adsabs/WIESP2022-NER huggingface dataset:
Paper: 2018ApJS..234....5Y (fulltext)
be the H ii regions misidentified as galaxies. Thus, follow-up may be needed to confirm this parallel sequence. Figure 13. Zoom-in regions of the M r / and M * / diagrams. The dashed–dotted lines indicate the separation between the fainter paralleled sequence and the main population of galaxies. 127 common galaxies from both panels are color coded by redshift, while the distinct ones are shown by the gray color. Four outliers on the left side of each panel are actually three galaxies, for which two outliers with are two H ii regions in the same galaxy. Alternatively, the distribution of the individual field for each panel in Figure 12 also has been shown in Figure 14 . Figure 14. Same as Figure 12 but for individual fields. Each galaxy has been color coded by redshift. The histograms of each unique color index are shown on the right side of the panel. 6. Summary We present here a spectroscopic redshift catalog from the LAMOST Key Project, LaCoSSPAr, which is designed to observe all sources (Galactic and extragalactic) by using repeating observations with a limiting magnitude of in two FOVs in the SGC. The project is mainly focusing on the completeness of LEGAS in the SGC, the deficiencies of source selection methods and the basic performance parameters of the LAMOST telescope. Two chosen FOVs represent the relatively lower (Field A) and higher (Field B) density of galaxies. Targets in the FOV are mainly consisted of stars, galaxies, quasars, and u -band variables, as well as complementary H ii regions. We conduct the observation from 2012 September to 2014 January. Field A contains 2519 galaxies and 13,930 stars in which 2447 () and 13,278 () of them have been observed (97%) with 5 B () and 12 F plates (), respectively. Field B contains 3104 galaxies and 11,381 stars in which 2995 () and 10,224 () of them have been observed with 6 B and 5 F plates, respectively. The raw data have been reduced with LAMOST 2D and 1D pipelines. An additional post-processing has been applied to the LAMOST 1D spectrum to remove the majority of remaining sky background residuals. More than 10,000 spectra have been visually inspected to measure redshift by using combinations of different emission/absorption features with a uncertainty of . All galaxies have been divided into two categories as emission and absorption line galaxies, depending on whether there are obvious emission lines appeared or not. In total, 1528 redshifts ( of observed galaxies; including 623 absorption and 905 emission line galaxies) have been measured in Field A with a median value of z = 0.125 and a range from 0.001 to 1.598 (99% at ). For Field B, 1570 redshifts ( of observed galaxies; including 569 absorption and 1001 emission line galaxies) have been measured with a median value of z = 0.0952 and a range from 0.006 to 3.148 (99% at ). The results show that it is possible to derive redshift from low S/N galaxies with our post-processing and visual inspection, since the S/N r is less than
Paper: 2021ApJ...912....8B (fulltext)
of the total CGM column density within ±600 km s −1 of the galaxy systemic velocity was found at ∣ v ∣ 100 km s −1 (Tumlinson et al. 2013 ; Werk et al. 2014 ). Kinematic analysis of warm gas signatures in the quasar absorption-line survey COS-GAL also shows that a substantial portion of the CGM is likely hidden at ∣ v ∣ 100 km s −1 (Zheng et al. 2019 ). In the recent CGM 2 survey, the majority of the H i column density detected in absorption around z 0.48 galaxies lies within ±250 km s −1 of the galaxy systemic velocity, despite a velocity window of 1000 km s −1 (Wilde et al. 2020 ). Additionally, Martin et al. ( 2019 ) find that the velocity of low-ionization gas around nearby galaxies is tied to the rotation of the disk out to radii of ∼70 kpc. If the Milky Way is similar to other star-forming galaxies at low redshift, these observations further reinforce the evidence suggesting that a significant fraction of Galactic baryons are yet to be detected in the low-velocity Galactic CGM. Simulations of Milky Way analogs also broadly agree that a significant fraction of circumgalactic baryons are moving at low velocities. The FOGGIE simulations, which focus on resolving the CGM around galaxies with extreme spatial and mass resolution, show with mock observations that the strongest absorption is confined to within 200 km s −1 of the systemic velocity (Peeples et al. 2019 ; Zheng et al. 2020 ). Other synthetic observations of a Milky Way−mass galaxy generated from the high-resolution cosmological simulation Enzo also predict that ∼ 65% of the Milky Way's CGM mass at Galactic latitudes ∣ b ∣ > 20° is hidden at low to intermediate velocities (∣ v ∣ 100 km s −1 ) for all gas phases and that the warm−hot component (10 5 K T 10 6 