adsabs/FOCAL huggingface dataset:
It is interesting that the tracers of atomic and molecular hydrogen become maximum at distances ∼0.85 kpc, where no dust cloud is inferred from the Swift/XRT data (see Fig. 5). A fiducial dust cloud at the distance of ∼0.85 kpc would produce an X-ray ring with angular size ∼9 arcmin on MJD 57205.5. As this would fall well within the Swift/XRT FOV (see Fig. 2), its absence should be related to the dust properties of the respective cloud. We estimated therefore that the maximum grain size should be ≫ 0.2 μm. A dust cloud composed by large grains ( ∼ 1 μm) would suppress the scattered intensity even at 1 keV, while it would significantly attenuate X-rays at ≤0.5 keV (e.g. Smith & Dwek 1998; Corrales & Paerels 2015). Alternatively, the absence of the X-ray ring might indicate a much smaller number of grains per hydrogen atom at ∼0.85 kpc compared to the other clouds. The analysis presented so far, as in most studies, does not take into account possible variations of the radial profiles in the azimuthal direction. We remind that the profiles shown in Figs 3 and B1 were created by summing the counts of each annulus, i.e. integrating over the azimuthal angle. Although this method is sufficient for probing the average properties of the dust clouds, such as position and average column density, it cannot provide information about the spatial inhomogeneity of the dust clouds and/or their inclination with respect to the LOS. The photon statistics of the Swift/XRT observations are sufficient for quantifying the azimuthal variations of the ring intensity (see also Fig. 2). Fig. 12 shows the azimuthal variation of the scattered photons for Swift/XRT observation 2. There are three important features that need to be mentioned: (i) the radial profile of ring 5 is highly variable along the azimuthal direction, with the peak number of counts changing by a factor of ∼5 above the background level (see sub-panels for 180°–216° and 252°–288°); (ii) azimuthal variations are also present in the rings 3 and 4, yet the variability amplitude is lower when compared to the ring 5. The peak number of counts of the fourth ring is for all azimuth angles larger compared to that of the third ring; (iii) the azimuthal behaviour of the rings 1 and 2 is the most intriguing, as the second peak (corresponding to the ring 2) becomes prominent for azimuth angles 0°–36° and 324°–360° while the first peak dominates for azimuth angles of 216°–324°. Obviously, this information is lost from the azimuthal integrated radial profiles shown in Fig. 3. Similar features appear in all Swift/XRT observations with their significance varying according to the photon statistics of the observation.
Citation: Smith & Dwek 1998
Citation function: Uses
One of the main uncertainties in elemental abundances is the quality of the adopted atomic data used in spectral synthesis calculations (Bigot & Thevenin 2008). The Belgian repository of fundamental atomic data and stellar spectra (BRASS) aims to provide astronomers with quality information for the large amount of atomic data available for high-resolution optical spectroscopy, in an attempt to help reduce systematic input errors in quantitative spectroscopy from atomic data and line selection (Lobel et al. 2017). Previously, we retrieved and cross-matched a large quantity of atomic data from several major atomic databases such as the Vienna Atomic Line Database (VALD3; Ryabchikova et al. 2015), the National Institute of Standards and Technology Atomic Spectra Database (NIST ASD; Kramida et al. 2018), and providers within the Virtual Atomic and Molecular Data Centre (VAMDC; Dubernet et al. 2016), in preparation for quality assessment work (Laverick et al. 2018; hereafter Paper 1). In this work the atomic data of seemingly “unblended” spectral lines are quality assessed against several benchmark dwarf stars, including the Sun, spanning late F-type to early K-type stars, for the spectral range 4200–6800 Å1. Unblended spectral lines for stars of ∼G2V spectral type are identified in a homogeneous manner using both the observed benchmark spectra, and the theoretical input line list of Paper I. Astrophysical oscillator strengths2 are derived for these unblended lines, using two commonly utilised methods, to gauge the reliability of the spectral line for quantitative spectroscopy and to produce “benchmark” log(g f) values for quality assessment of atomic data. The literature log(g f) values are then compared against these benchmark log(g f) values to determine which literature values reliably reproduce the stellar spectra of cool dwarf stars, and thus whether the values can be recommended for spectroscopic modelling. This paper presents three main sets of results:
Citation: Dubernet et al. 2016
Citation function: Uses; Uses; Uses
Relativistic jets are the manifestation of the extreme processes that occur within the central regions of galaxies (see Blandford et al. 2019 for a review). Active galactic nuclei (AGNs) hosting relativistic jets closely aligned to the line of sight are called blazars. Due to their peculiar orientation, the relativistic amplification of the nonthermal jetted radiation (Doppler boosting; see, e.g., Rybicki & Lightman 1979) leads to the observation of a number of interesting phenomena. A few examples are detection at all accessible frequencies (e.g., Abdo et al. 2011), observation of temporal and spectral variability (Gaidos et al. 1996; Acciari et al. 2011; Fuhrmann et al. 2014; Paliya et al. 2017b), and superluminal motion and high brightness temperature (Scheuer & Readhead 1979; Lister et al. 2019). The optical and radio emissions detected from blazars are found to be significantly polarized (e.g., Fan et al. 2008; Itoh et al. 2016). The flux enhancement also makes blazars a dominating class of γ-ray emitters in the extragalactic high-energy sky (Ajello et al. 2020) and one of the very few astrophysical source classes detected at cosmic distances (e.g., Romani et al. 2004; Sbarrato et al. 2013). Blazars are classified as flat-spectrum radio quasars (FSRQs) and BL Lac objects based on their optical spectroscopic properties. FSRQs are characterized by broad emission lines (rest-frame equivalent width >5 Å), whereas BL Lac sources exhibit weak or no emission lines in their optical spectra, thereby making it challenging to detect their redshift (Stickel et al. 1991). BL Lac objects are known to exhibit a negative or mildly positive evolution compared to the strong positive evolution noticed in FSRQs (Ajello et al. 2012, 2014). Altogether, FSRQs dominate the known population of high-redshift (z ≳ 3) blazars and are found to be much more luminous than the BL Lac population (e.g., Ajello et al. 2009; Ackermann et al. 2017; Paliya et al. 2019d).
Citation: Lister et al. 2019
Citation function: Background; Background
One might hope that these global observations would strongly constrain the SFHs of individual galaxies, but this connection is not easily established. For example, average SFHs can be inferred by integrating the main sequence SFR over time (e.g., Leitner 2012), but this approach leads to inconsistencies (Leja et al. 2015). Instead, the most successful theoretical models link the growth of stellar mass to the growth of the dark matter halos that galaxies inhabit, for example, via subhalo abundance matching (e.g., Kravtsov et al. 2004; Conroy et al. 2006; Behroozi et al. 2013b; Moster et al. 2013), halo occupation distributions (e.g., Peacock & Smith 2000; Seljak 2000; Hearin et al. 2016), semi-analytic models (Kauffmann et al. 1993; Somerville et al. 2001; Guo et al. 2011), or other assumptions (Bouché et al. 2010; Davé et al. 2012; Lilly et al. 2013; Tacchella et al. 2013; Mitra et al. 2017). One important conclusion from these models is that there has to be significant scatter between halo and galaxy masses (and thus growth histories) in order to explain observations (More et al. 2009; Behroozi et al. 2013b; Reddick et al. 2013; Gu et al. 2016). As a result, even models that agree on global constraints can lead to orthogonal interpretations of the evolution of individual galaxies. A good example for such disagreement is the “rapid quenching”7

