the K–S test to sets of Monte Carlo simulations of the data and the posterior distributions derived therefrom. In particular, it can take advantage of the fact that one may typically generate simulations that are of greater sophistication and realism than may be modelled in the inference process, and thus allows for a more thorough validation of the inference than has been possible with the methods developed previously. In particular, our validation procedure enables us to test all the assumptions made (explicitly or implicitly) in the inference process, such as the statistical description of the data, model assumptions and approximations, as well as the software implementation of the analysis. Moreover, we consider the full posterior distribution, regardless of its dimensionality and form, without the need to resort to marginalization, and thereby keeping intact its n-dimensional character.

2021ApJ...913..115A__Linden_et_al._2012_Instance_2

The origin of the GC VHE emission remains undetermined, due in part to source confusion and the limitations of current instruments. The source of VER J1745–290 may be Sgr A* (Atoyan & Dermer 2004; Aharonian & Neronov 2005; Ballantyne et al. 2011; Chernyakova et al. 2011; Fatuzzo & Melia 2012; Kusunose & Takahara 2012; Fujita et al. 2017; Rodríguez-Ramírez et al. 2019) or PWN G359.95-0.04 (Wang et al. 2006; Hinton & Aharonian 2007), with which it is spatially coincident (Acero et al. 2010). Other possible origins include the annihilation of dark matter particles (Bergström et al. 2005a, 2005b; Horns 2005; Profumo 2005; Aharonian et al. 2006c; Belikov et al. 2012; Cembranos et al. 2012, 2013; Gammaldi et al. 2016) or a population of millisecond pulsars (Bednarek & Sobczak 2013; Bartels et al. 2016; Guépin et al. 2018). The mechanism of gamma-ray emission may be predominantly due to hadronic processes, where relativistic protons interact with gas and subsequently produce gamma rays through neutral pion decay (Aharonian & Neronov 2005; Ballantyne et al. 2011; Chernyakova et al. 2011; Fatuzzo & Melia 2012; Linden et al. 2012; Guépin et al. 2018), leptonic processes where gamma rays are produced when electrons and positrons undergo inverse Compton scattering off a radiation field (Atoyan & Dermer 2004; Hinton & Aharonian 2007; Kusunose & Takahara 2012; Lacroix et al. 2016), or a combination of processes (hybrid scenario), where leptons produce high-energy, but not VHE, gamma rays (Guo et al. 2013). Both the correlation of VHE emission with the CMZ and the lack of a cutoff in the diffuse spectrum support a hadronic scenario, capable of explaining both VER J1745–290 and the diffuse emission (Aharonian et al. 2006b; Linden et al. 2012; Abramowski et al. 2016). Measurement of the diffuse spectrum by H.E.S.S. up to energies of tens of TeV with no evidence of a cutoff has also been interpreted as evidence for the existence of PeV protons within the central 10 parsecs of the GC, accelerated by Sgr A* (Abramowski et al. 2016). While cosmic rays are known to extend up to PeV energies (e.g., Hörandel 2003), few, if any, accelerators of PeV cosmic rays, or “PeVatrons,” have been clearly established (e.g., Abramowski et al. 2016; Abeysekara et al. 2020). Discovering the nature of PeVatrons in our Galaxy is thus a particularly important step in understanding the origins of cosmic rays.

2018MNRAS.479.3923Z__Welsh_&_Lallement_2012_Instance_1

Simulations are performed in Fig. 6 to compare the spectrum profiles of the S ii triplets for a synthetic absorption spectrum of a DLA with and without the magnetic alignment included. Fig. 6 was designed up to illustrate the effect in a realistic instrumental set-up, with a given typical pixel size and S/N for an optical spectrum taken by an 8m-class telescope. The graphical use of steps instead of curves, which is common in absorption spectroscopy, is intended to visualize the pixel-by-pixel noise variations in the data. The three transitions of singly ionized Sulfur (Sii; upper ionization potential 23.3 eV) at λλ1250.58, 1253.81, 1259.52Å represent important tracers for neutral and weakly ionized gas in the local interstellar and intergalactic medium and in distant galaxies (e.g. Richter et al. 2001; Welsh & Lallement 2012; Fox, Richter & Fechner 2014a; Kisielius et al. 2014). Being an α element, singly ionized Sulfur only has a weak depletion into dust grains (e.g. Savage & Sembach 1996). Thus the interstellar Sulfur abundance is often used as a proxy for the α-abundance in the gas. In addition, Sulfur has a relatively low-cosmic abundance (Asplund et al. 2009) and under typical interstellar conditions (in particular in low-metallicity environments) these lines are not saturated. The three lines are observed in the same wavelength region with identical S/N. The important parameters for simulations are presented in the caption, such as the assumption of S ii column density, etc. The synthetic spectra were generated using the fitlyman routine (Fontana & Ballester 1995) implemented in the eso-midas software package. Atomic data were taken from Morton (2003). To show the effect clearly, we zoom in the spectrum to the radial velocity range [ − 10km · s−1, 10km · s−1]. The enhancement and reduction of the spectral line profile due to the magnetic realignment change among the triplets. Given the fact that meanwhile optical QSO spectra reach up to a new standard of S/N of a few hundred (e.g. D’Odorico et al. 2016), the predicted effect is already VISIBLE, if the component structure of the DLA allows a detailed investigation.

2018AandA...616A..99K__Narang_et_al._2016_Instance_4

The high-resolution imaging observations of TR from IRIS reveal the ubiquitous presence of network jets. We have used three different IRIS observations of the quiet sun, which are located near the disk center. On the basis of careful inspection, 51 network jets are identified from three QS observations and used for further analysis. These 51 network jets are very well resolved and are not affected by the dynamics of other jets. The study is focused on the rotating motion of network jets along with the estimation of their other properties (speed, height, and lifetime). The mean speed, as predicted by statistical distributions of the speed, is 140.16 km s−1 with a standard deviation of 39.41 km s−1. The mean speed of network jets is very similar, as reported in previous works (e.g., Tian et al. 2014; Narang et al. 2016). However, in case of their lifetimes, we found a value that is almost double (105.49 s) that of the previously reported mean lifetime of the network jets (49.6 s; Tian et al. 2014). As mentioned above, we took only those network jets that are very well resolved in space and in the time; these criteria exclude short lifetime network jets. Therefore, our statistical distribution of the lifetime predicts a higher mean lifetime. The mean length of the network jets is 3.16 Mm with a standard deviation of 1.18 Mm. In the case of CH network jets, Tian et al. (2014) have reported that most of the network jets have lengths from 4.0 to 10.0 Mm. However, the mean length for QS network jets is smaller (3.53 Mm; Narang et al. 2016). So, the mean length for QS network jets from the present work is in good agreement with Narang et al. (2016). In addition, the apparent speed and length of these network jets are positively correlated, which is very similar to what has already been reported in previous works (Narang et al. 2016). Finally, we can say that these networks jets are very dynamic features of the solar TR, as revealed by their estimated properties.

2022AandA...666A..80N__Piatti_2022_Instance_1

Many studies indicate a much more complicated star formation history (SFH; e.g., Pagel & Tautvaišvienė 1998; Carrera et al. 2008; Harris & Zaritsky 2009; Rubele et al. 2012; Meschin et al. 2014; Palma et al. 2015; Perren et al. 2017) or AMR for star clusters (e.g., Olszewski et al. 1991; Hill et al. 2000; Dirsch et al. 2000; Rich et al. 2001; Leonardi & Rose 2003; Kerber et al. 2007) in the LMC than in the SMC. Early studies of the cluster AMR in the LMC (e.g., the spectroscopic study of Olszewski et al. 1991) revealed a mysterious gap in the star cluster formation between 10 and 3 Gyr ago (with the sole exception of cluster ESO121-3 and very recently also KMHK1592, as reported by Piatti 2022), which follows the initial formation of old, metal-poor globular clusters, and precedes more recent active formation of intermediate-age clusters. This so-called “age gap”, which is simultaneously a metallicity gap, was later reported also by other authors (e.g., Harris & Zaritsky 2009; Sharma et al. 2010; Kerber et al. 2007, and references therein), even though it has not been fully confirmed when only the field stars are considered. For example, Piatti & Geisler (2013) reported that no clear age gap in the field star formation is observed in their study of fields in the LMC main body, based on Washington photometry. Furthermore, based on their spectroscopic analysis of four fields to the north of the LMC bar, Carrera et al. (2008) maintain that the disk and cluster AMR are similar. However, unlike clusters, there is no age gap in the field population. On the contrary, Harris & Zaritsky (2009) claim that such a gap is evident in the field population of the bar, mostly omitted in previous studies. Also Meschin et al. (2014), using optical photometry, identified two main star-forming epochs with a period characterized by a lower activity in between; however, in their work that interval of time was shorter and lasted from ∼8 up to ∼4 Gyr ago. All the aforementioned authors agree that star formation in the LMC is continuing to this day.

2016AandA...591A..13V__Clarke_2004_Instance_1

The first direct proof of the existence of magnetic fields in large-scale extragalactic environments, i.e., galaxy clusters, dates back to the 1970s with the discovery of extended, diffuse, central synchrotron sources called radio halos (see, e.g., Feretti et al. 2012 for a review). Later, indirect evidence of the existence of intracluster magnetic fields has been given by several statistical studies on the effect of the Faraday rotation on the radio signal from background galaxies or galaxies embedded in galaxy clusters (Lawler & Dennison 1982; Vallée et al. 1986; Clarke et al. 2001; Johnston-Hollitt 2003; Clarke 2004; Johnston-Hollitt & Ekers 2004). On scales up to a few Mpc from the nearest galaxy cluster, possibly along filaments, only a few diffuse synchrotron sources have been reported (Harris et al. 1993; Bagchi et al. 2002; Kronberg et al. 2007; Giovannini et al. 2013, 2015). Magnetic fields with strengths on the order of 10-15 G in voids might be indicated by γ-ray observations (see Neronov & Vovk 2010; Tavecchio et al. 2010; Takahashi et al. 2012, 2013; but see Broderick et al. 2014a,b for alternative possibilities). Nevertheless, up to now, a robust confirmed detection of magnetic fields on scales that are much larger than clusters is not available. Stasyszyn et al. (2010) and Akahori et al. (2014a) investigated the possibility of statistically measuring Faraday rotation from intergalactic magnetic fields with present observations, showing that only the Square Kilometre Array (SKA) and its pathfinders are likely to succeed in this respect. By comparing the observations with single-scale magnetic field simulations, Pshirkov et al. (2015) infer an upper limit of 1.2 nG for extragalactic large-scale magnetic fields, while the Planck Collaboration XIX (2016) derived a more stringent upper limit for primordial large-scale magnetic fields of B 0.67 nG from the analysis of the Cosmic Microwave Background (CMB) power spectra and the effect on the ionization history (but see also Takahashi et al. 2005; Ichiki et al. 2006).

2019AandA...622A..62A__Aviles_et_al._(2018)_Instance_1

On the other hand, PT has experienced many developments in recent years (Matsubara 2008a; Baumann et al. 2012; Carlson et al. 2013), in part because it can be useful to analytically understand different effects in the power spectrum and correlation function for the dark matter clustering. These effects can be confirmed or refuted, and further explored with simulations to ultimately understand the outcomes of present and future galaxy surveys, such as eBOSS (Zhao 2016), DESI (Aghamousa et al. 2016), EUCLID (Amendola et al. 2013), and LSST (LSST Dark Energy Science Collaboration 2012). Two approaches have been used to study PT: the Eulerian standard PT (SPT) and Lagrangian PT (LPT), which both have advantages and drawbacks, but they are complementary in the end (Tassev 2014). The nonlinear PT for MG was developed initially in (Koyama et al. 2009), and has been further studied in several other works (Taruya et al. 2014a,b; Brax & Valageas 2013; Bellini & Zumalacarregui 2015; Taruya 2016; Bose & Koyama 2016, 2017; Barrow & Mota 2003; Akrami et al. 2013; Fasiello & Vlah 2017; Aviles & Cervantes-Cota 2017; Hirano et al. 2018; Bose et al. 2018; Bose & Taruya 2018; Aviles et al. 2018). The LPT for dark matter fluctuations in MG was developed in Aviles & Cervantes-Cota (2017), and further studies for biased tracers in Aviles et al. (2018). The PT for MG has the advantage that it allows us to understand the role that these physical parameters play in the screening features of dark matter statistics. We here study some of these effects through screening mechanisms by examining them at second- and third-order perturbation levels using PT for some MG models. To this end, we build on the LPT formalism developed in Aviles & Cervantes-Cota (2017), which was initially posited for MG theories in the Jordan frame, in order to apply it to theories in the Einstein frame. Because of the direct coupling of the scalar field and the dark matter in the Klein–Gordon equation, the equations that govern the screening can differ substantially from those in Jordan-frame MG theories. In general, screening effects depend on the type of nonlinearities that are introduced in the Lagrangian density. We present a detailed analysis of screening features and identify the theoretical roots of their origin. Our results show that screenings possess peculiar features that depend on the scalar field effective mass and couplings, and that may in particular cases cause anti-screening effects in the power spectrum, such as in the symmetron model. We perform this analysis by separating the growth functions into screening and non-screened parts. We note, however, that we do not compare the perturbative approach with a fully nonlinear simulation. We refer to (Koyama et al. 2009), for instance, for investigations like this at the level of the power spectrum.

2015MNRAS.450...45G__Klypin_et_al._1999_Instance_1

The Λ cold dark matter (CDM) model has had tremendous success in providing a cosmogony that links the state of the very high redshift Universe as inferred from cosmic microwave background observations and big bang nucleosynthesis considerations, with the observed large-scale distribution of galaxies and its evolution at later times. In this paradigm, the observed structures grew due to gravitational amplification of initially small perturbations, perhaps seeded by inflation (Guth 1981), with most of the gravitating mass in the form of ‘dark matter’, an as of yet unknown type of matter that apart from gravitationally, interacts only very weakly if at all with baryonic matter and radiation, see e.g. Frenk & White (2012) for a recent review. Observations on smaller, sub galactic scales, have proven more problematic for ΛCDM, with suggestions that the low abundance (e.g. Klypin et al. 1999; Moore et al. 1999) and shallow density profiles (e.g Gilmore et al. 2007; de Vega & Sanchez 2010) inferred for haloes hosting Milky Way satellites are inconsistent with the numerous substructures with cuspy density profiles that form in Milky Way-like CDM haloes. Indeed the substructures in the haloes of the Aquarius project (Springel et al. 2008) and the GHALO project (Stadel et al. 2009) may be difficult to reconcile with those inferred to host Milky Way satellites. Even if many of the smaller DM substructures may not have a sufficiently deep potential well to form stars after reionization (e.g Efstathiou 1992; Benson et al. 2002) and so may well be dark, some of the more massive ones are probably too big to be affected (Okamoto, Gao & Theuns 2008) and would hence appear to be ‘too big to fail’ (Boylan-Kolchin, Bullock & Kaplinghat 2011, 2012). However, the jury on this is still out: the Milky Way's halo may simply be of lower mass than those of the Aquarius haloes and hence have fewer massive satellites (Wang et al. 2012). The status of the density profiles of the satellite's haloes – cored versus cuspy – is similarly unresolved. Strigari, Frenk & White (2010) claim that the stellar dynamics observations of the satellites do not imply cores at all and hence may be consistent with CDM cusps. But even if the satellites had cored profile, this might result from the action of baryonic feedback processes (Governato et al. 2012; Pontzen & Governato 2012), and hence still be consistent with CDM.

2015AandA...584A.103S__Lattimer_&_Swesty_1991_Instance_1

The energy in the inner crust is largely influenced by the properties of the neutron gas and, therefore, the EoS of neutron matter of the different calculations plays an essential role. The NV calculation (Negele & Vautherin 1973) is based on a local energy density functional that closely reproduces the Siemens-Pandharipande EoS of neutron matter (Siemens & Pandharipande 1971) in the low-density regime. The Moskow calculation (Baldo et al. 2007) employs a semi-microscopic energy density functional obtained by combining the phenomenological functional of Fayans et al. (2000) inside the nuclear cluster with a microscopic part calculated in the Brueckner theory with the Argonne v18 potential (Wiringa et al. 1995) to describe the neutron environment in the low-density regime (Baldo et al. 2004). The BBP calculation (Baym et al. 1971a,b) gives the EoS based on the Brueckner calculations for pure neutron matter of Siemens (Siemens & Pandharipande 1971). The LS-Ska (Lattimer & Swesty 1991; Lattimer 2015) and DH-SLy4 (Douchin & Haensel 2001) EoSs were constructed using the Skyrme effective nuclear forces Ska and SLy4, respectively. The SLy4 Skyrme force (Chabanat et al. 1998) was parametrized, among other constraints, to be consistent with the microscopic variational calculation of neutron matter of Wiringa et al. (1988) above the nuclear saturation density. The Shen-TM1 EoS (Shen et al. 1998b,a; Sumiyoshi 2015) was computed using the relativistic mean field parameter set TM1 for the nuclear interaction. The calculations of LS (Lattimer & Swesty 1991; Lattimer 2015) and Shen et al. (Shen et al. 1998b,a; Sumiyoshi 2015) are the two EoS tables in more widespread use for astrophysical simulations. The BSk21 EoS (Pearson et al. 2012; Fantina et al. 2013; Potekhin et al. 2013; Goriely et al. 2010) is based on a Skyrme force with the parameters accurately fitted to the known nuclear masses and constrained, among various physical conditions, to the neutron matter EoS derived within modern many-body approaches which include the contribution of three-body forces.