K) is primarily moving at ∣ v ∣ 150 km s −1 (Zheng et al. 2015 ; Joung et al. 2012 ). The C iv doublet is a useful probe of warm ionized gas in galaxy halos because of its strong oscillator strength (Savage Wakker 2009 ) and high covering fraction in the CGM of external galaxies (Keeney et al. 2013 ; Liang Chen 2014 ). In low-redshift galaxies that span a wide range of stellar mass (9.5 log ( M * / M ⊙ ) 11), estimates of log N C IV (cm −2 ) range from 13.5 to 14.5, with a covering fraction of ∼50% out to half the virial radius for log N C IV > 13.5 cm −2 (Bordoloi et al. 2014 ; Burchett et al. 2016 ). Using conservative ionization fraction arguments that take the maximum fraction of carbon that presents as C iv , ∼30%, for both photoionized and collisionally ionized gas, such measurements imply that > 10 6 M ⊙ of carbon sits in the CGM of external galaxies. For sub- L * galaxies with stellar masses 10 8.5 ≲ M * ( M ⊙ ) ≲ 10 10 , this estimated CGM carbon mass amounts to 50%–80% of the total ISM carbon mass (Bordoloi et al. 2014 ). Measurements of the Milky Way's CGM are needed at all velocities in order to directly probe the baryonic mass of the Milky Way, test the expectations from cosmological simulations, and compare the
Paper: 2019A&A...631L...1M (fulltext)
with multiple components, ν is given for the component with the highest frequency. (3) Spectrometer used to record the data. FTS and VESPA were used at resolutions of 200 kHz and 20 kHz, respectively. (4) Velocity resolution. All spectra were resampled with channels of 0.6 km s −1 (FTS) or 0.06 km s −1 (VESPA). (5) Maximum main-beam temperature of the transition in the map. (6) Approximate rms range computed from a 10 km s −1 range, at least 20 km s −1 off the line, where no astronomical signal is found. We observed 14 tiles of typically 200′′ × 180′′, and built a mosaic that covers some 130 arcmin 2 around the position . Each tile was observed multiple times and in orthogonal directions in on-the-fly (OTF) mode and position-switching mode, with a scan velocity of at most 9′′ s −1 , a dump time of 1 s, and a maximum row spacing of 12′′. The beam full width at half-maximum (FWHM) ranges from 21′′ (0.08 pc) at 115 GHz to 26′′ (0.1 pc) at 93 GHz. The off position was observed every 1 to 1.5 minutes. It was chosen at after searching the SPIRE 250 μ m map for a minimum in surface brightness. Pointing corrections and focus corrections were performed every 1.5 h and 3 h, respectively, leading to a pointing accuracy measured to be ≲5′′. We converted the antenna temperature into the main beam temperature assuming a standard telescope main-beam efficiency 3 of 0.78 for CO observations and 0.80 for N 2 H + . We also used archival data from the WISE satellite ( Wright et al. 2010 ) at 3.4, 4.6, 12, and 22 μ m with a spatial resolution ranging from 6.1′′ (0.02 pc) at the shortest wavelength to 12′′ (0.04 pc) at 22 μ m. We used these data to complement the spectral energy distributions (SEDs) of cores in the MIR range. The data were converted into surface brightness units with the conversion factors given in the explanatory supplement ( Cutri et al. 2011 ). The calibration uncertainty is approximately 6% for the 22 μ m band and less for the shorter wavelengths. 3. Method 3.1. Analysis of the molecular line data For the following analysis, we used multi-component Gaussian fits to characterise the emission lines. For compact sources, spectra in all CO isotopologues were first averaged within the ellipse of the source as defined in the GCC catalogue by Montillaud et al. (2015) . A combined single-component Gaussian fit of the 12 CO, 13 CO, and C 18 O lines with the same centroid for the three lines was attempted. If the residuals showed features with a signal-to-noise ratio (S/N) greater than five, a new fit with one more component was made, again using the same centroid for all three lines. The residuals were examined again, and new fits with additional components were attempted until the residuals were below 5 σ . We found three components at most. Examples for a few sources are shown in Appendix A.1 . The constraint that each Gaussian component must have the same centroid in all CO isotopologues was motivated by the following virial analysis, which combines
Paper: 2021A&A...650A.161P (fulltext)