7
The term “quenching” is somewhat ambiguous. In this paper, we use it to mean the cessation of star formation, without any presumption as to whether the decrease happens quickly or slowly, and whether it happens due to a diminishing gas supply or other physical processes.
 framework where galaxies follow the main sequence until they sharply fall below the main sequence (Peng et al. 2012; Wetzel et al. 2013; Tacchella et al. 2016b; Tinker et al. 2016) and the “stochastic” framework where correlated scatter and the central limit theorem lead to the main sequence (Kelson 2014; Kelson et al. 2016).
Citation: Conroy et al. 2006
Citation function: Background
To explore magma effects on sub-Neptune atmospheres, we assume the atmosphere equilibrates with a well-stirred magma ocean. Our model makes the following simplifications: (a) we consider only the elements Fe, Mg, Si, O, and H. Chemically reduced carbon compounds may also contain H; for simplicity, we omit consideration of them here. We also restrict ourselves to the range of magma elemental compositions for which SiO2 is a major constituent. (b) We set 2000 K ≤ Tmai ≤ 3000 K, so that the magma–atmosphere interface is molten but the vapor pressure of the magma is small relative to the total atmospheric pressure (Fegley et al. 2016; Sossi & Fegley 2018). This Tmai is at the low end of the Tmai output by thermal evolution models for multi-Gyr-old sub-Neptunes (e.g., Bodenheimer & Lissauer 2014; Howe & Burrows 2015; Vazan et al. 2018a). We consider lower Tmai in Section 4.4. (c) We ignore Fe3+ (i.e., Fe2O3). We expect Fe3+ will be a minor constituent of a magma ocean equilibrated with a H2-dominated atmosphere. Equal thermodynamic activities of FeO and Fe2O3 in magma at 3000 K require fO2 = 28 bar, much higher than expected from thermal dissociation of steam at any P and T below 1 kilobar and 3500 K. (d) We assume that metal (if present) is pure Fe for these calculations; in reality, the metal will be an Fe-dominated alloy. We may be (slightly) underestimating fO2 by doing this. (e) We track nonideal behavior of both H2 and H2O (Appendix C), but we assume ideal mixing of H2 and H2O. This is a valid assumption both under mineral-free conditions in the atmosphere for T > 650 K, and also at the magma–atmosphere interface given our model assumptions (Seward & Franck 2019; Bali et al. 2013; Soubiran & Militzer 2015). We ignore joint-solubility effects. (f) We use a single value of gravitational acceleration g, corresponding to 1.2× the bare-rock radius, to convert from bottom-of-atmosphere pressure to atmosphere column mass. (g) We ignore the effect of dissolved volatiles on core mass.
Citation: Howe & Burrows 2015
Citation function: Compare/Contrast
In Figure 2, we show the Chandra 0.3–8 keV images with SDSS contours overlaid for the six mergers in our sample. In Table 4 we list the number of counts detected in the 0.3–8 keV and 2–8 keV bands, and list the detection threshold, PB, associated with each position. There are a number of PB thresholds employed in the literature to define source detection significance. Based on weak sources in Chandra deep field images, the threshold for PB adopted based on a balance between reliability and completeness varies from 0.002 to 0.007 (Xue et al. 2011, 2016; Luo et al. 2017). Based on even the lowest of all these thresholds, all sources are detected. Note that the detection thresholds adopted in the literature for sources at known locations are often PB  0.01, which corresponds to 