2018MNRAS.479.3923Z__Yan_&_Lazarian_2006_Instance_1

As illustrated in this paper, the variation of spectral line intensity induced by GSA varies among different spectral lines. Thus, such influence could be precisely analysed if multispectral lines for the same element is achievable. In addition, the alignment on the ground state is transferred to the levels of atoms on the excited states through absorption process, as illustrated in Section 3 and 4. The intensity of the ultraviolet-pumped fluorescence lines, which are derived from successive decays to different levels of atoms and applied to the modelling of reflection nebulae (Sellgren 1984, 1986), are dependent on the initial upper levels, and thus is influenced by GSA through the scattering process. The influence of collision is neglected in this paper, which applies to most diffuse ISM and IGM. Collisionsreduce the alignment efficiency (see Hawkins 1955). The collision effect can become important in the case of higher density medium where the collision rate $\tau _c^{-1}$ (either inelastic collision rate or Van der Waals collision rate) dominates over optical pumping rate $B_{lu}\bar{J}^0_0$ (see Yan & Lazarian 2006 for details). The focus of our paper is on the GSA effect that is a saturated state. When the magnetic precession rate is comparable to the optical pumping from the ground state ($2\pi \nu _L\sim B_{lu}\bar{J}^0_0$), the ground-level Hanle effect is applicable (see Landolfi & Landi Degl’Innocenti 1986), which means the magnetic field influence on the spectrum is not limited to the change of direction but also the magnetic field strength. As demonstrated in Yan & Lazarian (2008), the effect becomes saturated when $2\pi \nu _L\rightarrow 10B_{lu}\bar{J}^0_0$. Therefore, we set rHanlewhere $2\pi \nu _L\simeq 10B_{lu}\bar{J}^0_0$ as the boundary between the ground-level Hanle regime and the GSA regime (see Fig. 12a): (10) \begin{eqnarray*} r_{Hanle}=r_\ast \sqrt{\frac{A_{ul}[J_u]}{1.76(B/{\mu }G)(\exp (h\nu /(k_BT))-1)[J_l]}} \end{eqnarray*} We calculate the boundary rHanle for C ii λ1037 Å in the presence of stars with different effective temperature Teff and radius r* for the magnetic field with the strength range from μG to mG in Fig. 12(b). The rHanle increases as the magnetic field becomes weaker and as the effective temperature Teff and radius r* increase. Nevertheless, even in the most optimistic scenario with Teff = 4 × 104K, r* = 10r⊙, B = 1μG (though rarely applies), the boundary rHanle ≃ 180Au = 8.5 × 10−4pc, which is a thousand times smaller than the normal H ii Region which is in pc scale. All the analysis with GSA and their observational implication in this paper is applicable to most of the ISM, except when performing very high resolution spectral analysis on regions very close to the very bright O-type star.

2019MNRAS.490.5478W__Facchini_et_al._2016_Instance_1

The focus of this work is to address the proplyd lifetime problem from a modelling perspective using recent developments in both the theory of photoevaporating discs and observations of the star and disc population in the ONC. The most similar study to this work is that of Scally & Clarke (2001), who produced an N-body model of the ONC coupled with theoretical photoevaporative mass-loss rates. The aim was to test the idea put forward by Störzer & Hollenbach (1999) that radial orbits of stars could result in shorter periods of exposure to strong FUV flux close to θ1C, thus increasing the PPD dispersal time-scale. The models demonstrated that such dynamical orbits alone are insufficient to produce significantly extended disc lifetimes. However, since that study a number of developments mean that the problem is due to be revisited. First, thermodynamic calculations of conditions in photodissociation regions (PDRs) have been coupled with self-consistent equations for the thermally driven disc wind (Adams et al. 2004; Facchini et al. 2016; Haworth et al. 2018; Haworth & Clarke 2019). In particular, the recent Fried grid (Haworth et al. 2018) can be interpolated across FUV flux, disc outer radius, and disc mass to calculate an instantaneous mass-loss rate for a given PPD. Secondly, the recent sub-mm survey of disc masses and radii by Eisner et al. (2018, hereafter E18) offers further observational constraints on a successful model of PPD evolution, and the host mass-dependent disc properties permit a test of theoretical predictions. Thirdly, Beccari et al. (2017, see also Jerabkova et al. 2019) recently found evidence of three stellar populations with distinct ages in the ONC. This has multiple consequences for models of a PPD population, most obviously that a subset of discs has evolved for a shorter period than the oldest stars in the region. Additionally, since stars are formed from gas, during the evolution of the cluster prior to the most recent formation event there may have been considerable intracluster extinction of UV photons. Understanding how such a scenario influences the disc population would also represent a test of the hypothesis that discrete epochs of star formation occurred in the ONC.

2020ApJ...901..130Z___2020_Instance_1

Fast radio bursts (FRBs), a promising new and mysterious astrophysical phenomenon, are a class of bright transients with millisecond durations detected at ∼GHz (Lorimer et al. 2007; Keane et al. 2011; Thornton et al. 2013; Burke-Spolaor & Bannister 2014; Spitler et al. 2014; Masui & Sigurdson 2015; Petroff et al. 2015, 2016; Ravi et al. 2015, 2016; Champion et al. 2016; Keane et al. 2016; Caleb et al. 2017). Although the physical origin of these intense short pulses has not been figured out so far, most of them have been detected with relatively large dispersion measures (DM) (greater than the maximum produced by the Milky Way). This suggests that they may occur at a cosmological distance, probably at distances of the order of gigaparsecs (Ioka 2003; Inoue 2004; Deng & Zhang 2014; Zheng et al. 2014; Zhang 2018). So far, the cosmological origin of these kinds of mysterious flashes has been confirmed by successfully localizing several bursts (including two repeaters and several apparently nonrepeating ones; Spitler et al. 2016; Scholz et al. 2016; Chatterjee et al. 2017; Marcote et al. 2017; Tendulkar et al. 2017; Bannister et al. 2019; Prochaska et al. 2019; Ravi et al. 2019; Wang & Zhang 2019; Zhang & Wang 2019; Marcote et al. 2020). The confirmation of their cosmological origin allows them to be widely proposed as promising tools for studying the universe and fundamental physics, e.g., the distribution of baryons in the intergalactic medium (IGM) or diffuse gas (Deng & Zhang 2014; Mcquinn 2014; Muñoz & Loeb 2018; Li et al. 2019, 2020; Walters et al. 2019; Wei et al. 2019; Macquart et al. 2020), dark energy (Gao et al. 2014; Zhou et al. 2014; Walters et al. 2018; Wei et al. 2018; Zhao et al. 2020), cosmic ionization history (Deng & Zhang 2014; Zheng et al. 2014), the large-scale structure of the universe (Masui & Sigurdson 2015), the Einstein’s equivalence principle (Wei et al. 2015; Nusser 2016; Tingay & Kaplan 2016), the rest mass of the photon (Wu et al. 2016; Shao & Zhang 2017; Xing et al. 2019), the cosmic proper distance measurements (Yu & Wang 2017), and constraints on the magnetic fields in the IGM (Akahori et al. 2016), as well as measuring the cosmic expansion rate (Wu et al. 2020). Because the event rate of this phenomenon inferred from observations is very high (∼103–104 per day all sky; Thornton et al. 2013; Champion et al. 2016) and due to their extragalactic origin, these bursts are likely to be gravitationally lensed by intervening objects with a different magnitude of mass. Moreover, high time resolutions or short durations of these bursts (∼(1–10) ms) (Lorimer et al. 2007; Keane et al. 2011; Thornton et al. 2013; Spitler et al. 2014, 2016; Petroff et al. 2015, 2016; Ravi et al. 2015; Champion et al. 2016) guarantee that the difference between arrival times of two images can be resolved even if they are lensed by an object as small as 10 M⊙. Therefore, different scale lensing effects of FRBs have been proposed as a probe of compact dark matter (Muñoz et al. 2016; Wang & Wang 2018; Liao et al. 2020; Ranjan 2020), motion of the FRB source (Dai & Lu 2017), and precision cosmology (Li et al. 2018; Liu et al. 2019; Wucknitz et al. 2020). Recently, taking into consideration the theoretical prediction that a portion of FRBs might be associated with GWs, Wei et al. (2018) proposed the joint measurements of DM from FRB observations and DL from GW detections in the same FRB/GW association system (i.e., the combination DM · DL as a function of redshift) as a complementary cosmic probe. The most striking merit of this probe is the independence of the Hubble constant H0, which is a fundamental cosmological parameter now under intense debate because of the well-known Hubble constant tension (Planck Collaboration et al. 2018; Riess et al. 2019). In this paper, we propose that the combination DM · DL as a function of redshift could be further extended to the independent measurements of DMs of localized FRBs and DL of other distance indicators (e.g., SNe Ia) at a similar redshift according to the fundamental assumption that luminosity distance monotonously increases with increasing redshift. Following Masui & Sigurdson (2015), who call brief broadband radio impulses like FRBs “standard pings,” the extended combination DM · DL as a function of redshift can be easily constructed from independent measurements of standard pings and standard candles at similar redshifts (Wei et al. 2018). Moreover, in the CPL framework, we investigate the constraining power on the equation of state of dark energy from this extended combination.

2015ApJ...805...88Y__Metzger_et_al._2011_Instance_1

GRB 100814A is another special event with an early-time shallow decay phase and late-time significant rebrightening in its optical afterglow light curve (Nardini et al. 2014). The power-law ( ) temporal index of the early shallow decay is , which is inconsistent with expectations from the external shock model. It is argued that the shallow decay phases come from energy injection. Usually, the injection luminosity is assumed as (Nousek et al. 2006; Zhang et al. 2006; Yu & Huang 2013), which may naturally come from the magnetic dipole radiation of a newborn millisecond magnetar (Dai & Lu 1998; Zhang & Mészáros 2001; Dall’Osso et al. 2011). As a result, magnetars have been suggested as the central engines for some GRBs, including both long and short events (Zhang & Mészáros 2001; Troja et al. 2007; Metzger et al. 2011; Bernardini et al. 2012; Rowlinson et al. 2013). In both Dai & Lu (1998) and Dall’Osso et al. (2011), works considering a strongly magnetized neutron star as the central engine of a GRB, the energy injection power is more realistically derived as , where T is the spin-down timescale and is the initial luminosity. In particular, while considering the exact form for the energy injection power of a spinning down magnetar due to magnetic dipole radiation, Dall’Osso et al. (2011) found that the luminosity of the X-ray afterglow naturally has a shallow decay phase with a temporal power-law index of . Recently, a nearly constant dipole radiation luminosity ( ) during the spin-down timescale was favored by observations from GRBs, such as 050801 (de Pasquale et al. 2007), 060729 (Grupe et al. 2007), and 080913 (Greiner et al. 2009). However, some observations of GRB afterglows with rebrightenings or bumps (i.e., ) require that the injection luminosity increases with time (i.e., ). Additionally, there is a plateau phase in the X-ray band of GRB 100814A between 103 and 105 s (Nardini et al. 2014) indicating continuous energy injection from the central engine during this prolonged period.

2017AandA...607A.120P__Warnecke_et_al._(2016)_Instance_1

Outside the TC, the MHD simulation behaves similarly to its HD counterpart, with baroclinicity being the dominant contribution. In terms of balance between left- and right-hand sides of (13), panels A and D show a very good agreement in most of the CZ. Differences are only evident inside the TC in the top layers and slightly near the poles. We attribute these differences to the upper and polar boundary conditions for the magnetic field. The difference observed between panels 12A and D in the top boundary might be due to the radial magnetic field we enforce at the surface. This means that when we have a strong poloidal field located near the surface, it will be forced over a couple grid points by the boundary condition into the radial direction. This is exactly the case of the poloidal field configuration during cycle maximum (see Fig. 3E). This problem might be alleviated in future simulations by introducing more realistic top boundary conditions like that used in Warnecke et al. (2016). The differences between the left- and right-hand sides during cycle minimum (not shown here) are much smaller. It is the radial derivative of the poloidal field present in the second magnetic term of Eq. (13) that is responsible for this “artificial” contribution. There are two other possible sources of error that can explain the minute differences we find in this balance calculation (and in the previous section as well). The first is numerical diffusivity, which we cannot measure directly. The other issue is related with the different numerical methods used to compute derivatives and other composite quantities in the main code during the simulation and a posteriori. During the simulation run, EULAG numerics computes central cell values and fluxes across the cell borders, while the type of analysis that we perform a posteriori assumes values computed in the cell corners using centered finite differences. Differentiation across the poles can also introduce some artifacts. Nevertheless, the very good match obtained in the HD case indicates that these two sources of error are in fact very small, and that the main issue here seems related to the magnetic field boundary conditions. Despite these possible sources of uncertainty, we consider that there is a general good agreement between left- and right-hand sides for most of the CZ.

2019ApJ...871L..22W__Alexandrova_2008_Instance_1

In analogy to the hydrodynamic case, the nonlinear coherent vortex structure also plays an important role in plasma dynamics and transport processes (Hasegawa & Mima 1978; Shukla et al. 1985; Petviashvili & Pokhotelov 1992; Horton & Hasegawa 1994). These vortices tend to have a long lifetime and are widely observed in space, laboratory, and numerical simulation of plasma (Chmyrev et al. 1988; Burlaga 1990; Volwerk et al. 1996; Stasiewicz et al. 2000; Sundkvist et al. 2005; Alexandrova et al. 2006; Alexandrova 2008; Alexandrova & Saur 2008; Vianello et al. 2010; Servidio et al. 2015). An essential subset of these plasma vortices is known as Alfvén vortices, which can be viewed as the cylindrical analog of the nonlinear Alfvén wave (Petviashvili & Pokhotelov 1992). The Alfvén vortices have an axis that is nearly parallel to the unperturbed magnetic field, along which the shape is generally invariant. Thus, these vortices are quasi-2D structures. The associated perpendicular magnetic fluctuations are linearly related with the perpendicular velocity fluctuations, but their relative amplitudes are not obligatorily equal (as is the case in an Alfvén wave): , where ξ is not necessarily equal to 1. In addition, Alfvén vortices do not propagate along in the plasma frame, and they hardly propagate in the perpendicular plane when the axis of the vortex is inclined with respect to that are in contrast with Alfvén wave (Wang et al. 2012). After first being reported in the Earth’s magnetosheath (Alexandrova et al. 2006; Alexandrova 2008), multiscale quasi-bidimensional Alfvén vortices (with ) have been identified in numerous space environments: in slow solar wind (Perrone et al. 2016; Roberts et al. 2016), in fast solar wind (Lion et al. 2016; Perrone et al. 2017), and in Saturn’s magnetosheath (Alexandrova & Saur 2008). It seems that the intermittent structures in fast solar wind are dominated by Alfvén vortices (Perrone et al. 2017), which agrees with the 2D MHD turbulence model (Zank et al. 2017).

2016ApJ...827...47L__Dmitruk_et_al._2004_Instance_1

Given the time-consuming nature of simulating energetic particle acceleration in multiple contracting and reconnecting (merging) small-scale magnetic islands produced by magnetohydrodynamic (MHD) turbulence and particle-in-the-cell (PIC) models on large spatial scales and in three dimensions, there has been an increased effort to develop statistical kinetic transport theories that capture the essential physics of particle acceleration in multi-island regions (de Gouveia dal Pino & Lazarian 2005; Drake et al. 2006, 2010, 2013; Bian & Kontar 2013 ). Recently, Zank et al. (2014) developed a comprehensive kinetic transport theory for small-scale flux ropes (helical magnetic field structures) which, for the first time, unified three different mechanisms currently thought to play an important role in the energization of suprathermal particles traversing solar wind regions containing numerous contracting and reconnecting (merging) small-scale flux ropes. It was argued that magnetic flux ropes in the solar wind can be viewed to first order as being quasi-two-dimensional (quasi-2D) helical contracting and merging flux-rope structures based on three-dimensional (3D) simulations of compressible MHD turbulence that included a strong guide magnetic field (Dmitruk et al. 2004). The three acceleration mechanisms include (i) curvature and grad-B drift acceleration in the motional electric fields generated by the plasma flow at the endpoints of contracting magnetic flux ropes (Drake et al. 2006), (ii) curvature and grad-B drift acceleration in the motional electric fields induced by x-point plasma outflows generated near the center of merging neighboring magnetic islands (Drake et al. 2013), and (iii) acceleration due to field-aligned guiding center motion in the secondary reconnection electric field formed in the x-point region at the center of reconnecting islands (Oka et al. 2010). Interestingly, in Zank et al. (2014) contracting flux ropes were modeled to behave in a compressible manner so that betatron acceleration by the increasing flux-rope field strength also contributes to particle energization. Both Drake et al. (2013) and Zank et al. (2014) consider reconnecting (merging) magnetic islands/flux ropes as incompressible phenomena so that negative betatron acceleration from the decreasing flux-rope field strength reduces particle energization. Zank et al. (2014) found that the mean electric field induced by contracting and merging flux ropes naturally accelerates suprathermal test particles to hard power-law distributions in the supersonic, slow solar wind. The results show that the power-law index depends on the Alfvén Mach number and on the ratio of the diffusion timescale to that for island contraction.