objects typically have red optical colours ( Gulbis et al. 2006 ) with ≈30% of the population found in binaries ( Grundy et al. 2011 ). The cold component comprises ≈50% of the CKB total population ( Petit et al. 2011 ) and is believed to have formed in situ because of the presence of extremely wide binaries that otherwise would have been destroyed by close encounters with Neptune ( Parker Kavelaars 2010 ). (2) The hot classicals (HCs), with a wider range of inclinations and eccentricities compared to CCs. These represent the other 50% of the total CKB population ( Petit et al. 2011 ) 1 . Contrary to the CCs, HCs were probably implanted in their current location, evidenced by the fact that the two populations are very different from each other. Indeed, in addition to having more excited orbits, the HCs show a wider range of photometric colours and a lower binary fraction than CCs ( Noll et al. 2008 ). Resonant KBOs These are objects in mean motion resonance with Neptune, such as Plutinos (3:2), Twotinos (2:1), and 5:3, 7:4, and 5:2 populations, and so on. These resonant KBOs are estimated to make up about 25% of the total Kuiper belt population ( Gladman et al. 2012 ). Gulbis et al. (2006) found that objects in the 3:2 resonance span the full range of KBO colours. The objects in the 4:3, 5:3, 7:4, and 2:1 resonances are predominantly red and the 5:2 resonant objects are grey or neutral in colour. Moreover, the 2:1 resonance inclination distribution is much colder than the 5:2 or 3:2 resonances ( Volk et al. 2016 ). Fig. 1 Eccentricities ( upper figure ) and inclinations ( bottom figure ) of TNOs. The data are from the IAU Minor Planet Center database 2 . The dashed line and the dash-dotted line represent respectively q = 30 and q = 40 au perihelion distances. Vertical solid coloured lines indicate the main mean-motion resonances with Neptune. Scattered disc objects (SDOs) These are the objects found in the scattered disc, which extends from 30 au to roughly 1000 au and interacts with Neptune by close encounters. The SDOs have perihelion distances in between 30 au and roughly 40 au and are mainly grey (or neutral) in colour ( Sheppard 2010 ). Detached objects These have slightly larger perihelion distances than the SDOs and are no longer affected by close encounters with Neptune. The first hypothesis for the very peculiar structure of the Kuiper belt was proposed by Malhotra (1993 , 1995 ) who predicted the existence of objects in external mean-motion resonances with Neptune. In the model, these objects are trapped via adiabatic resonance sweeping during a phase of outward planetesimal-driven migration of the ice giant ( Fernandez Ip 1984 ). Indeed, resonance capture can occur when the orbital frequency of a planetesimal and/or a planet changes gradually and the resonance ‘sweeps’ across the orbit of the planetesimal. Resonance sweeping may result in the capture of the planetesimal in the resonance (if the migration direction is convergent
Paper: 2020ApJ...905...21A (fulltext)
We include only neighboring galaxies with stellar masses greater than M * = 10 9 M ⊙ h −1 . We define the observable Δ r as the ratio of density within 0.6 Mpc h −1 , as compared to the density within 5 Mpc h −1 . The smaller scale is chosen to represent a galaxy’s local environment, sensitive to whether or not it exists as a part of a group or a cluster of galaxies, while the larger radius is representative of its large-scale environment or neighborhood beyond its own parent halo. In the following sections, we study the properties of the host galaxies in relation to BNS mergers, as a function of the time-delay model. We then estimate the number of events required in order to make inferences about the evolutionary history of merging binaries. 3. Results 3.1. Weighted Distributions The underlying population of BNS systems is drawn from the distribution of stars in the universe. Among the first questions to be posed is whether BNS host galaxies are biased tracers of the underlying population of galaxies in the universe. For example, we may ask whether BNS mergers trace stellar mass, in which case they would occur preferentially in high M * galaxies (Artale et al. 2020 ; Ducoin et al. 2020 ; Toffano et al. 2019 ). Alternatively, BNS mergers may trace star formation rate (Phinney 1991 ) or halo mass, or they may be randomly distributed in galaxies with equal probability. We ask how large a sample of host galaxies would be required in order to distinguish these simple models, where mergers trace either the stellar mass of a galaxy, the star formation rate, or the virial mass of the parent halo in which they reside. The arguments in this section are not specific to BNS systems, and can be extrapolated to black hole binaries, or black hole–neutron star mergers, assuming that their host galaxies can be identified. Physically, we can associate a model in which BNS mergers trace the star formation rate with a zero delay time model, where binaries merge as soon as they are born. In this scenario, the merger rate would simply trace the rate at which new stars are forming in a galaxy. At the other extreme, for very long time delays on the order of 10 Gyr, we expect low-redshift BNS mergers to trace the stellar mass, as high stellar mass galaxies reached the peak of their star formation at early redshifts. Alternatively, it has been proposed that, rather than forming from isolated stellar binaries in the galactic field (Tauris et al. 2017 ; Vigna-Gómez et al. 2018 ), a significant fraction of BNSs may form via dynamical interactions in dense globular clusters (Grindlay et al. 2006 ; Andrews Mandel 2019 ). Recent studies indicate that globular cluster abundance is a good tracer of a galaxy’s host halo mass (Hudson et al. 2014 ; Harris et al. 2013 ). In this way, a BNS merger rate that traces dark matter halo mass, rather than galaxy stellar mass, could be an indication that BNS systems are preferentially formed in globular clusters. We also note that some