 (e.g., Lansbury et al. 2014). We note that due to insufficient counts, coupled with the fact the exact location of the galaxy nuclei is uncertain in the advanced mergers in our sample (see SDSS images in Figure 1), it is impossible to quantify any possible spatial offsets between the positions of the detected Chandra sources and the actual galactic nuclei. It is therefore not possible to determine using these observations alone if some of the mergers host offset AGNs, another unambiguous signature of a galaxy merger that can probe AGN triggering through galaxy interactions (Barrows et al. 2016, 2017). We note that for sources within the 2′ of the boresight, the absolute accuracy of source locations on the ACIS-S chip has a 90% uncertainty radius of 





,18

18

http://cxc.cfa.harvard.edu/proposer/POG/pdf/MPOG.pdf

 indicating that the positions of all detected targets are consistent with the locations of the SDSS knots, suggesting that the detected sources likely correspond to the nuclei of the mergers. J1036+0221, J1045+3519 Gal 1, J1221+1137 Gal 1, and J1306+0735 Gal 2 were detected in the hard band using the same detection threshold PB  0.002 using the 2–8 keV source counts. Note that there are insufficient counts to perform a spectral analysis or to obtain reliable HRs for our targets. We therefore list in Table 6 the observed X-ray luminosity, assuming a simple power-law model with 





, corrected for Galactic absorption.
Citation: Luo et al. 2017
Citation function: Uses
In order to see whether the CN- and HK′-strong stars in our study are also enhanced in Fe and s-process elements, we have compared our results with high-resolution spectroscopy by M15. In Figure 4, our δCN and δHK′ indices are plotted with [Na/Fe] and [Ca/Fe] abundances, respectively, for 33 common stars. In general, the strength of the CN band is correlated with the N and Na abundances, while the CH band is affected by C abundance (Sneden et al. 1992; Smith et al. 1996; Marino et al. 2008). The upper panel of Figure 4 also shows a strong correlation between [Na/Fe] and the δCN index, which is in good agreement with previous studies (Sneden et al. 1992; Lim et al. 2016).4