2018ApJ...869...47H__Hoppe_et_al._1994_Instance_1

As for Mg, one would expect to find a positive correlation between δ29Si and initial 18O/16O ratios for the parent stars of category A grains if these quantities represent GCE. Indeed, there is a correlation between δ29Si and initial 18O/16O, as can be seen from Figure 10. The observed trend is a bit shallower than predicted by the GCE model of Timmes & Clayton (1996), which was inferred and extended to higher metallicities from predicted 18O/16O ratios at [Fe/H] = −0.3 (18O/16O = 0.56 × solar) and [Fe/H] = 0 (18O/16O = 1.26 × solar); corresponding δ29Si values are −500‰ ([Fe/H] = −0.3) and +260‰ ([Fe/H] = 0), respectively. It is interesting to note that astronomical observations of a variety of sources have not detected a variation in Si isotope ratios with galactocentric radius, which stands in contrast to the monotonically decreasing trend for the 18O/16O ratio (Monson et al. 2017) and our observations for category A grains. Following the approach of Nguyen et al. (2010), we have inferred a GCE relationship between δ29Si and initial 18O/16O, which is based on a tight correlation between 29Si/28Si and 46Ti/48Ti ratios in SiC mainstream grains (Figure 11, left; data from Hoppe et al. 1994; Alexander & Nittler 1999; Huss & Smith 2007) and a correlation between 46Ti/48Ti and initial 18O/16O ratios in presolar oxide grains (Figure 11, right; data from Choi et al. 1998; Hoppe et al. 2003), interpreted to represent largely GCE. Error-weighted linear regressions yield δ46Ti = (0.98 ± 0.08) × δ29Si-(11 ± 7) for SiC mainstream grains and for Group 1 oxides. Combining the two equations gives , which is labeled as “SiC-Oxides GCE” in Figure 10. Note that this equation is different from the one presented by Nguyen et al. (2010), which was recognized to be in error (L. Nittler 2018, private communication). Gyngard et al. (2018) recently reported a slightly shallower slope for the δ46Ti versus δ29Si of SiC mainstream grains than inferred here, which would make the δ46Ti versus relationship a bit steeper. Our data for category A grains fall to the right of the SiC-Oxides GCE line but are fully compatible with this line if errors for the SiC-Oxides GCE line are taken into account (Figure 10). Finally, the good correlation between δ25Mg and δ29Si (Figure 12) rounds out the picture emerging from presolar silicate category A grains, suggesting that a subset of presolar Group 1 silicates carries resolvable signatures of the GCE of O, Mg, and Si isotopes.

2021MNRAS.503.1319G__Chae_&_Mao_2003_Instance_1

In the first scenario, we assume that neither the characteristic velocity dispersion (σ*) nor the number density (n*) of galaxies evolves with redshifts (νn = νv = 0). Given the redshift coverage of the lensing galaxies in the lens sample (0.06 zl 1.0), if we constrain a non-evolving VDF using the lens data, then, assuming the VDF evolution with redshift is smooth, the fits on the VDF parameters may represent the properties of ETGs at an effective epoch of z ∼ 0.5. Such non-evolving VDF has been extensively applied in the previous studies on lensing statistics (Chae & Mao 2003; Ofek et al. 2003; Capelo & Natarajan 2007; Cao et al. 2012a). By applying the above-mentioned χ2 – minimization procedure to Sample A – we obtain the best-fitting values and corresponding 1σ uncertainties (68.3 per cent confidence level): $\alpha =0.66^{+2.13}_{-0.66}$, $\beta =2.28^{+0.24}_{-0.18}$. It is obvious that the full sample analysis has yielded improved constraints on the high-velocity exponential cut-off index β, compared with the previous analysis of using the distribution of image separations observed in CLASS and PANELS to constrain a model VDF of ETGs (Chae 2005). Suffering from the limited size of lens sample, such analysis (Chae 2005) found that neither of the two VDF parameters (α, β) can be tightly constrained, due to the broad regions in the α − β plane. Consequently, the image separation distribution is consistent with the SDSS measured stellar VDF (Sheth et al. 2003) and the Second Southern Sky Redshift Survey (SSRS2) inferred stellar VDF (Chae & Mao 2003), although the two stellar VDFs are significantly different from each other concerning their corresponding parameter values. We also consider constraints obtained for the Sample B (defined in previous section), with the likelihood is maximized at $\alpha =1.00^{+2.38}_{-1.00}$ and $\beta =2.34^{+0.26}_{-0.24}$, from which one could clearly see the marginal consistency between our fits and recent measurements of three stellar VDFs (especially the SDSS DR5 VDF of ETGs).

2022ApJ...934...63O__Werf_et_al._1988_Instance_1

Cosmic rays (CRs) play a vital role in the chemistry of cold (10–30 K), dense (>102 cm−3) molecular clouds as they can pierce deep into them, unlike interstellar UV radiation (for a review see Indriolo & McCall 2013). These high-energy interstellar particles primarily consisting of protons can be heavier elements and electrons, and have large energy ranges, up to zetaelectronvolt energies (Blandford et al. 2014). Although the energies can be high, it is the lower energy CRs (≤1 TeV) that affect the dense interiors (Viti et al. 2013; Padovani et al. 2020). In these regions, CRs have a wide variety of effects, one of the most important is being a producer of atomic hydrogen through the dissociation of H2 (van der Werf et al. 1988; Montgomery et al. 1995; Li & Goldsmith 2003; Goldsmith & Li 2005; Padovani et al. 2018a). Other important effects are being the dominant source of ionization; regulating the degree of coupling of the gas and the magnetic field; having an important role in the dynamics and the collapse timescale of collapsing clouds (e.g., Padovani et al. 2013, 2014); providing heating and energy to dust grains (de Jong & Kamijo 1973; Shingledecker et al. 2018; Kalvāns & Kalnin 2019; Sipilä et al. 2020, 2021; Silsbee et al. 2021) producing internal UV photons (Prasad & Tarafdar 1983); may have a role on the charge distribution on dust grains (Ivlev et al. 2015); influencing disk growth (Kuffmeier et al. 2020); and affecting deuteration (Caselli et al. 2008). For example, each species ionized by a CR releases an electron. This secondary electron can cause further collisions, which in turn, depending on the energy, can induce more ionization and heating (Ivlev et al. 2021). If a secondary electron does not have enough energy to ionize a species, the species may become excited (Shingledecker & Herbst 2018). Excited species produced by CR bombardment have energy levels higher than their base counterparts, allowing these excited species to overcome some reaction barriers that would otherwise be difficult in cold environments. These species have been shown to drive more complex chemistry from reactions that can form interstellar complex organic molecules (Abplanalp et al. 2016).

2021MNRAS.502.5935S__Hani_et_al._2018_Instance_1

We now turn to constraining c1. First, note that $\mathcal {Z} \gt 0$ for all x. In practice, we ask that $\mathcal {Z} \gt \mathcal {Z}_{\rm {min}}$ for some fiducial $\mathcal {Z}_{\rm {min}} \approx 0.01$. For x ≫ 1, this gives (42)$$\begin{eqnarray*} c_1 \gt \left(\mathcal {Z}_{\mathrm{min}}-\frac{\mathcal {S}}{\mathcal {A}}\right)\, x^{-\frac{1}{2}\left[\sqrt{\mathcal {P}^2+\, 4\mathcal {A}} - \mathcal {P}\right]}_{\mathrm{max}}, \end{eqnarray*}$$where xmax is the outer radius of the disc at which we apply this condition.3 Secondly, the total metal flux into the disc across the outer boundary cannot exceed that supplied by advection of gas with metallicity $\mathcal {Z}_{\rm CGM}$ into the disc, since otherwise this would imply the presence of a metal reservoir external to the disc that is supplying metals to it, which is true only in special circumstances, e.g. during or after a merger (Torrey et al. 2012; Hani et al. 2018), or due to long-term wind recycling through strong galactic fountains (Grand et al. 2019). Mathematically, this condition can be written as (43)$$\begin{eqnarray*} -\underbrace{\frac{\dot{M} \mathcal {Z}}{2\pi x}}_\text{adv. flux} - \underbrace{\kappa \Sigma _g\frac{\partial \mathcal {Z}}{\partial x}}_\text{diff. flux} \ge -\underbrace{\frac{\dot{M} \mathcal {Z}_{\rm {CGM}}}{2\pi x}}_\text{CGM flux}. \end{eqnarray*}$$For x ≫ 1, this translates to, (44)$$\begin{eqnarray*} c_1 \le \frac{2\mathcal {P}\left(\mathcal {Z}_{\mathrm{CGM}} - \mathcal {S}/\mathcal {A}\right)}{\mathcal {P}+\sqrt{\mathcal {P}^2+\, 4\mathcal {A}}}\, x^{-\frac{1}{2}\left[\sqrt{\mathcal {P}^2+\, 4\mathcal {A}} - \mathcal {P}\right]}_{\mathrm{max}}. \end{eqnarray*}$$Thus, we find that c1 is bounded within a range dictated by the two conditions above. Given a value of c1, we can also calculate the Σg-weighted and $\dot{\Sigma }_{\star }$-weighted mean metallicity in the model, (45)$$\begin{eqnarray*} \overline{\mathcal {Z}}_{\Sigma _\mathrm{ g}} = \frac{\int ^{x_\mathrm{max}}_{x_{\mathrm{min}}} 2\pi x \Sigma _{\mathrm{ g}0} s_\mathrm{ g} \mathcal {Z} dx}{\int ^{x_\mathrm{max}}_{x_{\mathrm{min}}} 2\pi x \Sigma _{\mathrm{ g}0} s_\mathrm{ g} dx}, \end{eqnarray*}$$ (46)$$\begin{eqnarray*} \overline{\mathcal {Z}}_{\dot{\Sigma }_{\star }} = \frac{\int ^{x_\mathrm{max}}_{x_{\mathrm{min}}} 2\pi x \dot{\Sigma }_{\star 0} \dot{s}_{\star } \mathcal {Z} dx}{\int ^{x_\mathrm{max}}_{x_{\mathrm{min}}} 2\pi x \dot{\Sigma }_{\star 0} \dot{s}_{\star } dx}. \end{eqnarray*}$$Finding $\overline{\mathcal {Z}}$ is helpful because we can use it to produce a mass-metallicity relation (MZR) that can serve as a sanity check for the model. We show in a companion paper that our model can indeed reproduce the MZR (Sharda et al. 2020b).

2020AandA...644L...7G__Magdis_et_al._2020_Instance_2

As in G18, we compiled existing constraints on the molecular gas fraction fgas of quiescent and pSB galaxies from recent literature, namely: local QGs consisting of the ATLAS3D (Young et al. 2011; Cappellari et al. 2013; Davis et al. 2014) and HRS (Boselli et al. 2014; Lianou et al. 2016) ETG samples as well as the samples of pSB galaxies (hereafter, the “low-z pSB” sample) of French et al. (2015) and Alatalo et al. (2016); at low and intermediate redshift, the ETG sample of Spilker et al. (2018) and the pSB sample of Suess et al. (2017); at intermediate and high redshift, constraints from Hayashi et al. (2018) on gas in z ∼ 1.46 cluster ETGs, as well as on individual galaxies from Sargent et al. (2015), Bezanson et al. (2019), and Rudnick et al. (2017). Given its size, we divided the ATLAS3D sample into high- and low-mass subsamples, choosing 5 × 1010 M⊙ as the cut-off mass. In addition, we also included fgas estimates derived from the (median) stacked FIR spectral energy distributions of ETGs at z ∼ 1.8 (G18; 977 galaxies), z ∼ 1.2, z ∼ 0.8, and z ∼ 0.5 (1394, 1536, and 563 galaxies, respectively; Magdis et al. 2020, hereafter M20). Finally, at higher redshift (z ∼ 3), we converted star formation rates (SFR) estimated from spectroscopy (Schreiber et al. 2018a; D’Eugenio et al. 2020) into gas masses assuming the star formation efficiency found by G18. As a consequence of our zmax = 3.5, we did not include higher-redshift quiescent galaxies (Glazebrook et al. 2017; Schreiber et al. 2018b; Tanaka et al. 2019; Valentino et al. 2020) in the analysis and considered z ∼ 3 galaxies as pSB. The dust-based estimates of G18 and M20 (and, by extension, the z ∼ 3 semi-constraints) assume a gas-to-dust ratio (G/D). It is dependent on metallicity, which is presumed to be solar or higher owing to both the relatively high gas-phase metallicity of MS galaxies at z ≲ 1 (e.g., Mannucci et al. 2010) and the already high stellar metallicities of QGs at z >  1 (Onodera et al. 2015; Estrada-Carpenter et al. 2019). Here we adopted an intermediate value between the solar and supersolar G/Ds used in M20, and we increased the error bars of these points to include both the solar and supersolar confidence estimates. These various samples, which are summarized with their selection criteria in Table B.1, combine into a nonhomogeneous dataset: some were specifically selected as ETGs, and others were based on varying degrees of quiescence. In particular, pSB galaxies are not necessarily truly quiescent and could, in principle, resume normal star formation. However, as a possible precursor of QGs, they provide useful, though not constraining (see Sect. 4), comparison samples for the model. Here we refer to all equally as either QGs or pSB galaxies, and we make the assumption that, on average, these different samples are not otherwise significantly biased with regard to their gas content compared to the full population, given each mass limit and type.

2015ApJ...814....2M__Davies_&_Taylor_1950_Instance_1

The 3D view provided in Figure 1 can be completed through the time evolution of the cross section of the same tube presented in Figure 2 for times t = 13, 35, 48 and 62. In the figure, magnetic field strength (top row) and vorticity (bottom row) maps are drawn on a vertical cut that coincides with the midplane of the box perpendicular to the initial axis of the tube. We confirm that most of the magnetic flux is concentrated at the very top of the structure. The general appearance and evolution of the structures shown are strongly reminiscent of those described by Moreno-Insertis & Emonet (1996), Emonet & Moreno-Insertis (1998) and Cheung et al. (2006) using 2D simulations. We recall a few salient features obtained in those papers and reproduced here: in the initial stages (two leftmost panels), the rising portion of the flux tube has a mushroom shape, akin to an air bubble rising in water (e.g., Davies & Taylor 1950; Collins 1965; Parlange 1969; Wegener & Parlange 1973; Hnat & Buckmaster 1976; Ryskin & Leal 1984; Christov & Volkov 1985). Within the ascending portion of the tube, vorticity is generated at the boundary layer between the tube and the ambient flow, in fact with opposite sign on the either side of the head (bottom row in the figure). Magnetic flux is dragged along the sides of the tube into a trailing pair of counter-rotating vortices. Later in time the wake is fragmented into smaller and smaller vortices because the Reynolds number increases in time due to the expansion of the tube (Cheung et al. 2006). The AMR device allows to see this fragmentation in much more detail than could be obtained in the original work of Emonet & Moreno-Insertis (1998). Inside the head of the tube, on the other hand, the plasma and magnetic field are executing a twisting oscillation, with small velocity compared to the global rise speed. This description of the time evolution of the flux tube structure generally applies to other simulations with comparable levels of refinement even when the twist and curvature vary. The cases with untwisted flux tubes, instead, follow a somewhat different pattern and their evolution is described in the following.

2017ApJ...844..152L__Famaey_et_al._2008_Instance_1

Figure 3 shows the metallicity distribution of the LS. We divided the whole region into square bins with size 3 km s−1 and used color to represent the mean metallicity of each bin. The most prominent feature is the Hyades–Pleiades structure, which includes the Hyades stream (peak 0) and Pleiades stream (peak 1). It exhibits a very metal-rich and consistent distribution; it is well known that the Hyades cluster has a high metallicity ([Fe/H] ∼ 0.13, Heiter et al. 2014). We speculate that some stars of the Hyades stream might be remnants of the Hyades cluster, while others may be the dynamical effect of non-axisymmetric components (Famaey et al. 2008). Though not in sharp contrast, there is a valley with lower metallicity between the horizontal V = −50 km s−1 structure and center. To better present the gap, we picked up a window in the metallicity distribution. We divided the window into parallelogram bins, and the edge parallel to the V axis of each bin equals 1 km s−1. The right panel of Figure 4 shows that the mean metallicity of each bin distributes along with the V direction. In Figure 3, the Hercules I (peak 6) and Hercules II (peak 4) have different metallicities, and peak 4 is definitely different from peak 12 (NEW2). That the Hercules stream has a wide metallicity range (Table 1) is in accord with the purported effect of Galactic bar resonances (Kalnajs 1991; Dehnen 2000; Fux 2001). The upper left side of this plot contains stars moving faster than the LSR. In this region the kinematics suggest peak 13 and peak 14 may be part of the thin disk, although their metallicities are quite low. The Sirius stream (peak 2) is a little more metal-poor than its surroundings and has a very small metallicity scatter. This is similar to the results of Klement et al. (2008), and this supports the notion that the Sirius stream (or at least a part of it) comprises remnants evaporated from a cluster. According to De Silva et al. (2007), HR1614 (peak 11) may be dispersed remnants of star-forming events. New1 (peak 9) is close to peak 11 in both kinematics and metallicity; part of its member stars may be remnants of star-forming events, too. New2 (peak 12) has a large metallicity scatter. It is possible to be induced by other dynamical n:1 resonance of the bar. The γ Leo stream (peaks 7, 10) is more metal-poor than our Sun, and it is rapidly moving toward the center of the Galaxy. Considering that there is a radial metallicity gradient in the Galaxy, we conjecture this structure has drifted inwards from beyond the solar Galactocentric radius.