Paper: 2016MNRAS.456.2537R (fulltext)
mass. The upper and lower limits of the SNR luminosities in Fig. 6 are found in Section 5.2 and are the same as those plotted on Fig. 4 . The solid lines of Fig. 6 show the range of luminosities that can be detected by Chandra -ACIS-S with 20 ks exposures (based on flux limits of 3 × 10 −15 and 9 × 10 −15 erg cm −2 s −1 for a 10 ks exposure). The lower horizontal axes are given in terms of the maximum resolvable distance of the SOI. This is the distance at which the (diameter of the) SOI of the SMBH is just within the core of the point-spread function of Chandra . For example, the SOI of a 10 8 M ⊙ SMBH is resolvable at any distance below ∼10 Mpc and, at 10 Mpc, the lower limit of detectable soft X-ray emission is given by the red line. At any distance less than 10 Mpc, this detection threshold drops and so fainter emission from SNRs would be detectable. Figure 6. Observable limits of the combined X-ray luminosities from young SNRs as a function of SMBH mass (upper axes) or maximum resolved distance (lower axes). The maximum resolved distance is that at which the SOI of the SMBH is within the core of the PSF of Chandra . The left-hand panel shows luminosities in the soft X-ray (0.5–2 keV), while the right-hand panel shows hard luminosities (2–8 keV). SNR luminosity limits are the dashed black lines (shown also in Fig. 5 ). Flux-limited detection thresholds from Chandra exposure times of 20 ks for galaxies at the distance limit are given as solid lines. The shaded region in the left-hand panel highlights the observable range of luminosities in the soft band. From Fig. 6 , it is evident that, even at the maximum resolved distance, the upper limit of SNR emission is detectable as it is above the 20 ks threshold in the soft band through most of the M • range (although the low end of possible X-ray luminosities is possibly not within the detection threshold of Chandra ). In the hard band, the Chandra 20 ks threshold follows very closely the high limit of predicted SNR emission. This suggests that, for galaxies at the maximum resolved distance, the emission would not be detectable in the hard band. Again, however, if a galaxy is closer than this maximum distance, the threshold marked by the blue solid line will drop; therefore, hard X-ray luminosities are still potentially detectable for more nearby galaxies. To compare this with the number of SMBHs known at these distances, in Fig. 7 , we plot the distances and masses of well-established SMBHs constructed from Tables 2 and 3 in the review of Kormendy Ho ( 2013 ) and the references therein. We show in the grey region the cases where the SOI of the SMBH is not resolved by Chandra . As for the upper axes in Fig. 6 , the limit between the grey and white area is determined by the distance at which the SOI of the SMBH equals in size the core of the point-spread function of Chandra . Figure 7. Distances and masses (with errors) of known SMBHs over the same mass range considered in this paper. Data were
Paper: 2017MNRAS.470..401R (fulltext)
star has an initial mass within a given mass range is given by the Kroupa ( 2002 ) IMF, with a slope x = 1.7 for high masses, normalized to unity in the 0.1–100 M ⊙ range. For the starbursts, we also investigate the effects of an IMF skewed towards high masses ( x = 0.95 in the high-mass regime), similar to the one proposed by Ballero et al. ( 2007 ) for the Galactic bulge. All our computations avoid the instantaneous recycling approximation by detailed accounting of the finite stellar lifetimes. This is a necessary prerequisite for a proper treatment of elements that are produced on different time-scales by stars of different initial masses and chemical compositions. The nucleosynthetic outcomes of binary stars exploding as Type Ia supernovae (SNe Ia) and novae are included in our computations, adopting the single-degenerate scenario for their progenitors (Matteucci Recchi 2001 , and references therein) for SNe Ia and our previous work (Romano et al. 1999 , 2001 ; based on D'Antona Matteucci 1991 ) for novae. Since CNO elements are produced in negligible amounts in SN Ia explosions (Iwamoto et al. 1999 ), the exact choice of the route leading to