4
Careful inspection of the upper panel of Figure 4 also shows the possibility that the s-poor and s-rich groups are probably separated on this diagram, with the s-rich stars more enhanced in both [Na/Fe] and δCN. This would imply that the variations in light elements would be present in each group with different s-process elements abundances, which has already been found in other GCs with s-process element and Fe variations, such as M2 and M22 (Marino et al. 2011; Yong et al. 2014). More samples of stars, however, are needed to confirm this trend in NGC 5286.
 The CN-weak (blue) and CN-strong (red) subpopulations are almost identical to the s-poor (triangles) and s-rich (squares) groups, respectively. In addition, the δHK′ index is understandably correlated with the [Ca/Fe] abundance with a few exceptions (see the lower panel of Figure 4). According to this comparison, the difference in δHK′ index between CN-weak and CN-strong stars (∼0.094) is equivalent to 0.09 dex in Δ[Ca/Fe] and 0.15 dex in Δ[Fe/H]. These comparisons confirm that our results from low-resolution spectroscopy are consistent with those from high-resolution spectroscopy by M15. Consequently, the later-generation stars in NGC 5286 show the enhancements not only in light elements (CN) but also in heavy elements (Fe and Ca) and s-process elements, although the presence of Fe spread requires further investigations (see Mucciarelli et al. 2015; Lee 2016).
Citation: Lim et al. 2016
Citation function: Similarities
The Vela Molecular Ridge Cloud-D (hereafter VMR-D) (260Â° â² â â² 264Â°; |b| â² 1Â°) is part of a giant molecular complex located along the Galactic plane (260Â° â² â â² 272Â°; |b| â² 3Â°; Murphy & May 1991) and is then well suited to represent a typical star-forming region (SFR) of our Galaxy. For this reason a subregion of this cloud has been the subject of many previous papers, dealing with different observational aspects of the star formation (SF), such as the presence of outflows (Wouterloot & Brand 1999; Elia etÂ al. 2007), jets (Lorenzetti etÂ al. 2002; Giannini etÂ al. 2005, 2013), and clustering (Massi etÂ al. 2000). The continuum submillimeter emission in the VMR-D cloud was surveyed by Massi etÂ al. (2007), who catalogued 29 resolved dust cores and also obtained a further list of 26 unresolved candidate cores. More recently, thanks to the opportunity offered by the Spitzer Space Telescope, the VMR-D region was observed with the IRAC (Î» = 3.6, 4.5, 5.8, 8.0âÎ¼m) and MIPS (Î» = 24, 70âÎ¼m) focal-plane instruments, obtaining in this way six mosaics, covering about 1.2Â deg2, which have been analyzed to produce a merged photometric Spitzer-IRAC point-source catalog (hereinafter Spitzer-PSC) complemented with MIPS photometry (Strafella etÂ al. 2010, hereinafter PaperÂ I). Further observational progress was made when the BLAST experiment (Pascale etÂ al. 2008) mapped the whole Vela Molecular Ridge in the far-IR (FIR) spectral region (Î» = 250, 350, 500âÎ¼m), complementing in this way the Spitzer spectral coverage toward long wavelengths. These observations were discussed by Olmi etÂ al. (2009), who obtained a catalog of dense cores/clumps in the VMR-D cloud. The last important observational progress was made with the Herschel Space Observatory, which, surveying the Galactic plane in the framework of the Hi-GAL key project, partially mapped the VMR-D region in the FIR spectral range (Î» = 70, 160, 250, 350, 500âÎ¼m) with a spatial resolution and sensitivity almost twice that of BLAST. Here we also analyze these observations for the first time, thanks to the support of the Hi-GAL collaboration that provided us with the corresponding calibrated maps. These have been used to extract five single-band photometries that constitute another important spectral extension of our information about this region.
Citation: Massi etÂ al. 2000
Citation function: Background; Background
Nitrogen chemistry mainly consists of three competing processes: (i) the conversion of atomic N to N2 in the gas phase, (ii) destruction of N2, for instance, via photodissociation and reaction with He+, and (iii) freeze-out of atomic N and N2 onto dust grains followed by surface reactions (e.g., Daranlot et al. 2012; Li et al. 2013). The conversion of atomic N into N2 has been proposed to occur by slow neutral-neutral reactions, such as NO + N and CN + N (Herbst & Klemperer 1973; Daranlot et al. 2012). According to the pseudo-time-dependent gas-phase astrochemical model under dense cloud conditions (104 cm−3, 10 K, 10 mag) by Le Gal et al. (2014), the conversion of atomic N into N2 takes an order of Myr, depending on assumed elemental abundances. In the gas-ice model of Daranlot et al. (2012), under the similar physical conditions, the conversion of atomic N to N2 takes ~5 × 105 yr, and it occurs after the significant fraction of nitrogen is frozen out. On the other hand, N2 mainly forms via the reactions NH2 + N and NH + N around the transition from atomic to molecular nitrogen in the models of Furuya & Aikawa (2018) and Furuya & Persson (2018), in which the dynamical evolution of molecular clouds is considered. NH2 and NH are mainly formed via photodesorption of NH3 ice, followed by