2015ApJ...807...26T__Zucker_&_Mazeh_1994_Instance_1

The numerous historical radial-velocity (RV) measurements of Capella have been discussed at length in our T09 study, which highlighted how challenging it has been to determine accurate values for the rapidly rotating secondary star ( km s−1), whereas those of the sharp-lined primary ( km s−1) have been quite consistent over the last century. T09 presented 162 new RV determinations for both components based on spectra obtained at the CfA covering only a very narrow wavelength range (45 Å). The RVs were measured using the two-dimensional cross-correlation algorithm TODCOR (Zucker & Mazeh 1994), with synthetic templates appropriate for each star. Because of the limited wavelength coverage, those measurements are susceptible to systematic errors resulting mostly from lines shifting in and out of the spectral window as a function of orbital phase. Therefore, an effort was made to control those biases by performing numerical simulations to determine corrections to the velocities, which were at the level of the final uncertainties in the individual measurements for the secondary, and slightly larger for the primary. Final errors in the RVs as measured from the scatter in the orbital fit were about 0.44 km s−1 for the primary and 0.89 km s−1 for the secondary. A sign that systematic errors remained at some level in the CfA velocities was evident in the residuals of the secondary star shown in Figure 2 of T09, in which a pattern can be seen as a function of orbital phase, with a peak semi-amplitude of about twice the typical error. Possible explanations for this, as discussed by T09, include the presence of spots on the active secondary star, or template mismatch.6 6 In particular, due to limitations in the available library of synthetic spectra they used, the macroturbulent velocity of the templates ( km s−1) was not quite as large as appropriate for giant stars. This also resulted in an overestimation of the rotational velocities of the components, as discussed by T09. An additional indication of possible biases was the fact that a small offset (0.267 ± 0.079 km s−1) was found between the primary and secondary velocities in the global orbital fit of T09 that could not be accounted for by differences in the gravitational redshift between the stars, and was ascribed to similar reasons as the secondary residual pattern.

2015MNRAS.453.3461S__Shakura_et_al._2012_Instance_1

The recent detection of X-ray pulsations in PSR J1023+0038 during the accretion active state (Archibald et al. 2015; Bogdanov et al. 2015) implies that channelled accretion, similar to that seen in higher luminosity accreting millisecond X-ray pulsars, is occurring at a much lower accretion rate, implying that the inner edge of the accretion disc lies close to rcor and a propeller does not form. In this case material can accumulate near rcor and non-stationary accretion can occur as matter piles up around the intrinsically unstable magnetospheric boundary. Accretion discs accreting on to the magnetosphere of a rotating star can end up in a trapped state, in which the inner edge of the disc stays near rcor. The captured material can form a quasi-spherical shell (Pringle & Rees 1972; Shakura et al. 2012) or a new disc structure, known as a ‘dead-disc’ and episodic accretion can occur (D'Angelo & Spruit 2010, 2012). As noted by Patruno et al. (2014), variations in the mass accretion rate of the accretion disc can move the inner disc radius by a factor of 2 or 3. The viscous time-scale defines the time-scale for this drift and to reach a viscous time-scale of 10–100 s requires a region with an annulus of radius ∼10–100 km. The thermal time-scale is given by ttherm ∼ (H/R)2 tvis (where H and R are the height and radius of the disc) and for an inner thin disc with H/R 0.02 implies ttherm few seconds, much lower than the time-scales observed. Thus, in principle, fluctuations in the mass accretion rate can move rm outside rlc ,which allows the radio pulsar to turns on, triggering a transition to the passive state, where the lower X-ray luminosity is produced by a shock between the pulsar wind and innermost accretion flow. An increase in the mass accretion rate pushes the inner edge of the disc back inside the light cylinder and turns off the radio pulsar. The X-ray pulsations are only observed in the active state and not in the passive-state light curves, which suggests that the switching between the passive and active states results in transitions between a non-accreting pure propeller mode and an accreting trapped-disc mode (Archibald et al. 2015).

2019ApJ...884..132K__Tanihata_et_al._2003_Instance_1

First, we discuss the discrepancy of the distribution scale of the radio core positions based on the discussions of the internal shock model (Koyama et al. 2015; Niinuma et al. 2015). As is discussed there, the radio cores in Mrk 501 and Mrk 421 observed at 43 or 22 GHz can usually be considered as the internal shocked regions owing to the convex shape of the radio spectrum peaking around 10 GHz (Giroletti et al. 2008; Sokolovsky et al. 2010; Lico et al. 2012; Blasi et al. 2013). The standard internal shock model of blazars considers that the discrete ejecta with higher speeds (with Lorentz factor Γf) catch up with the preceding slower ejecta (with Lorentz factor Γs), and the collision leads to the nonthermal emission (e.g., Spada et al. 2001; Tanihata et al. 2003; Guetta et al. 2004; Kino et al. 2004; Ghisellini et al. 2005). Based on the model, the distribution scale of the internal shocks (ΔDIS in Figure 7, defined as the difference between the largest distance between the internal shock and the central engine DIS,max and the closest one DIS,min) can be explained as the variation of the Lorentz factors of the ejecta (Koyama et al. 2015; Niinuma et al. 2015), by assuming the Lorentz factor ratio (Γf/Γs) and the initial separation of the ejecta (IIS). The core stable within 200 μas constrained by the VERA can be explained by Lorentz factors within a factor of two variation for the slower ejecta, i.e., 8 ≤ Γs ≤ 17, by assuming a minimum value of 8 (e.g., Kino et al. 2002), Γf/Γs ≤ 1.01 (Tanihata et al. 2003), and IIS ∼ 1 Rs (Koyama et al. 2015). This time we refined the distribution scale of the radio core within 42 μas along its main jet axis, or 4.6 × 103 Rs deprojected (see Figure 7). Based on the same assumptions as in Koyama et al. (2015), to explain the further stable distribution scale of the internal shocks, the variation of Lorentz factors of the slower ejecta is constrained to be much smaller, within 30% or 8 ≤ Γs ≤ 10. On the other hand, the radio core wandering of ΔDIS ∼ 2.6 × 105 Rs in Mrk 421 can be explained by the maximum value as Γs ∼ 60 (with different assumptions; Niinuma et al. 2015). Even by applying the same assumptions to Mrk 421 as those for Mrk 501, the maximum of the slower Lorentz factor is estimated to be Γs ∼ 50, which is still a few times as large as that of Mrk 501. Therefore, even during the X-ray and VHE γ-ray active states in 2012, the maximum Lorentz factors that explain the stability of Mrk 501's core are roughly a few times smaller than those for Mrk 421's wandering core, based on the internal shock model.

2021MNRAS.508.2743A__Kennedy_et_al._2019_Instance_1

Star formation from molecular cloud cores collapse is a chaotic process that is expected to result in initially misaligned and warped discs (Bonnell & Bastien 1992; Bate, Lodato & Pringle 2010; Offner et al. 2010; Bate 2018). We expect this to be the general case for circumbinary discs as well as circumstellar ones. Indeed, some misaligned circumbinary discs have already been reported (e.g. KH 15D Chiang & Murray-Clay 2004; Winn et al. 2004; Lodato & Facchini 2013; Smallwood et al. 2019; Fang et al. 2019; Poon, Zanazzi & Zhu 2021, GG Tau A Köhler 2011; Andrews et al. 2014; Aly, Lodato & Cazzoletti 2018, IRS 43 Brinch et al. 2016, L1551 NE Takakuwa et al. 2017, and HD 98800B Kennedy et al. 2019). Misaligned discs around binaries experience a gravitational torque that leads to radially differential precession, which causes disc warping and twisting. For the gas component, warps are expected to propagate in a wave-like manner in thicker discs with low viscosity that are more relevant in protoplanetary contexts (Papaloizou & Lin 1995; Nelson & Papaloizou 1999; Facchini, Lodato & Price 2013), as opposed to the diffusive warp propagation that occurs in more viscous, thinner discs expected around black holes (Papaloizou & Pringle 1983; Ogilvie 1999; Lodato & Pringle 2007; Lodato & Price 2010). The final state of gas discs precessing around binaries depends on the binary parameters; for circular and low-eccentricity binaries, the disc will align with the binary plane, either in a prograde or retrograde sense depending on the initial misalignment (King et al. 2005; Nixon et al. 2011). For eccentric binaries, discs with high initial misalignments will align in a polar configuration around the binary eccentricity vector (Farago & Laskar 2010; Aly et al. 2015; Martin & Lubow 2017; Zanazzi & Lai 2018). Either way, the disc is susceptible to breaking when the binary torque is larger than the viscous torque and the disc communicates the precession more slowly than it occurs (Nixon, King & Price 2013; Doǧan et al. 2018).

2015ApJ...800...97T___2012_Instance_1

The spectral evolution of an ensemble of stars of various masses can be combined through an IMF and followed over time. Such spectral synthesis codes are valuable tools for ultraviolet spectral libraries (Robert et al. 1993; Rix et al. 2004; Leitherer et al. 2014) and stellar population synthesis codes such as Starburst99 (Leitherer et al. 1999). Figure 12 shows a series of spectra for a cluster starburst containing 105 M in which the stars follow a Salpeter IMF (0.1 ⩽ m ⩽ 120). The two panels show model spectra at times t = 0, 1, 3, 5, and 7 Myr after a coeval burst of star formation, using evolutionary tracks with rotation, at solar metallicity (Z = 0.014 from Ekström et al. 2012) and at sub-solar metallicity (Z = 0.014 from Georgy et al. 2013). These models were created by a Monte Carlo sampling of stars for each mass for which we have an evolutionary track (m = 20, 25, 32, 40, 60, 85, 120). For the Salpeter differential mass distribution, ξ(m) = Km−α with α = 2.35, the fraction of stars above mass m is given by 8The constant K is normalized to the total cluster mass M = 5.862 K, and the total number of stars N = 16.582 K for mass limits mmin = 0.1 and mmax = 120. For M = 105 M, we expect a mean number stars and mean stellar mass 〈m〉 = M/N = 0.354 M. In many of our Monte Carlo samples the numbers fluctuate about this value, with small numbers at the high-mass end of the IMF. The mean numbers of stars at the high-mass end are N(> 60 M) ≈ 30 and N(> 100 M) ≈ 5. If the upper mass was extended to mmax = 200, we would expect 40 stars above 60 M and 15 stars above 100 M. As discussed earlier, the existence of these very massive stars is controversial, owing to resolution effects. Moreover, the LyC from stars at m > 100 M may not escape the embedded cloud from which they formed, or from the dense gas produced in mass-loss episodes or binary mergers (Smith 2014). We therefore do not consider stars above the 120 M track.

2021ApJ...922...78X__Nan_et_al._2011_Instance_1

Fast radio bursts (FRBs) are bright, cosmological origin, and millisecond-duration bursts in radio wavelengths (Lorimer et al. 2007; Thornton et al. 2013; Bassa et al. 2017; Macquart et al. 2020). After the discovery of the first FRB (Lorimer et al. 2007), a number of dedicated facilities have been conducted to search FRBs, such as the Parkes telescope (e.g., Bhandari et al. 2018), the updated Molonglo Observatory Synthesis Telescope (e.g., Farah et al. 2018), the Australian Square Kilometre Array Pathfinder (e.g., Shannon et al. 2018), the Canadian Hydrogen Intensity Mapping Experiment (CHIME; The CHIME/FRB Collaboration et al. 2018), the Deep Synoptic Array (Kocz et al. 2019; Ravi et al. 2019), the Green Bank Telescope (Masui et al. 2019), Arecibo (Spitler et al. 2014; Patel et al. 2018), and the Five-hundred-meter Aperture Spherical radio Telescope (FAST; Nan et al. 2011; Li et al. 2019). All these efforts result in an increasing rate of new FRB detections. Among them, more than 20 repeating FRBs have been reported. Particularly, the physical origin of the repeating FRB 20121102A was identified to be with a low-metallicity star-forming dwarf galaxy at a redshift 0.19273 (Bassa et al. 2017; Tendulkar et al. 2017). Another repeating FRB 20190523A was found to be associated with a more massive but low specific star formation rate (Ravi et al. 2019). The identification of the counterpart of the brightest radio bursts from SGR 1935+2154 as a magnetar in our Galaxy by HXMT (Li et al. 2021) and INTEGRAL (Mereghetti et al. 2020) with short-duration X-ray bursts suggests that at least a fraction of FRBs are connected with newborn magnetized neutron stars (e.g., Weltman & Walters 2020; Zhang 2021). More bursts with similar characteristics need to be detected in the future to confirm this conclusion. Recently, a new large sample with 535 FRBs was presented by CHIME/FRB Collaboration et al. (2021) that were detected by the CHIME survey, including 61 bursts from 18 previously reported repeating sources and 474 one-off bursts. Though an increasing catalog of theories and models is developing to explain the physical nature of FRBs (e.g., see the review of Platts et al. 2019; Xiao et al. 2021), the origin of FRBs remains a mystery.

2018AandA...615A.148D__Weidner_et_al._(2010)_Instance_2

The last column in Table 1 reports the number of OB stars minus the “diffuse” population estimated from their density in the Reference field (22.5 stars per square degree): as is immediately seen, the M-star statistics is much larger than the OB star statistics. This can hardly be considered surprising, if an ordinary IMF (e.g., that from Weidner et al. 2010) is assumed for the star-formation region. In Fig. 19 we show the density ratio between M and OB stars, which provides a consistency test between our results and a plausible IMF: this ratio varies however by a large factor, close to 20, among our subregions. This might reflect differences in the respective IMFs, but also differences in completeness among the stellar samples considered for the various regions. We first note that the ratio between M and OB stars in NGC 6231 is dramatically lower than anywhere else in Sco OB1. We can indeed expect that M stars are detected less efficiently in the inner parts of NGC 6231, where the density of bright stars is very large, and their diffuse glare raises the limiting magnitude locally. As already discussed above in Sect. 4.1, this causes our sample of M stars in NGC 6231 to be highly incomplete. Moreover, we determined above that NGC 6231 is significantly more extincted, by almost half a magnitude in V, than Tr 24, and this implies a higher minimum detectable mass among NGC 6231 M stars compared to Tr 24 (see the MDA diagrams in Fig. 5); this effect reduces the completeness of the M-star sample in NGC 6231 more than in Tr 24. If Tr 24 is also slightly younger than NGC 6231, as we argue below, our M-stars in Tr 24 will reach down to lower masses than in NGC 6231, with a steep increase in the detected M-star population: adopting the IMF from Weidner et al. (2010), the predicted number of cluster M stars doubles considering the mass interval 0.25–0.5 M⊙ rather than 0.35–0.5 M⊙. If Tr 24 is younger than NGC 6231, moreover, its stars in the mass range 2.5–3 M⊙ might not have yet reached their ZAMS position as B stars, and therefore would not be counted among OB stars; this would further raisethe M/OB star ratio there by up to 30%. Therefore, the proportions of both M and OB stars that are detected in a young cluster will depend on their age and extinction, in accordance with the MDA diagrams, even for a fixed, spatially uniform photometric sensitivity. We estimated using the Weidner et al. (2010) IMF the expected range for the observed M/OB number ratio. Siess et al. (2000) predict that the latest-type B stars have a mass of ~ 3.5 M⊙ at 2 Myr, and ~ 2.2 M⊙ at 10 Myr, that is, in the range of ages expected for Sco OB1 clusters. The MDA diagrams of Fig. 5 predict that the lowest-mass stars we are able to detect using the available Sco-OB1 data have ~ 0.2 M⊙, even assuming the most favorable (and unlikely) circumstances of an age less than 2 Myr and negligible reddening. The extreme values found for the M/OB ratio are then ~ 3.8 for a minimum M-star mass as high as 0.35 M⊙ and an old age of 10 Myr, and ~ 20 for a minimum M-star massas low as 0.2 M⊙ and age of 2 Myr. These extremes are also shown as horizontal lines in Fig. 19. We note that the M/OB ratio in NGC 6231 falls well within this range; however, both Tr 24 regions are significantly richer of M stars than expected, by more than a factor of two and well above (statistical) errors. If true, then paradoxically this part of the OB association would form preferentially lower-mass stars. Of course, more detailed studies are needed to confirm this result. In the G345.45+1.50 region the M/OB ratio is highest, and far above predictions from the IMF: we may tentatively explain this since this region is very young, and some of its most massive members, like IRAS 16562-3959, are still in formation, thus decreasing the number of optically revealed OB stars. The lowest M/OB ratio in NGC 6231 is unlikely to be real, since as discussed above our M-star sample in this densest subregion is likely incomplete.