such events does not affect the results presented in this paper. Classical novae, instead, are thought to significantly overproduce 13 C, 15 N and 17 O with respect to their solar abundances (e.g. José Hernanz 2007 ) making assumptions about their precursors a much more thorny problem (see the next section). The adopted nucleosynthesis prescriptions are summarized in Table 2 . The stellar yields for low- and intermediate-mass stars are from Karakas ( 2010 ). For massive stars, we adopt the grid of yields suggested by Nomoto, Kobayashi Tominaga ( 2013 , Models 1, 2 and 5). However, since the important effects of stellar rotation are not accounted for in this case, we also consider the grid of CNO yields from fast-rotating massive stars provided by the Geneva group (Meynet Maeder 2002b ; Hirschi, Meynet Maeder 2005 ; Hirschi 2007 ; Ekström et al. 2008 , Models 3 and 4). Detailed yields for super-AGB stars (Doherty et al. 2014a , b ) – often neglected in chemical evolution studies – are implemented in Models 2, 4 and 5, while nova nucleosynthesis – also disregarded in most studies – is included in one case (Model 5). All the adopted yields for single stars are dependent on mass and metallicity. For novae, we assume average yields, independent of mass and metallicity (see discussion in Section 4.1 ). The different sets of yields were all tested against the Milky Way data, while only the set labelled ‘1’ was used in the models for the other galaxies. Table 2. Prescriptions for nucleosynthesis. 4 RESULTS 4.1 Milky Way galaxy In this section, we present the results of our chemical evolution models for the Milky Way. These models differ in their adopted nucleosynthesis prescriptions (see Table 2 ). First, we discuss the predictions of Models 1, 2, 3 and 4, where the CNO elements come only from single stars.
Paper: 2018ApJ...867..119F (fulltext)
the peak of the distribution to larger distances, from ≈5 kpc in the smallest galaxy considered here to ≈12 kpc in the largest galaxy. We note that GC distributions tend to be broader around the peak of their number distributions in elliptical galaxies relative to spiral galaxies, in which they appear more concentrated around the peak. The Sérsic index slightly affects the cluster distribution (the lower the n , the smaller the peak distance), but it has a negligible effect on the final number of GCs. Figure 2. Radial distribution of surviving GCs (with IMBH in their centers) in early-type galaxies (left) and late-type galaxies (right) with stellar mass (top), (center) and (bottom), for different Sérsic indexes. Figure 3. The final cumulative radial distribution of IMBHs in star clusters in different early-type galaxies (top) and late-type galaxies (bottom), and different Sérsic indexes. 5. TDEs We calculate the TDE rates by IMBHs in GCs in two limiting cases: one in which a density cusp cannot form due to a rapid depletion by TDEs and one in which a density cusp of stars with total mass M IMBH forms around the IMBH. In both cases, we take into account the stars accreted by the IMBH and remove stars from the host GC every time they undergo a TDE. The tidal disruption of a star by an IMBH occurs when a star on an eccentric orbit has an angular momentum smaller than the so-called loss-cone angular momentum (Peebles 1972 ; Bahcall Wolf 1976 ; Lightman Shapiro 1977 ; Baumgardt et al. 2006 )whereis the tidal disruption radius of a star of mass m * and radius R * . Within the IMBH radius of influencewhere is the velocity dispersion in the cluster core, the dynamics is dominated by the IMBH gravitational potential. Nevertheless, stars exchange energy and angular momentum through two-body interactions on the typical relaxation timescalewhere Λ is a dimensionless constant of order unity (which contains the Coulomb logarithm), and and are the velocity dispersion and density at semimajor axis a , respectively. As a consequence of the numerous small-angle two-body deflections, a star with energy E and angular momentum J will diffuse in E – J space (for a comprehensive review see Alexander 2017 , and references therein). Being a random-walk process, the change in angular momentum in a time is ( J c is the angular momentum of a circular orbit with the same a ), which implies a typical timescalewhere e is the eccentricity of the star, to change the angular momentum to be of order J . Thus, more eccentric orbits relax more rapidly than circular orbits at the same a . If (empty loss-cone regime), any star deflected into the loss-cone is disrupted within a dynamical time, while if (full loss-cone regime), stars may be scattered in and out of the loss-cone on their way from apoapse to periapse (Baumgardt et al. 2004a , 2004b , 2005 ). After a rapid initial phase characterized by the wandering of the IMBH through a sea of stars (Chatterjee et al. 2002a , 2002b