photodissociation in the gas phase. In this case, the formation rate of N2 from atomic N is, roughly speaking, similar to the freeze-out rate of atomic N. Considering that interstellar ices, at least water ice, are already abundant in molecular clouds with relatively low line-of-sight visual extinction (e.g., ~3 mag for the Taurus dark clouds, Whittet 1993), it may not be surprising that the transition from atomic to molecular nitrogen occurs in the parent cloud of L1544 or in the outer regions of L1544. It should be noted that the N2-dominant region could be larger than the regions traced by N2H+ and NH3 emission, since their abundances are controlled not only by N2, but also by CO; the catastrophic CO freeze-out, which occurs in the late stage of the interstellar ice formation at high densities (≳105 cm−3; e.g., Pontoppidan 2006), causes their abundances to be enhanced (e.g., Aikawa et al. 2005).
Citation: Le Gal et al. (2014)
Citation function: Compare/Contrast; Compare/Contrast
To mitigate this problem, several studies have suggested to use the width of the [O iii]λ5007 Å emission line (hereafter [O iii]) originating in the narrow-line region (NLR) as a surrogate for σ⋆, assuming that the NLR is gravitationally bound to the bulge and thus, that the gas kinematics follows the bulge potential (e.g. Terlevich, Diaz & Terlevich 1990; Whittle 1992; Nelson & Whittle 1996; Nelson 2000; Boroson 2003; Shields et al. 2003; Greene & Ho 2005; Netzer & Trakhtenbrot 2007; Salviander et al. 2007; Salviander & Shields 2013). However, while the [O iii] emission line is a prominent line that can be easily measured in AGNs out to large distances, it is also known to often have asymmetric line profiles due to non-gravitational gas kinematics such as outflows, infalls, or interaction with radio jets. In particular, it is known to often display a blue wing (e.g. Heckman et al. 1981; De Robertis & Osterbrock 1984; Whittle 1985; Wilson & Heckman 1985; Mullaney et al. 2013; Woo et al. 2016), generally interpreted as a signature of outflows with dust preferentially hiding one cone behind the stellar disc. For that reason, some studies have excluded the [O iii] blue wing, as well as any radio sources and galaxies undergoing tidal interactions. The MBH was found to scale with the width of the [O iii] line (σ[O iii]), albeit with a large scatter (e.g. Nelson & Whittle 1996; Greene & Ho 2005). Other studies have suggested the use of different emission lines, such as [S ii]λλ6716, 6731 (e.g. Komossa & Xu 2007; Ho 2009) that have a lower ionization potential and do not suffer from substantial asymmetries, or mid-infrared lines (e.g. Dasyra et al. 2008, 2011), but the scatter is comparable to that of the core of the [O iii] line. While all studies confirm the original findings by Nelson & Whittle (1996), i.e. a moderately strong correlation between σ⋆ and σ[O iii] but with real scatter, the origin of the scatter remains unclear. No dependencies have been found with AGN luminosity, host-galaxy morphology, star formation rate, or local environment (Greene & Ho 2005; Rice et al. 2006).
Citation: Mullaney et al. 2013
Citation function: Motivation; Motivation
The number counts of the most massive clusters have the potential to constrain cosmological parameters. Unfortunately, these systems also tend to be most affected by the effects described above. Massive systems will produce the greatest gravitational lensing shear, and in our hierarchical universe, they are also commonly disrupted by recent merging activity. In this work, we aim to better understand how these considerations affect the observed SZE signals using high-resolution submillimeter and radio imaging of a representative sample of SZE-selected clusters.We present new observations at 345 GHz (19 2 resolution) with the Large APEX Bolometer Camera (LABOCA; Siringo et al. 2009) on the Atacama Pathfinder EXperiment (APEX; Güsten et al. 2006) telescope25

25
This publication is based on data acquired with the Atacama Pathfinder Experiment (APEX). APEX is a collaboration between the Max-Planck-Institut für Radioastronomie, the European Southern Observatory, and the Onsala Space Observatory.
 and at 2.1 GHz (5″ resolution) with the Australia Telescope Compact Array (ATCA) of a sample of massive SZE-selected galaxy clusters. We call the project “LASCAR,” the LABOCA/ACT Survey of Clusters at All Redshifts, in honor of the Lascar volcano near the ACT site in northern Chile. We use these data to measure the properties of the clusters’ spatially resolved SZE increment signals, and quantify the degree of background and foreground radio and infrared galaxy contamination. Section 2 describes our cluster sample. Section 3 presents observations and data reduction techniques. Section 4 assesses the SZE contamination by point sources. Section 5 uses the point-source subtracted multi-wavelength SZE maps to place constraints on cluster peculiar velocities. In Section 6 we discuss our results in the context of previous work, and in Section 7, we conclude. In our calculations, we assume a flat ΛCDM cosmology with 





, 





, and 





 (Komatsu et al. 2011).
Citation: Güsten et al. 2006
Citation function: Uses; Uses; Uses