2017MNRAS.470.1442C__Hurley_et_al._2002_Instance_2

We then allow the synthetic single or binary system to evolve until present time, adopting for our reference model a thin disc age of 10 Gyr (Cojocaru et al. 2014) and a thick disc age of 12 Gyr. This is motivated by the findings of Feltzing & Bensby (2009), who presented a sample of very likely thick disc candidates with ages, on average, well above 10 Gyr and of Ak et al. (2013), who found that thick disc cataclysmic variables have ages up to 13 Gyr. If the synthetic star is single and has time to become a white dwarf, it evolves following the cooling tracks detailed in the following section. If that is the case, the mass of the white dwarf is obtained from the initial-to-final mass relation (IFMR) according to the prescription from Hurley, Tout & Pols (2002). If the object is member of a binary system and the primary star has time to become a white dwarf, then the pair can evolve through two different scenarios. In the first scenario, the binary evolves without mass transfer interactions as a detached system and the primary star evolves into a white dwarf that subsequently cools down following the cooling sequences described in the next section. In this case, the mass of the white dwarf is also calculated from the IMFR of Hurley et al. (2002). The second scenario involves mass transfer episodes and the evolution of the binary is obtained following the prescriptions of the bse package (Hurley et al. 2002), following the parameter assumptions detailed in Camacho et al. (2014). If the system evolves though the common envelope phase, we use the α-formalism as described in Tout et al. (1997), with αCE being the efficiency in converting orbital energy into kinetic energy to eject the envelope (assumed to be 0.3 in our reference model). This implementation also takes into account the αint parameter (assumed to be 0.0 in our reference model), first presented in Han, Podsiadlowski & Eggleton (1995), describing the fraction of the internal energy (thermal, radiation and recombination energy) used to eject the envelope. As described in Camacho et al. (2014), the αint parameter is used to include the effects of the internal energy in the binding energy parameter λ, which is thus not taken as a constant, but computed using a specific algorithm (Claeys et al. 2014) in bse. In the current version of the code, provided that a positive value is used, the parameter αint represents the fraction of recombination energy that contributes to eject the envelope. It is important to note that the thermal energy of the envelope is always taken into account (using the virial theorem) even if αint is set to zero. For a more detailed discussion on how this is implemented in the latest version of BSE and important comments on the correct use of BSE and the notations used in the code itself, we direct the reader to Zorotovic, Schreiber & Parsons (2014a), mentioning that the notations αint or αrec are, in our case, equivalent.

2018MNRAS.476..814H__Byun_et_al._2017_Instance_1

The most general third-order statistics is the three-point correlation function (hereafter referred to as 3PCF), which is defined in configurations space. Alternatively, one can study its Fourier space counterpart, the bispectrum. These two statistics contain, in principle, the same information. However, their analyses implicate different limitations and challenges, which can affect the physical interpretation of the results. A main advantage of the bispectrum is that an analysis in Fourier space allows for a clear exclusion of high-frequency modes in the density fluctuations, which are difficult to interpret theoretically due to their highly non-linear evolution. In configuration space, these high-frequency modes contribute to the 3PCF, in principle, at all scales. In practice, one therefore needs to restrict the analysis to large scales, where their contribution is negligible, lavishing a lot of valuable data. Another advantage of the bispectrum is that its covariance is diagonal for Gaussian density fluctuations. This approximation works well, even for evolved density fields, while deviations from Gaussianity can also be taken into account (Scoccimarro 2000; Sefusatti et al. 2006; Chan & Blot 2017). The covariance of the 3PCF, on the other hand, is not diagonal, even for Gaussian fluctuations, which makes the modelling more difficult (Srednicki 1993; Slepian & Eisenstein 2015; Byun et al. 2017; Gualdi et al. 2017). An additional difference in the analysis of the bispectrum and the 3PCF lies in the fact that the computation of the latter is more expensive. However, this aspect can be tackled by employing advanced algorithms and appropriate computational resources, as done in this work (see also, Barriga & Gaztañaga 2002; McBride et al. 2011a; Jarvis 2015; Slepian & Eisenstein 2015, and references therein). Besides its disadvantages, there are some arguments that speak for the 3PCF. One of them is the fact that the amplitude of the 3PCF (but not its errors) is not affected by shot-noise, whereas the latter affects the bispectrum amplitude at all scales and hence needs to be modelled for correcting the measurements. In addition, an analysis in configuration space has the advantage that complicated survey masks can be easily taken into account in the analysis of observational data, while in Fourier space such masks impose complicated effects on the measured bispectrum, which are difficult to model (e.g. Scoccimarro 2000). A more general consideration is that it is easier to interpret effects such as redshift space distortions or baryon acoustic oscillations (BAOs) on the statistics in configuration space, since that is where the physical processes that cause these effects happen. Studies of third-order correlations in the literature usually focus on either Fourier or configuration space (e.g. McBride et al. 2011b; Marín et al. 2013; Gil-Marín et al. 2015). However, it is worthwhile studying both statistics and cross-check the results, since their different advantages and disadvantages are quite complementary.

2020MNRAS.494.4382S___2010_Instance_1

It has been thought that QPOs originate from the innermost part of an accretion disc, which is associated with strong gravity, so that we might detect general relativistic effects. Miller et al. (1998) proposed beat-frequency models and estimated the parameters of NSs using this model. Stella & Vietri (1999) developed the relativistic precession model. In the last 20 years, disc-oscillation and resonance models and wave models have been proposed (e.g. Osherovich & Titarchuk 1999; Abramowicz & Kluźniak 2001; Abramowicz et al. 2003; Zhang 2004; Li & Zhang 2005; Erkut, Psaltis & Alpar 2008; Shi & Li 2009, 2010; Shi 2011; Shi, Zhang & Li 2014, 2018; de Avellar et al. 2018). Shi & Li (2009, 2010) obtained the twin modes of MHD waves in LMXBs (including NS LMXBs and black hole LMXBs), which are considered as the sources of high-frequency QPOs. Shi, Zhang & Li (2014, 2018) also considered the waves produced by the two MHD oscillation modes at the magnetosphere radius as the origin of kHz QPOs. A relationship between the frequencies of the twin-peak kHz QPOs and the accretion rate, in which parallel tracks can be explained, was obtained (Shi, Zhang & Li 2018). Recently, many simulations on the oscillations of accreting tori in the accretion process of NS LMXBs (e.g. Kulkarni & Romanova 2013; Parthasarathy, Kluźniak, Čemeljić 2017) have been performed, and almost every model can reproduce some of the observed characteristics of QPOs. However, most models cannot fit the observed data perfectly, the observed data. Belloni, Méndez & Homan (2005) suggested that the twin kHz QPOs showed no intrinsically preferred frequency ratio, and this weakened support for the resonance models. Morsink & Stella (1999) were able to fit the overall NS data with different masses and spins of NSs using the relativistic precession model; however, Belloni, Méndez & Homan (2007) found that there were deviations between the expected and the observed trends. Recently, Török et al. (2016b, 2018) identified the observed QPO frequencies with the frequencies of the epicyclic modes of torus oscillations, and suggested that the relationship between the strong modulation of the X-ray flux and high values of QPO frequencies is connected to the orbital motion in the innermost part of an accretion disc. In addition, there are studies that compared a large set of models with the data of many sources in a complex manner (Lin et al. 2011; Török et al. 2012, 2016a).

2018ApJ...854...17L__Larionov_et_al._2016_Instance_1

Early 15 GHz images using the very long baseline interferometry (VLBI) technique obtained from the very long baseline array (VLBA) indicated a twisted morphology with jet bending on a scale of ∼20 mas (Kellermann et al. 1998), and multi-epoch 43 GHz observations show jet knots with complex kinematics involving a mixture of apparent superluminal motion and as well as stationary components (Jorstad et al. 2001, 2005). Multi-frequency (15 and 43 GHz) multi-epoch observations during the 2006 radio flare (Fromm et al. 2013a) inferred a possible association between a jet component ejection event at the end of 2005 and a strong radio flare in 2006 April. The authors interpreted the 2006 radio flare as a result of the interaction between a propagating shock and a stationary shock at a de-projected distance of 18 pc from the core. Temporal variability studies during the 2012 September–October multi-band flaring period found a near-simultaneous γ-ray and optical flaring behavior, inferring a co-spatial origin (Cohen et al. 2014; Larionov et al. 2016). The latter study in addition suggested that the measured Stokes parameter variations is consistent with a bright jet knot moving along a helical trajectory. A multi-wavelength polarimetric study during the same flaring phase (Casadio et al. 2015) detected a co-spatial origin from the near-simultaneous variability and identified the passage of a superluminal radio knot coincident with the γ-ray flare. Further evidence, including an intra-day optical polarization variability and clockwise rotation of the electric vector position angle (EVPA, , where U and Q are Stokes components) during the flaring phase, is consistent with a jet knot passing a region hosting helical magnetic fields. A study of γ-ray–optical variability in flux density and polarization between prominent flares during the end of 2016 (Larionov et al. 2017) finds no time lag between the light curves indicating co-spatial origin of synchrotron (optical) and inverse-Compton (γ-ray) flux, and a smaller viewing angle (more energetic, emission closer to jet base) compared to a flare in 2012 when interpreted in terms of a blob or shock wave on a helical trajectory. From the above studies, the γ-ray flares may be associated with optical flux and polarization variability, and the jet kinematics and polarization properties may be described in terms of a helical jet.

2021ApJ...914L...6A__Chhiber_et_al._2018_Instance_2

On 2017 November 24 the MMS orbit allowed us to collect measurements in the pristine solar wind, well outside the Earth's magnetosheath and the bow shock, for a long period (i.e., a few times longer than the typical correlation scale) of approximately 1 hour from 01:10 to 02:10 UT. Figure 1 (upper panel) displays an overview of the magnetic field measurements collected by the FIELDS instrument suite (Torbert et al. 2016) on board of MMS1 with a temporal resolution Δt = 128 samples s−1 (Russell et al. 2016). The period of interest is a typical example of slow solar wind stream (V ∼ 377 km s−1), with an average magnetic field 〈B〉 ∼ 6.6 nT and a mean plasma density 〈n〉 ∼ 9 cm−3 (Roberts et al. 2020a, 2020b). This means that the average Alfvén speed is VA ∼ 50 km s−1, while the ion inertial length and gyroradius are di ∼ 76 km and ρi ∼ 96 km, respectively (Chhiber et al. 2018), with the corresponding timescales τd ∼ 1.3 s and τρ ∼ 1.6 s, respectively. As reported in previous works (Bandyopadhyay et al. 2018; Chhiber et al. 2018; Roberts et al. 2020a, 2020b) this interval is characterized by two different spectral scalings: a typical inertial range ∼ τ5/3 is found at large scales (i.e., τ > τb), while a steeper scaling ∼ τ7/3 is found at small scales (i.e., τ τb), with τb ∼ 2.4 s (Roberts et al. 2020a). Furthermore, the magnetic field spectrum flattens near τnoise ∼ 0.2 s, due to the instrumental noise floor near ∼5 Hz (Russell et al. 2016). Finally, a decrease at shorter timescales (e.g., τ ∼ 0.1 s) is due to an anti-aliasing filter of nonphysical origin (Russell et al. 2016; Roberts et al. 2020a). Taken together, this interval is particularly suitable for testing our formalism with respect to processes of both physical and nonphysical origin. The presence of an instrumental noise floor allows us indeed to assess our formalism with respect to purely stochastic processes, while the existence of two spectral regimes (i.e., the MHD/inertial and the kinetic/dissipative) allows us to investigate small- versus large-scale processes and their possible coupling in a dynamical system framework.

2017MNRAS.471.4286F__McConnell_&_Ma_2013_Instance_1

One of the key model ingredients that determines the TDE rates is the distribution of stars in galactic nuclei (Magorrian & Tremaine 1999; Wang & Merritt 2004). Depending on the merger history of the galaxy and the efficiency of feedback on star formation, the stellar density profile can develop either a core or a cusp. For simplicity, we adopt a singular isothermal sphere density profile ρ(r) = σ2/2πGR2 with σ being the constant velocity dispersion and R the halo virial radius. For a galaxy of halo mass Mh, the relation between the halo mass and the velocity dispersion is simply Mh = 2σ2R/G; while the velocity dispersion can be directly related to the black hole mass using the MBH–σ relation (Kormendy & Ho 2013; McConnell & Ma 2013; Baldassare et al. 2015; Saglia et al. 2016; Thomas et al. 2016) (1) \begin{equation} M_{{\rm BH}} = 0.309\times 10^9\times \left(\sigma /200\ \rm{km\,\,s}^{-1}\right)^{4.38}\ \mathrm{M}_{\odot }, \end{equation} which holds for a wide range of black hole masses from 5 × 104 M⊙ (Baldassare et al. 2015) to 1.7 × 1010 M⊙ (Thomas et al. 2016) in galaxies with a bulge (Guillochon & Loeb 2015). Assuming the isothermal stellar distribution, Wang & Merritt (2004) derived TDE rates for galaxies with a single central black hole, while Chen et al. (2009) report the rates in a case of a black hole binary. As we discuss in Section 2.2, for MBH with masses in the range MBH ∼ 105–108 M⊙, the TDE rates per halo computed using the isothermal stellar distribution are similar (within tens of percent) to more realistic estimates based on a large galaxy sample (Stone & Metzger 2016), which justifies our assumption. The error in the rate estimation due to the idealized stellar density profile is small compared to other uncertainties, e.g. introduced by the poorly constrained occupation fraction of IMBHs in low-mass galaxies, which amounts to one–two orders of magnitude uncertainty in the derived volumetric TDE rates.

2022AandA...662A..42M__Vázquez_2007_Instance_1

A number of fundamental results have been rigorously proved in the mathematical literature concerning the asymptotic behaviour in time of some of the solutions of the porous medium equation and related equations (e.g. Kamin & Vázquez 1991; Bernis et al. 1993; Hulshof et al. 2001). What is of interest for us here is, primarily, the results that can be applied to the cylindrically symmetric case with diffusion coefficient which is proportional to the square of the dependent variable (n = 2, m = 3 in the notation of Eq. (7)). The most basic result, already mentioned in Sect. 4.4.1, is that initial conditions which have a finite nonzero flux integral (called ‘the mass’ in the mathematical literature for the PME) converge toward the ZKBP solution with the same flux integral (‘mass’) asymptotically in time (Vázquez 2007, Theorem 18.2); here, allowance is made for either a positive or negative flux integral by globally changing the sign of the ZKBP solution; also, ‘convergence’ is meant in the sense that the Lp norm of the difference between the actual solution and the ZKBP function tends to zero as t → ∞ faster than a negative power of the time with an exponent which is a function of n, m, and p (e.g. −1/3 for n = 2 and m = 3 in the L2 norm; see details in the book by Vázquez 2007). A complementary result is the following: when the initial condition has positive net flux and its negative part has compact support, then the whole solution evolves into a positive function after a finite time (Vázquez 2007, Theorem 18.29). Since we are dealing with signed functions which have zero flux integral, these results are of interest mainly because they impose a strict condition on the possible flux imbalance caused by numerical errors (as discussed in Sect. 4.4.1, final paragraph): if it is not small, the numerical solutions will approach the ZKBP solution in a comparatively short time. However, the flux imbalance in all the Bifrost experiments discussed in the present paper is small enough that they have not shown this behaviour even though they have been run until a very long diffusive time.

2017ApJ...846...52G__Mauche_et_al._1995_Instance_1

In addition to the above problem in the UV spectroscopy of disk-dominated systems, X-ray data of CVs have also been in strong disagreement with theoretical expectations for more than three decades (Ferland et al. 1982). The culprit has been the difficult to study boundary layer (BL) between the accretion disk and the WD star. About half of the disk accretion energy (in the form of kinetic energy) is expected to be dissipated in the BL between the Keplerian disk and slowly rotating stellar surface (Pringle 1981). Because of its small size, the BL was predicted to emit in the X-ray band: at low accretion rates (when the WD is dominant in the UV), the BL was expected to be optically thin and emit hard X-rays (Pringle & Savonije 1979; Tylenda 1981; Narayan & Popham 1993); at large accretion rates, typical of NLs in a high state and DNe in outburst, the BL was expected to be optically thick and emit soft X-rays (Pringle 1977; Narayan & Popham 1993; Popham & Narayan 1995). Systems in the low state indeed reveal optically thin hard X-ray emission (Szkody et al. 2002; Pandel et al. 2005; Mukai et al. 2009). However, systems in a state of high mass accretion often do not show an optically thick soft X-ray component; instead, many exhibit optically thin hard X-ray emission (Patterson & Raymond 1985a, 1985b; Mauche et al. 1995; van Teeseling et al. 1996; Baskill et al. 2005; Balman et al. 2014), with an X-ray luminosity much smaller than expected, i.e., much smaller than the disk luminosity. While optically thin hard X-ray emission from high mass accretion rate systems was unexpected, it is, however, not especially inconsistent with the theoretical work: optically thin BLs can occur in high mass accretion rate systems, since the transition to being optically thin depends not only on the mass accretion rate, but also on the WD mass, the WD rotation rate, and the (unknown) alpha viscosity parameter (Popham & Narayan 1995). Simulations of optically thin BLs (Narayan & Popham 1993; Popham 1999) show that the inner edge of the Keplerian (and optically thick) disk starts at an actual radius R0 = Rwd + δBL, where the size δBL of the BL is of the order of the stellar radius Rwd: δBL ∝ Rwd (the BL is actually geometrically thick). The direct consequence of having an optically thin and geometrically thick BL is that the optically thick Keplerian disk will appear to have an inner hole of size δBL (possibly of the order of the radius of the WD Rwd). Two decades ago, it had already been pointed out that optically thin BL can explain the inner hole observed in circumstellar disks around young stellar objects (T Tauri stars; Godon 1996). In other words, optically thin BLs are consistent not only with the X-ray data, but also with the UV data, as truncated optically thick disks produce a UV continuum with a shallow slope in better agreement with the UV observations than non-truncated disks.

2021AandA...655A..98A__Agliozzo_et_al._2019_Instance_1

We have employed a simple grey-body fitting method to model the infrared SED of individual sources. In the LMC, which has the most numerous list of LBVs, large amounts of dust are observed (∼10−3 − 10−2 M⊙), similar to Galactic LBVNe. We stacked the infrared images of the LMC LBVs and extracted the photometry of the resulting source, detected up to 160−250 μm. The integrated SED from the stacks resembles that of LBVs with a strong ionised stellar wind and an extended dusty nebula. The SED can be fitted with only two components: a power-law describing the free-free spectrum of ionised stellar winds and the stellar photosphere, and a single-component grey-body for the dust. For the grey-body we adopted two different values of the κ parameter, including the value determined by Gordon et al. (2014) to fit the integrated ISM SED of the LMC. A significant contribution to the stack SED comes from a few sources, the most important one is RMC143. This was already identified as a massive nebula (Agliozzo et al. 2019). We obtain an integrated present dust mass of 0 . 11 − 0.03 + 0.06 M ⊙ $ 0.11^{+0.06}_{-0.03}\,M_{\odot} $ . We have repeated a similar analysis on the sample of AGBs and RSGs by Riebel et al. (2012). We obtain a detection in the stacked images only when considering the “extreme”-AGBs. We find that the integrated 160 μm emission of 1342 extreme-AGBs is of the same order of magnitude as that of 18 LBVs. The integrated dust mass from these sources is 1 . 2 − 0.4 + 0.3 × 10 − 4 M ⊙ $ 1.2^{+0.3}_{-0.4}\times 10^{-4}\,M_{\odot} $ . We do not find any correlation between the dust masses and the stellar luminosities. This could be due to the fact that such stars have different evolutionary histories or that the dust production mechanism does not depend on the initial mass of the star. Most likely we are also unable to detect the lowest-mass nebulae. To estimate the total dust mass produced by LBVs in the LMC during its full lifetime, we consider two cases: constant number of LBVs across time and a case accounting for IMF and SFH. The uncertainty on the duration of LBV phase in the first case, or on the population of LBVs in the second case, add a significant uncertainty in the total mass produced by LBVs.

2022MNRAS.513.1459M__Kaviraj,_Martin_&_Silk_2019_Instance_1

Hierarchical structure formation scenarios (e.g. Fall & Efstathiou 1980; van den Bosch et al. 2002; Agertz, Teyssier & Moore 2011) predict that massive galaxies acquire much of their stellar mass through a combination of continuous cold gas accretion and mergers with smaller objects (e.g. Press & Schechter 1974; Moster, Naab & White 2013; Kaviraj et al. 2015; Rodriguez-Gomez et al. 2016; Martin et al. 2018b; Davison et al. 2020; Martin et al. 2021). As a consequence, mergers are also expected to play a significant role in driving the evolution of galaxy properties, for example, by triggering (Schweizer 1982; Mihos & Hernquist 1996; Duc et al. 1997; Elbaz & Cesarsky 2003; Kaviraj et al. 2011; Lofthouse et al. 2017; Martin et al. 2017) or quenching (Schawinski et al. 2014; Barro et al. 2017; Kawinwanichakij et al. 2017; Pontzen et al. 2017) star formation in the host galaxy or by driving its morphological evolution (e.g. Toomre 1977; Conselice, Yang & Bluck 2009; Dekel, Sari & Ceverino 2009; Taranu, Dubinski & Yee 2013; Naab et al. 2014; Fiacconi, Feldmann & Mayer 2015; Graham, Dullo & Savorgnan 2015; Deeley et al. 2017; Gómez et al. 2017; Welker et al. 2017; Martin et al. 2018a; Jackson et al. 2019). Signatures of past mergers take the form of faint extended tidal features such as tails (e.g. Pfleiderer 1963; Toomre & Toomre 1972; Peirani et al. 2010; Kaviraj 2014; Kaviraj, Martin & Silk 2019), or plumes (e.g. Lauer 1988) – which are typically produced by major mergers – and streams (e.g. Johnston, Sigurdsson & Hernquist 1999; Shipp et al. 2018; Martinez-Delgado et al. 2021) or shells (e.g. Malin & Carter 1983; Quinn 1984) – which mainly arise from minor interactions – as well as in the structure of the surrounding diffuse light (e.g. Choi, Guhathakurta & Johnston 2002; Graham 2002; Johnston, Choi & Guhathakurta 2002; Seigar, Graham & Jerjen 2007; Kaviraj et al. 2012; Monachesi et al. 2016, 2019; Iodice et al. 2019; Montes 2019). These features, which arise from many different types of encounter, hold a fossil record of the host galaxy’s past interactions and mergers which can be used to reconstruct its assembly history and dynamical history (Johnston et al. 2008; Martínez-Delgado et al. 2009; Belokurov et al. 2017; Montes et al. 2020; Ren et al. 2020; Spavone et al. 2020; Vera-Casanova et al. 2021). However, the majority of tidal features are expected to have surface brightnesses fainter than 30 mag arcsec−2 in the r-band (Johnston et al. 2008). Although pushing towards these kinds of limiting surface brightnesses remains extremely challenging, it is nevertheless desirable to do so, being necessary to uncover a more detailed history of local Universe. This is not only vital for our understanding of hierarchical galaxy assembly (e.g. Johnston, Sackett & Bullock 2001; Wang et al. 2012), but also serves as a novel galactic scale probe of more fundamental physics such as theories of gravity (e.g. Gentile et al. 2007; Renaud, Famaey & Kroupa 2016) and dark matter (Dubinski, Mihos & Hernquist 1996; Kesden & Kamionkowski 2006; Dumas et al. 2015; van Dokkum et al. 2018; Montes et al. 2020). In particular, tidal structure is a powerful tracer of the underlying galactic halo potential (e.g. Dubinski, Mihos & Hernquist 1999; Varghese, Ibata & Lewis 2011; Bovy et al. 2016; Ibata et al. 2020; Malhan, Valluri & Freese 2021).

2016ApJ...830..156M__Villforth_et_al._2014_Instance_1

Comparison to a sample of inactive galaxies is also key to demonstrating that an observed merger fraction is actually related to AGN activity. Large samples of inactive galaxies are observed at all merger stages, so it is clear that a major merger alone is not a sufficient condition for quasar activity. Thus, to conclusively demonstrate that mergers are an important channel for quasar fueling, we would need to observe an enhancement to the merger fraction in quasar hosts relative to a matched sample of inactive galaxies. Several studies of lower-luminosity AGN host morphologies with inactive control samples have been conducted in HST extragalactic survey fields (e.g., Grogin et al. 2005; Gabor et al. 2009; Cisternas et al. 2011; Schawinski et al. 2011; Kocevski et al. 2012; Böhm et al. 2013; Villforth et al. 2014). In particular, we designed our study methodology following Cisternas et al. (2011), who used visual classification to compare strong distortion signatures in moderate-luminosity X-ray selected AGN hosts to a comparison sample of inactive galaxies in the redshift range z = 0.3–1.0. They found no significant enhancement to the merger fraction of AGN hosts relative to inactive galaxies, demonstrating that the majority of cosmic black hole mass accretion at , i.e., in AGN with inferred SMBH masses (Vestergaard & Osmer 2009), is not merger driven. How do we then reconcile this result with the results from the red quasar and radio galaxy studies? One possibility is that certain sub-classes of AGN may be preferentially merger driven, even though the bulk of all objects are not. In particular, a downsizing trend has been observed, such that near the peak of quasar activity at z = 2, higher-mass SMBHs dominate the cosmic mass accretion ( , Vestergaard & Osmer 2009). It is possible that forming these most massive black holes requires major mergers, as a particularly efficient gas transport mechanism, and that the declining major merger rate of galaxies is one of the driving forces behind this downsizing trend.

2019MNRAS.488.5029H__Stacey_et_al._2010_Instance_1

For the first time, we detected [C ii] 158-μm emission from a GRB host galaxy at z > 2. This is the second detection of [C ii] 158-μm emission among known GRB host galaxies, following GRB 980425 (Michałowski et al. 2016). The [C ii] 158-μm fine structure line is the dominant cooling line of the cool interstellar medium, arising from photodissociation regions (PDR) on molecular cloud surfaces. It is one of the brightest emission lines from star-forming galaxies from FIR to metre wavelengths, almost unaffected by dust extinction. [C ii] 158-μm luminosity, L[C II], has been discussed as an indicator of SFR (e.g. Stacey et al. 2010). If L[C II] scales linearly with SFR, the ratio to FIR luminosity, L[C II]/LFIR, is expected to be constant, since LFIR is a linear function of SFR (e.g. Kennicutt 1998a). However, LC II/LFIR is not constant, but declines with increasing LFIR, known as the ‘[C ii] deficit’ (e.g. Luhman et al. 1998, 2003; Malhotra et al. 2001; Sargsyan et al. 2012; Díaz-Santos et al. 2013, 2017; Spilker et al. 2016). The [C ii] deficit persists when including high-z galaxies (e.g. Stacey et al. 2010; Wang et al. 2013; Rawle et al. 2014). In Fig. 5, we compare the [C ii] deficit in the GRB 080207 host and other star-forming galaxies. Two GRB hosts are shown by stars: GRB 080207 (orange star) and 980425 (blue star). The comparison sample is compiled from the literature up to z ∼ 3 (Malhotra et al. 2001; Cormier et al. 2010, 2014; Ivison et al. 2010; Stacey et al. 2010; Sargsyan et al. 2012; Farrah et al. 2013; Magdis et al. 2014; Brisbin et al. 2015; Gullberg et al. 2015; Schaerer et al. 2015). Active galactic nuclei are separated from star-forming galaxies based on either (i) the explicit description in the literature or (ii) EWPAH 6.2μm 0.1 (Sargsyan et al. 2012). As reported by previous studies (e.g. Maiolino et al. 2009; Stacey et al. 2010), high-z galaxies are located at a different place from local galaxies in the L[C II]/LFIR–LFIR plane.

2016MNRAS.459.3161C__Lorimer_&_Kramer_2012_Instance_1

For an informed opinion on the expected fluxes and durations of short transients, we have to understand coherent emission processes. What we know from incoherent emission physics is that the intrinsic brightness temperature of sources is likely limited to 1011 − 12 K (e.g. Kellermann & Pauliny-Toth 1969; Singal 1986, where brightness temperature is defined as the value of T in the Rayleigh–Jeans formula that yields the correct flux of the source). Sources having brightness temperatures above about 1012 K must emit coherently, have their emission relativistically boosted, or both. However, we understand the processes underlying such sources very poorly, and so in this paper, we shall take the approach of expecting a wide range of known and unknown types of source, and exploring as much of parameter space as our experiment allows. One important thing to note, that is particularly relevant here, is that most of those coherent emitters for which we know the properties of the radio spectrum have quite steep spectra, typically going as ν−2 or even ν−3 (see e.g. Melrose 2009; Lorimer & Kramer 2012), in contrast with a typical ν−0.8 for optically thin synchrotron emission. This means that low-frequency instruments such as LOFAR may be intrinsically at an advantage to find coherent emitters (in addition to having larger fields of view). While known coherent transients have mostly been found in beam-formed searches and last milliseconds to seconds, more recently fast transients have been discovered in low-frequency image plane surveys. For example, the sources GCRT J1745-3009 (Hyman et al. 2005) and GCRT J1746-2757 (Hyman et al. 2002) were detected at 330 MHz with the VLA, while GCRT J1742-3001 (Hyman et al. 2009) was discovered at 235 MHz with the Giant Metrewave Radio Telescope. These sources showed bright flares lasting from minutes to a few hours. More recently, the low-frequency radio transient ILT J225347+862146 (Stewart et al. 2016) was discovered at 60 MHz with LOFAR, lasting about 10 min. The only significant population of transient radio sources previously known in this duration range are relatively nearby and low-luminosity flare stars, having fluxes of about 1 Jy at 1.2 GHz (Osten & Bastian 2006).

2020ApJ...889..164M__Romani_et_al._2004_Instance_1

The hard X-ray band has been crucial to studying some of the most powerful blazars (see e.g., Tavecchio et al. 2000; Massaro et al. 2004a, 2004b, 2006; Donato et al. 2005). More recently, the outstanding sensitivity of the Nuclear Spectroscopic Telescope Array (NuSTAR, 3–79 keV, Harrison et al. 2013) has enabled us to find and study some of the most distant and luminous ones (e.g., Sbarrato et al. 2013; Tagliaferri et al. 2015; Ajello et al. 2016; Paliya et al. 2016; Sbarrato et al. 2016; Marcotulli et al. 2017). Harboring highly relativistic jets pointed closely at the observer (θV 1/Γ, θV being the viewing angle and Γ the bulk Lorentz factor, Γ ∼ 10−15, Urry & Padovani 1995), this subclass of the Active Galactic Nuclei (AGNs) is home to some of the most energetic particle acceleration and radiation processes known in astrophysics. The boost in flux ascribed to relativistic beaming, arising from the peculiar orientation of the jets, renders them visible at redshifts well beyond z = 2 (the farthest blazar detected so far is at z = 5.47, Romani et al. 2004), making them extraordinary beacons with which to explore the early universe. Their typical double-hump spectral energy distribution (SED) spans the whole electromagnetic spectrum and is shaped by the nonthermal processes occurring in the jets. Relativistic electrons, spiraling along the magnetic field lines, undergo both synchrotron and inverse Compton (IC) processes. The first produces a peak in the SED located between infrared and X-ray frequencies. The second instead results in a peak located between X- and γ-ray energies. If the electrons interact with a source of low-energy photons within the jet, this is referred to as Synchrotron Self Compton (SSC, e.g., Ghisellini & Maraschi 1989), whereas if the photons are external to the jet (i.e., the accretion disk, the torus, and/or the broad line region, BLR), it is referred to as External Compton process (EC, e.g., Sikora et al. 1994). Based on their optical spectra, blazars are usually classified either as BL Lacertae objects (BL Lacs) or flat spectrum radio quasars (FSRQs), the first showing weak or no emission lines, the second showing broad (EW > 5 Å) ones. Following Abdo et al. (2010a), these sources can also be classified according to the position of the synchrotron peak ( ), with low-, intermediate-, and high-synchrotron peak (LSP, ISP, HSP) blazars having, respectively, Hz, Hz, and Hz. FSRQs usually belong to the LSP class and at the high-luminosity end of such subclass are the so-called “MeV blazars,” whose high-energy peak falls in (or close to) the MeV band. With bolometric luminosities exceeding 1048 erg s−1, these are among the most powerful objects in the universe. In fact, they host powerful relativistic jets (Ghisellini et al. 2014), are usually found at high-redshift (z > 2, e.g., Ajello et al. 2009; Ghisellini et al. 2010; Ackermann et al. 2017; Marcotulli et al. 2017), and typically host billion solar mass black holes (e.g., Ghisellini et al. 2010; Paliya et al. 2017a).

2019AandA...629A..54U__Marinucci_et_al._2015_Instance_3

NGC 2110. NGC 2110 is another nearby (z = 0.00779, Gallimore et al. 1999), X-ray bright Seyfert galaxy. Diniz et al. (2015) report a black hole mass of 2 . 7 − 2.1 + 3.5 × 10 8 M ⊙ $ 2.7^{+ 3.5}_{- 2.1} \times 10^{8}\,{{M}_{\odot}} $ , from the relation with the stellar velocity dispersion. From BeppoSAX data, Malaguti et al. (1999) found the X-ray spectrum to be affected by complex absorption. This has been later confirmed by Evans et al. (2007), who find the Chandra+XMM–Newton data to be well fitted with a neutral, three-zone, partial-covering absorber. Rivers et al. (2014) find the Suzaku data to be well fitted with a stable full-covering absorber plus a variable partial-covering absorber. A soft excess below 1.5 keV is also present (Evans et al. 2007), and possibly due to extended circumnuclear emission seen with Chandra (Evans et al. 2006). No Compton reflection hump has been detected with Suzaku (Rivers et al. 2014) or NuSTAR (Marinucci et al. 2015), despite the presence of a complex Fe Kα line. According to the multi-epoch analysis of Marinucci et al. (2015), the Fe Kα line is likely the sum of a constant component (from distant, Compton-thick material) and a variable one (from Compton-thin material). Concerning the high-energy cut-off, ambiguous results have been reported in literature (see Table 1). Ricci et al. (2017) report a value of 448 − 55 + 63 $ 448^{+63}_{-55} $ keV, while Lubiński et al. (2016) report a coronal temperature of 230 − 57 + 51 $ 230^{+51}_{-57} $ keV and an optical depth of 0 . 52 − 0.13 + 0.14 $ 0.52^{+ 0.14}_{- 0.13} $ . From 2008–2009 INTEGRAL data, Beckmann & Do Cao (2010) report a cut-off of ∼80 keV with a hard photon index, but these results are not confirmed by NuSTAR (Marinucci et al. 2015). Indeed, only lower limits to the high-energy cut-off have been found with NuSTAR (210 keV: Marinucci et al. 2015), Suzaku (250 keV: Rivers et al. 2014) and BeppoSAX (143 keV: Risaliti 2002). No hard X-ray spectral variability has been detected by Caballero-Garcia et al. (2012) and Soldi et al. (2014) from BAT data, despite the significant flux variability.

2020MNRAS.499..462S__Quillen_2002_Instance_1

The physical nature of the X-structures themselves is also an open question, although significant progress has already been made in this direction. The spatial resolution of the models was not very good in the first numerical studies of 3D bar structure (≈103−104 particles represented the disc component). X-structures were only distinguished in unsharp masked images constructed from such models. Some authors (Friedli & Pfenniger 1990; Pfenniger & Friedli 1991) therefore suggested that X-structures are akin to an optical illusion due to the tendency of eyes to perceive the intensity gradients instead of actual intensity values. However, with an increase of spatial resolution, it became evident that the X-structures are real density enhancements that can be observed even without unsharp masking processing (see Smirnov & Sotnikova 2018 for many representative examples). The question then is why such density enhancements are observed. Studies of orbit composition of B/PS bulges and X-structures in different numerical and analytical models (Patsis, Skokos & Athanassoula 2002; Quillen 2002; Quillen et al. 2014; Patsis & Katsanikas 2014a; Parul, Smirnov & Sotnikova 2020) showed that an X-shape is observed in these models due to a tendency of a star to spend more time near turning points of its trajectory. More specifically, 3D bars are constituted by different types of periodic, quasi-periodic, and sticky chaotic orbits (Pfenniger 1984; Pfenniger & Friedli 1991; Patsis et al. 2002; Skokos, Patsis & Athanassoula 2002; Patsis & Katsanikas 2014a,b; Patsis & Harsoula 2018; Patsis & Athanassoula 2019). Stars that move along such orbits spend different periods of time in different parts of their trajectories. For example, stars moving along banana-shaped orbits (Pfenniger & Friedli 1991) spend more time at the highest points of their trajectory (Patsis et al. 2002; Patsis & Katsanikas 2014a). Therefore, the bulk of such orbits produces a density profile with visible density enhancements at the highest points of such orbits. For an X-structure to be observed, these density enhancements should be aligned along an almost straight line for orbits with different apocentric distances. This is indeed the case for the realistic bar potential (Patsis et al. 2002; Quillen 2002; Quillen et al. 2014; Patsis & Katsanikas 2014a). Parul et al. (2020) showed that the orbits of a more complicated morphology than banana-shaped orbits can build an X-structure in a similar manner. In general, cited works showed that X-structures and B/PS bulges are produced by the same orbits. They are not constituted by different types of orbits like, for example, disc and classical bulge components. The open question that has to be answered in the upcoming studies is what types of orbits are actually presented in real galaxies.

2020MNRAS.499.4206B__Johnston_2020_Instance_1

Lempo–Paha—Hiisi is a trans-Neptunian hierarchical triple system composed of a tight inner binary with components of similar size and an outer companion about half their size orbiting 10 times further away (Trujillo & Brown 2002; Benecchi et al. 2010). All large trans-Neptunian objects like Pluto have multiple small moons, but Lempo’s structure is unique in the Solar system. The place and timing of its origin are still a subject of debate (Nesvorný, Youdin & Richardson 2010; Correia 2018). In contrast to the Lempo system, all other known triples in the Solar system have their orbits almost regularly spaced, with one component much smaller than the others, with the most distant component being the largest (Johnston 2020). Unveiling the possible origin of the Lempo system is relevant, as the architecture of multiples holds clues to their formation story and the conditions prevailing in the primitive outer Solar system, but its origin is still unclear. Capture theories proposed so far failed to reproduce the orbital characteristics of observed binaries, especially the distribution of their orbital inclinations (Nesvorný et al. 2010; Brunini 2020). Also, triple formation requires multiple captures, a very unlikely event. Gravitational collapse of pebble clouds in a turbulent gas disc would be efficient in producing binaries and, in some particular conditions, can also produce triple systems. However, such triples do not seem to match the orbital structure of Lempo–Paha–Hiisi (Nesvorný et al. 2010). The non-detection of triple systems in the cold classical Kuiper belt, where the number of known binaries is much higher than in the resonant populations (Noll et al. 2020), argues against this formation mechanism of triple systems. The fragile dynamical stability of Lempo–Paha–Hiisi (Correia 2018) also casts doubt on the place and time of its origin, leading to speculations about a possible recent formation at the place in which it currently resides.

2019AandA...629A..92G__Octau_et_al._2016_Instance_1

The Nançay Radio Telescope (NRT) is a meridian telescope equivalent to a 94 m parabolic dish located near Orléans (France). Owing to its design, the NRT can track objects with declinations δ >  −39° for approximately one hour around culmination, and is thus well suited for the long-term timing of pulsars, for example, for the study of individual objects (see, e.g., Cognard et al. 2017; Octau et al. 2018, for recent examples) or for searching low-frequency gravitational waves from supermassive black hole binaries, using pulsar timing arrays (PTAs; see, e.g., Desvignes et al. 2016). With the goal of identifying new exotic pulsar systems or highly stable MSPs suitable for PTA studies, the SPAN512 pulsar survey (Desvignes et al. 2013; Octau et al. 2016; Desvignes et al., in prep.) was conducted between 2012 and 2018 at the NRT. As part of this survey, new pulsars were searched for at intermediate Galactic latitudes (3.5 °  |b| 5°) and away from the inner Galaxy (Galactic longitudes 74 °  l   150°). Observations were conducted at 1.4 GHz with 0.5 MHz frequency channels over a total bandwidth of 512 MHz and a fine time resolution of 64 μs, to be sensitive to faint and distant MSPs. We used PRESTO pulsar searching routines (Ransom et al. 2002) to search the data for pulsars with dispersion measures (DMs) up to 1800 pc cm−3, and a moderate acceleration search in the Fourier domain (the zmax parameter was set to 50 in PRESTO analyses) to be sensitive to pulsars in binary systems. Searches for periodic signals in the data from this survey so far led to the discovery of one “ordinary” (i.e., non-millisecond) pulsar, PSR J2048+49, and two MSPs, PSRs J2055+3829 and J2205+6012. Details on the survey, the data analysis, and the discovered pulsars will be reported in Desvignes et al. (in prep.). In the present paper we report on the results from the timing of PSR J2055+3829, an MSP in an eclipsing BW system, and from the analysis of the radio eclipses of the pulsar. In Sect. 2 we describe the radio timing observations and the results from the analysis of the timing data. In Sect. 3 we present observations of eclipses of PSR J2055+3829 at 1.4 GHz, and analyses of the data taken around superior conjunction of the pulsar. In the following section (Sect. 4), we present comparisons of the mass function distributions for eclipsing and non-eclipsing BWs, and for Galactic disk and globular cluster BWs. Finally, Sect. 5 summarizes our findings.

2018MNRAS.480.4154C__Li_et_al._2011a_Instance_1

In addition to the unconstrained optimization problems of (11) and (12), many CS-based approaches consider constrained forms of the analysis and synthesis models, which are, respectively, given by (14) \begin{eqnarray*} \min _{\boldsymbol{x}} \Vert \boldsymbol {\mathsf {\Psi }}^\dagger {\boldsymbol{x}}\Vert _1, \quad {\rm s.t.} \ \ \Vert {\boldsymbol{y}}-\boldsymbol {\mathsf {\Phi }} {\boldsymbol{x}}\Vert _2^2 \le \epsilon \end{eqnarray*} and (15) \begin{eqnarray*} \min _{\boldsymbol{a}} \Vert {\boldsymbol{a}}\Vert _1, \quad {\rm s.t.} \ \ \Vert {\boldsymbol{y}}-\boldsymbol {\mathsf {\Phi }}\boldsymbol {\mathsf {\Psi }} {\boldsymbol{a}}\Vert _2^2 \le \epsilon , \end{eqnarray*} where ε is an upper-bound related to the noise level present in . CS approaches based on constrained optimization problems, solved via convex optimization techniques, have been applied broadly in RI imaging (Wiaux et al. 2009a,b; McEwen & Wiaux 2011; Li et al. 2011a,b; Carrillo et al. 2012, 2014; Onose et al. 2016; Pratley et al. 2018). These techniques have shown promising results, with improvements in terms of image fidelity and flexibility compared to traditional approaches such as clean-based methods and MEM. For these constrained regularization approaches, parallel implementation structures have also been explored (Carrillo et al. 2014; Onose et al. 2016). Compared with the unconstrained analysis and synthesis models, constrained approaches are parametrized by ε (related to noise level) which controls the error of the reconstruction explicitly; in contrast, unconstrained models use regularization parameter μ to impose a tradeoff between the prior and data fidelity. The constrained approach therefore avoids the problem of unknown regularization parameter μ, replacing it with the problem of estimating the noise bound ε. The latter can be performed in a principled manner by noting that for Gaussian noise the ℓ2 norm data fidelity term follows a χ2 distribution with 2M degrees of freedom (see e.g. Carrillo et al. 2012). While constrained problems do not afford a straightforward Bayesian interpretation, the constrained and unconstrained models are closely related (Nikolova 2016).

2018MNRAS.476..814H__Scoccimarro_2000_Instance_1

The most general third-order statistics is the three-point correlation function (hereafter referred to as 3PCF), which is defined in configurations space. Alternatively, one can study its Fourier space counterpart, the bispectrum. These two statistics contain, in principle, the same information. However, their analyses implicate different limitations and challenges, which can affect the physical interpretation of the results. A main advantage of the bispectrum is that an analysis in Fourier space allows for a clear exclusion of high-frequency modes in the density fluctuations, which are difficult to interpret theoretically due to their highly non-linear evolution. In configuration space, these high-frequency modes contribute to the 3PCF, in principle, at all scales. In practice, one therefore needs to restrict the analysis to large scales, where their contribution is negligible, lavishing a lot of valuable data. Another advantage of the bispectrum is that its covariance is diagonal for Gaussian density fluctuations. This approximation works well, even for evolved density fields, while deviations from Gaussianity can also be taken into account (Scoccimarro 2000; Sefusatti et al. 2006; Chan & Blot 2017). The covariance of the 3PCF, on the other hand, is not diagonal, even for Gaussian fluctuations, which makes the modelling more difficult (Srednicki 1993; Slepian & Eisenstein 2015; Byun et al. 2017; Gualdi et al. 2017). An additional difference in the analysis of the bispectrum and the 3PCF lies in the fact that the computation of the latter is more expensive. However, this aspect can be tackled by employing advanced algorithms and appropriate computational resources, as done in this work (see also, Barriga & Gaztañaga 2002; McBride et al. 2011a; Jarvis 2015; Slepian & Eisenstein 2015, and references therein). Besides its disadvantages, there are some arguments that speak for the 3PCF. One of them is the fact that the amplitude of the 3PCF (but not its errors) is not affected by shot-noise, whereas the latter affects the bispectrum amplitude at all scales and hence needs to be modelled for correcting the measurements. In addition, an analysis in configuration space has the advantage that complicated survey masks can be easily taken into account in the analysis of observational data, while in Fourier space such masks impose complicated effects on the measured bispectrum, which are difficult to model (e.g. Scoccimarro 2000). A more general consideration is that it is easier to interpret effects such as redshift space distortions or baryon acoustic oscillations (BAOs) on the statistics in configuration space, since that is where the physical processes that cause these effects happen. Studies of third-order correlations in the literature usually focus on either Fourier or configuration space (e.g. McBride et al. 2011b; Marín et al. 2013; Gil-Marín et al. 2015). However, it is worthwhile studying both statistics and cross-check the results, since their different advantages and disadvantages are quite complementary.

2018MNRAS.474.2444S__Merloni_et_al._2015_Instance_1

Other examples of AGN variability are given by the so-called changing-look AGN, which present a change in the AGN type (e.g. from Type 1 to Type 1.9) due to broadening or narrowing of the Balmer lines4 (Denney et al. 2014; LaMassa et al. 2015; Ruan et al. 2015; Gezari et al. 2016; Husemann et al. 2016; McElroy et al. 2016; MacLeod et al. 2016; Runnoe et al. 2016; Stern et al., in preparation). The appearance or disappearance of broad emission lines is often accompanied by a change in luminosity of a factor ∼10 over ∼10 yr time-scales. As described above, these time-scales are much shorter compared to time-scales expected for accretion state changes (e.g. Sobolewska, Siemiginowska & Gierliński 2011; Hickox et al. 2014), and possible alternative explanations of the changing-look behaviour are variable absorption due to a clumpy torus (e.g. Elitzur 2012), transient events, e.g. tidal disruption of a star by the central black hole (e.g. Eracleous et al. 1995; Merloni et al. 2015), or major changes in the photoionization balance. The magnitude of the drop in luminosity measured in IC 2497 is at least a factor of ∼2 higher than what has been observed in a changing-look AGN. Moreover, the Chandra  and NuSTAR data do not show significant variability, and the upper limits obtained from archival WISE, NEOWISE and IRAS data seem to exclude that the total drop in luminosity happened within the last decades. For these reasons, we argue that the AGN in IC 2497 should not be classified as a changing-look AGN. On the other hand, we suggest that a changing-look AGN corresponds to a short-time (∼10–100 yr) variability which is superimposed on the long-term (∼105–6 yr) AGN phases suggested by this work and other observations (e.g. Schawinski et al. 2015), high resolution (sub-kpc) simulations (Hopkins & Quataert 2010; Bournaud et al. 2011; Novak, Ostriker & Ciotti 2011; Gabor & Bournaud 2013; DeGraf et al. 2014; Sijacki et al. 2015) and theoretical models (Siemiginowska & Elvis 1997; Sanders 1981; Di Matteo, Springel & Hernquist 2005; Hopkins et al. 2005; Springel, Di Matteo & Hernquist 2005; King & Pringle 2007; King & Nixon 2015).

2022ApJ...927...91V__Koopmann_&_Kenney_2004_Instance_1

According to simulations, blue galaxies infalling from the field reach pericenter in about 2.4 Gyr (McGee et al. 2009; see also Oman et al. 2013), and we can hypothesize that, by the time they get there, they lose most of their gas. In the first part of this time frame, they can start feeling the action of the ram pressure, and their neutral gas content, which is less bound, starts being stripped. No signs at optical wavelengths are visible yet, but the stripping has started (Tonnesen & Bryan 2010). In some galaxies, ram pressure stripping might be able to unwind the spiral arms (Bellhouse et al. 2021), while in other galaxies it just strips the gas that at some point collapses and starts forming new stars (e.g., Poggianti et al. 2019a). In this phase, tails shine at optical wavelengths, as OB massive stars are very bright. We can assume the visibility of this phase lasts on the order of ∼6 × 108 yr (Fumagalli et al. 2011; Poggianti et al. 2019a). Stripping and star formation consume the available gas and galaxies first appear as truncated disks (Koopmann & Kenney 2004; Fritz et al. 2017) and then become passive, showing k+a spectra (Vulcani et al. 2020). Galaxies typically maintain blue colors for 0.5 Gyr after becoming passive and then move to the red sequence (Poggianti et al. 2004). In these phases, tails are not visible anymore at optical wavelengths. So to summarize, an infalling galaxy maintains its blue color for at least 2.4 + 0.5 ∼3 Gyr since infall and a tail is visible only for 6 × 108yr. We can assume that the sum of RS+SC+UG samples corresponds to all the noninteracting blue late-type galaxies in the clusters and that the tailed galaxies are either only SC or SC+UG. In the first case, ∼15% of the blue cluster galaxies currently show signs of stripping, but since the visibility phase is 6 × 108/3 × 109 ∼ 0.2, the total amount of galaxies undergoing stripping is 15%/0.2 ∼ 75%. In the second case, the incidence of blue cluster galaxies currently showing signs of stripping is even higher. On one hand, this suggests that all blue cluster galaxies undergo a stripping phase during their life in clusters, and on the other hand, it indicates that most likely we are overestimating the number of ram pressure stripped galaxies only using optical imaging.

2017AandA...607L...7M__Menezes_et_al._(2013)_Instance_1

Andromeda is a galaxy that lies in the green valley (Mutch et al. 2011; Tempel et al. 2011; Jin et al. 2014). According to Belfiore et al. (2016), it is typically a low-ionisation emission-line region (LIER), as first observed by Rubin & Ford (1971) and discussed by Heckman (1996). González-Martín et al. (2015) discussed that the torus is disappearing in LIER: there is indeed little gas in the inner part of M31 (Melchior et al. 2000; Melchior & Combes 2011, 2013). It is the closest external large galaxy in which we can explore the mechanisms that quenched the star formation activity. Optical ionised gas has been observed by Menezes et al. (2013) next to the black hole in a field of view1 of 5′′ × 3.5′′, but this emission is weak. Jacoby et al. (1985) estimated the ionised gas mass in the bulge (10′ × 10′) to be of the order of 1500 M⊙. It also hosts a very massive black hole of 1.4 × 108M⊙ (Bender et al. 2005), but as studied by Li et al. (2011a), it is non-active and only murmurs at a level of 10-10LEdd. It hosts very little star formation of the order of 0.25−0.3 M⊙ yr-1, mainly located in the 10 kpc ring of the disc (e.g. Ford et al. 2013; Rahmani et al. 2016). Inside the central region (10′ × 10′), no obvious sign of star formation is detected (e.g. Kang et al. 2012; Azimlu et al. 2011; Amiri & Darling 2016), except for a central cluster of A stars formed 200 Myr ago that is located next to the black hole (within 1′′) (Lauer et al. 2012), designated by P3 by Bender et al. (2005). Viaene et al. (2014) estimated the star formation rate (SFR) on a pixel basis with panchromatic spectral energy distribution modelling. This infrared-based SFR estimated in the central pixel (36′′ × 36′′) is 4 × 10-5M⊙ yr-1, while an integration over the central region with a radius of 1 kpc corresponds to 1.25 × 10-3M⊙ yr-1. This negligible SFR is much lower than the value predicted by Rimoldi et al. (2016), considering supernovae remnants expected within the sphere of influence of quiescent supermassive black holes. For M31, an SFR of 0.13 M⊙yr-1 is expected in the sphere of influence (RSOI = 14 pc = 3.7”) of its supermassive black hole. A past AGN activity is also expected, and the associated molecular torus, if it survives, should have a radius RMT = 25 pc = 6.7′′. In parallel, Chang et al. (2007) expected next to the black hole an accumulation of molecular gas (about 104M⊙) originating from stellar feed-back. Melchior & Combes (2013) estimated a minimum molecular mass of 4.2 × 104M⊙ within 30″ from the centre, while about 106M⊙ of gas is expected from stellar feedback (e.g. Gallagher & Hunter 1981).

2021MNRAS.502.4794N__Dullo_&_Graham_2012_Instance_1

Alongside the above theoretical uncertainties in the physics of core formation in ellipticals, there have also been observational challenges. In particular, determining the size of the core has proven to be a non-trivial task. The light profiles of ellipticals are well described by the 3-parameter Sérsic profile (Sérsic 1963, 1968) over a large radial range. The most luminous ellipticals, however, show a departure from the Sérsic law in their central regions, at a radius widely known as the ‘break’ or ‘core’ radius. In these galaxies, the profiles break downward from the inward extrapolation of the outer Sérsic law. Initially the core size of a galaxy was determined by fitting the so-called ‘Nuker-profile’ (Lauer et al. 1995) to the surface brightness profile, a method that however depends sensitively on the radial fitting range and yields unreliable results when fit to surface brightness profiles with a large radial extent (e.g. Graham et al. 2003; Dullo & Graham 2012). In more recent years, it has become customary to incorporate a central flattening in the light profile by adopting a 6-parameter core-Sérsic profile (Graham et al. 2003; Trujillo et al. 2004) which provides a reliable measurement of the core size even over a large radial range (e.g. Dullo & Graham 2012, 2013, 2014). Furthermore, it has been shown that adopting a multicomponent model rather than a single core-Sérsic model over the entire radial range provides a more reliable estimate of the core size (Dullo & Graham 2014; Dullo 2019). Measured core sizes for massive ellipticals – derived in this way – are typically tens to a few hundred parsecs (e.g. Dullo & Graham 2014), while cores larger than $1{\, \mathrm{kpc}}$ are rare. A study by Lauer et al. (2007) considered a large sample of brightest cluster galaxies (BCGs) and found that fewer than 10 systems had a core size of $\sim 1\rm {kpc}$ or greater, with the largest cored system being NGC 6166 which has a core size of $\sim 1.5{\, \mathrm{kpc}}$. More recently, Dullo (2019) considered the largest sample of ‘large-core’ galaxies to date, finding that only 13(7) galaxies have core sizes larger than $0.5(1){\, \mathrm{kpc}}$.

2020ApJ...895...51M__Rogers_&_McElwaine_2017_Instance_1

The mechanism(s) driving the transport of angular momentum (e.g., Aerts et al. 2019a) and chemical elements (e.g., Salaris & Cassisi 2017) within stars are still not understood from stellar evolution theory. Discrepancies between observations and theory have been shown for stars with birth masses between 1.3 and 8 M , which comprise a convective core, enshrouded by a radiative envelope (possibly with internal convective shells from partial ionization zones or a thin outer convective envelope for M ). In these radiative envelopes, the transport of chemical elements on a macroscopic scale is ascribed to convective core overshooting (e.g., Viallet et al. 2015), rotation (e.g., Maeder 2009), or internal gravity waves (IGWs, e.g., Rogers & McElwaine 2017), whereas the transport of chemical elements on a microscopic scale is the result of atomic diffusion (Michaud et al. 2015). In stellar evolution codes, the description of macroscopic mixing introduces additional free parameters, whereas mixing from atomic diffusion can be derived from first principles. So far, the theory of element transport has been mainly evaluated by measurements of surface abundances. Asteroseismology constitutes a novel technique to empirically assess the conditions deep inside the interior (Aerts et al. 2010) of a star, as well as its evolutionary history (e.g., Bowman et al. 2019). The unprecedented high-quality data from the space-based CoRoT (Auvergne et al. 2009), Kepler (Borucki et al. 2010), and TESS (Ricker et al. 2015) missions allow for scrutiny of the current stellar evolution models of the stars’ interiors by means of gravito-inertial asteroseismology (Aerts et al. 2018). The current state-of-the-art stellar models and pulsation codes are not capable of reproducing the observed oscillation frequencies of gravity (g) modes in γ Doradus (γ Dor; see Kurtz et al. 2014; Saio et al. 2015; Schmid & Aerts 2016; Van Reeth et al. 2016) and slowly pulsating B-type (see Pápics et al. 2014; Moravveji et al. 2015; Szewczuk & Daszyńska-Daszkiewicz 2018; Aerts et al. 2019b) stars within the uncertainties of the data. Hence, additional physics is required in order to improve both the current stellar models and the prediction of the g-mode frequencies from these equilibrium models. Studies have already demonstrated the potential of g-modes to distinguish between different near-core mixing profiles (Pedersen et al. 2018) and the temperature gradient close to the convective core interface (Michielsen et al. 2019). The work of Aerts et al. (2018) has evaluated a hierarchy of input physics when modeling g-modes across a wide mass range. In the current work, we investigate to what extent the process of atomic diffusion can improve the theoretically predicted oscillation frequencies in two slowly rotating γ Dor stars.

2018MNRAS.477.4308R__Matteo,_Springel_&_Hernquist_2005_Instance_1

It is well known that the accretion on to compact objects may influence the nearby ambient around SMBHs in the centre of galaxies (e.g. Salpeter 1964; Fabian 1999; Barai 2008; Germain, Barai & Martel 2009). Together with the outflow phenomena, it is believed to play a major role in the feedback processes invoked by modern cosmological models (i.e. Λ-Cold Dark Matter) to explain the possible relationship between the SMBH and its host galaxy (e.g. Magorrian et al. 1998; Gebhardt et al. 2000) as well as in the self-regulating growth of the SMBH. The problem of accretion on to an SMBH has been studied via hydrodynamical simulations (e.g. Ciotti & Ostriker 2001; Di Matteo, Springel & Hernquist 2005; Li et al. 2007; Ostriker et al. 2010; Novak, Ostriker & Ciotti 2011). In numerical studies of galaxy formation, spatial resolution permits resolving scales from the kpc to the pc, while the sub-parsec scales of the Bondi radius are not resolved. This is why a prescribed sub-grid physics is employed to solve this lack of resolution. With sufficiently high X-ray luminosities, the falling material will have the correct opacity, developing outflows that originate at sub-parsec scales. Therefore, calculations of the processes involving accretion on to SMBH have become of primary importance (e.g. Proga, Stone & Kallman 2000; Proga 2000, 2003; Proga & Kallman 2004; Proga 2007; Ostriker et al. 2010). Numerical calculations of the accretion of matter on to SMBHs, including the radiative-outflow component, have been mostly performed using Eulerian finite-difference methods (Mościbrodzka & Proga 2013) [see also the overviews by Edgar (2004) and Foglizzo et al. (2005) and references therein for earlier work], while only a few calculations have been reported using smoothed particle hydrodynamics (SPH) techniques (Barai 2008; Barai, Proga & Nagamine 2011, 2012; Nagamine, Barai & Proga 2012), where results for the accretion rates, outflow rates, thermal instabilities, and impact of the thermal, mechanical, and X-ray feedbacks have been obtained for evolutions up to 5 Myr and scales from 0.1 to 200 pc.

2021AandA...646A..53P__Roman-Oliveira_et_al._2019_Instance_1

In addition, the Abell 901/902 field has deep and extensive photometry in the UV (Galex, Gray et al. 2009), optical (COMBO-17 survey, Wolf et al. 2003), near-infrared (Spitzer 24 μm, Bell et al. 2007), and X-ray (XMM-Newton, Gilmour et al. 2007) wavelength range. Out of the four main substructures that embody Abell 901/902, only the two most massive (A901a and A901b) show significant X-ray emission, but this may come from a very bright AGN close to the cluster center in A901a (Gilmour et al. 2007). The evolution of the cluster members’ colors, morphologies, and star-formation activity has been studied over the years, and redder stellar populations, lower star-formation rates, and indications of interactions within the cluster population of galaxies were reported (Wolf et al. 2009; Gallazzi et al. 2009). More recently, the emission-line OMEGA-OSIRIS survey provided similar results (e.g., Chies-Santos et al. 2015; Rodríguez del Pino et al. 2017; Weinzirl et al. 2017; Roman-Oliveira et al. 2019). Our group carried out a kinematic analysis of a subsample of cluster galaxies using slit spectra taken by VIMOS at the Very Large Telescope (VLT) with the HR-blue grism (R ∼ 2000) to search for indications of ram-pressure stripping (Bösch et al. 2013a) and study the slope and scatter of the TFR (Bösch et al. 2013b). Galaxies within three times the velocity dispersion (3σ) of each substructure are considered to be cluster members (Bösch et al. 2013a). We retrieved a sample of 45 cluster galaxies from Bösch et al. (2013b) characterized by their high-quality rotation curves, their disk morphology, and stellar masses above log(M*) = 9.5. This sample is used in Sect. 4 to explore the evolution of the TFR between clusters at different redshifts. The distribution of the main parameters (M* and Vmax) and their mean properties are shown in Fig. 1 and listed in Table 3. However, the sizes and exact coordinates of these galaxies within the Abell 901/902 cluster complex are not provided in the publications mentioned above, and we therefore excluded this sample from the analysis that requires them.

2020MNRAS.492..686L__Shiokawa_et_al._2015_Instance_2

After the disruption phase, the star is tidally stretched into a very long thin stream and the evolution of the stream structure in the transverse and longitudinal directions are decoupled (Kochanek 1994). Thus, the system enters the free-fall phase where each stream segment follows its own geodesic like a test particle (Coughlin et al. 2016). Then, after passing the apocentres of the highly eccentric orbits, the bound debris falls back towards the BH at a rate given by the distribution of specific energy (Evans & Kochanek 1989; Phinney 1989). Due to relativistic apsidal precession, the bound debris, after passing the pericentre, collides violently with the still in-falling stream (see Fig. 1). It has been shown that shocks at the self-intersection point is the main cause of orbital energy dissipation and the subsequent formation of an accretion disc (Rees 1988; Kochanek 1994; Hayasaki, Stone & Loeb 2013; Guillochon, Manukian & Ramirez-Ruiz 2014; Shiokawa et al. 2015; Bonnerot et al. 2016). However, the aftermath of the self-intersection is an extremely complex problem, which depends on the interplay among magnetohydrodynamics, radiation, and general relativity in 3D. No numerical simulations to date have been able to provide a deterministic model for TDEs with realistic star-to-BH mass ratio and high eccentricity (see Stone et al. 2018a, for a review). Many simulations consider either an intermediate-mass BH (e.g. Guillochon et al. 2014, Evans, Laguna & Eracleous 2015; Shiokawa et al. 2015; Sa̧dowski et al. 2016) or the disruption of a low-eccentricity (initially bound) star (e.g. Bonnerot et al. 2016; Hayasaki, Stone & Loeb 2016). It is unclear how to extrapolate the simulation results to realistic configurations and provide an answer to the following questions: How long does it take for the bound gas to form a circular accretion disc (if at all)? How much radiative energy is released from the system? What fraction of the radiation is emitted in the optical, UV, or X-ray bands?

2022MNRAS.512.5165A__Uhlemann_et_al._2016_Instance_1

The number of objects in a specific volume such as a sphere is called counts-in-cells (CIC) (Hubble 1936; Zwicky 1957; Balian & Schaeffer 1989). We know that in small scales, the distribution of CIC or equivalently one-point probability of the matter density field is not Gaussian and follows approximately a lognormal distribution (Coles & Jones 1991; Ueda & Yokoyama 1996). The nearly lognormal behaviour of the cosmic matter density field is a feature of evolving perturbations from the linear Gaussian inflationary initial conditions (Guth 1981; Linde 1982) to the late time non-linear and non-Gaussian distribution. Accordingly, it is informative to investigate the shape of the probability distribution of the matter density field and its evolution (Lam & Sheth 2008; Bernardeau, Pichon & Codis 2014; Uhlemann et al. 2016; Ivanov, Kaurov & Sibiryakov 2019; Mandal & Nadkarni-Ghosh 2020; Repp & Szapudi 2020b). It is worth mentioning that other interesting ideas such as an Edgeworth expansion, skewness, and kurtosis analysis are argued in this field of study (Colombi 1994; Gaztanaga, Fosalba & Elizalde 2000; Shin et al. 2017; Klypin et al. 2018; Einasto et al. 2021). On large scales, the CIC contains the same information as the two-point correlation function. But there is more information encoded in the lognormal shape of the CIC distribution on small scale. Accordingly, the cosmological dependence of the CIC statistics is interesting to be explored in mildly and strongly non-linear regimes from an observational and theoretical point of view. Uhlemann et al. (2020) showed that the measured CIC statistics are sensitive to the cosmological parameters and neutrino mass. Repp & Szapudi (2020a) used the CIC to break the degeneracy between σ8 and galaxy bias. Also, it is employed to study the primordial non-Gaussianity in LSS by measuring the fNL parameter (Friedrich et al. 2020). Recently, Jamieson & Loverde (2020) introduced an approach to use a position-dependent one-point distribution of matter density as a cosmological observable. Besides all this progress, there are some limitations. The results depend on the size and shape of the cell, where for large smoothing scales the distribution is Gaussian whereas, for small scales, the distribution is approximately lognormal. So for each cell size, one should calculate the CIC distribution, which is a computationally expensive procedure. Finally, we conclude that although the CIC is a computationally costly process, it is advantageous to explore different regimes and compare the linear and non-linear scales.

2016MNRAS.462.3912Q__Pinnington_et_al._1974_Instance_1

When comparing the results obtained with our computational approach with the previously published decay rates, we find an overall good agreement. This is illustrated in Figs 2–5, where our calculations are compared with the experimental data reported by Salih et al. (1985), Crespo López-Urrutia et al. (1994), Mullman et al. (1998a,b) and those obtained theoretically by Raassen et al. (1998). More precisely, as shown in Fig. 2, we obtain a mean ratio of 1.036 ± 0.205 when comparing our transition probabilities with those of Salih et al. (1985), who combined lifetime values obtained by TR-LIF with branching fractions measured on spectra recorded with the 1-m Fourier-transform spectrometer at the Kitt Peak National Observatory, to deduce the decay rates for 41 transitions depopulating the 3d74p z5F, z5D and z5G levels. Fig. 3 shows a slightly larger scatter between our calculations and the transition probabilities published by Crespo López-Urrutia et al. (1994). Here the mean ratio gAThiswork/gACrespo is equal to 1.098 ± 0.493. However, it is worth noting that the gA-values obtained by the latter authors were deduced from the combination of branching ratio measurements with available experimental lifetimes for the 3d74p z5F, z5D, z5G levels (Pinnington, Lutz & Carriveau 1973; Pinnington et al. 1974; Salih et al. 1985) but also with estimated lifetimes for the z3G, z3F and z3D levels from the measurement of total intensity of all lines of each of these levels under the assumption of almost equal population. The branching fractions were found using intensity measurements with a special hollow electrode radio frequency discharge and using a phase method with a modified wall-stabilized arc in a spectrointerferometric arrangement. Mullman et al. (1998a) reported 28 oscillator strengths for ultraviolet Co ii lines deduced from laser-induced fluorescence lifetimes and branching fraction measurements using a high-resolution grating spectrometer and an optically thin hollow cathode discharge. As illustrated in Fig. 4 , our gf-values were found to agree in general within 20–30 per cent with the results obtained by Mullman et al. (1998a). More particularly, the mean ratio gfThiswork/gfMullman was found to be equal to 1.339 ± 0.552 when using all the common lines, and to 1.238 ± 0.411 when using the strongest transitions for which log gf > −1. Finally, Fig. 5 shows the comparison between our computed oscillator strengths and those published by Raassen et al. (1998) who used the theoretical method of orthogonal operators to determine the log gf-values for (3d8+3d74s)–3d74p transitions in Co ii. In this case, the two sets of data generally agree within about 20 per cent, this percentage difference being reduced to 12 per cent when considering the most intense transitions with log gf > −1. We also note that our oscillator strengths are on average larger than those obtained by Raassen et al. This could be due to the fact that these latter authors included explicitly a less extended set of interacting configurations in their model.