adsabs/AstroCLIMB huggingface dataset:
Paper: Gravitational Wave Eigenfrequencies from Neutrino-driven Core-collapse Supernovae
Authors: Noah E. Wolfe, Carla Fröhlich, Jonah M. Miller, Alejandro Torres-Forné, Pablo Cerdá-Durán
Figure caption: Mass–radius relationship for the six nuclear EOSs considered in this work. The remnant mass M rem is the gravitational birth mass of cold neutron stars, and R rem is the corresponding radius. The markers indicate the 1060 exploding models from this work. Different markers correspond to different progenitor metallicities series listed in Table 1, including s (cross), w (plus), u (triangle), and z (circle). The transparent lines are the complete mass–radius relations for each EOS. The gray dashed lines and shaded regions indicate the mass of PSR J1810+1744 (Romani et al. 2021) and the most massive pulsar observed to date, PSR J0952–0607 (Romani et al. 2022). The thin black lines show 90% symmetric credible intervals on M rem at each radius R rem derived in Legred et al. (2021) from radio observations of pulsars (dashed–dotted) and radio, X-ray, and GW measurements of neutron star masses and radii (solid). The dark gray shaded regions in the upper left corner denote nonphysical parameter space.
Paper: Gravitational Wave Eigenfrequencies from Neutrino-driven Core-collapse Supernovae
Authors: Noah E. Wolfe, Carla Fröhlich, Jonah M. Miller, Alejandro Torres-Forné, Pablo Cerdá-Durán
Figure caption: The time–frequency evolution of the f-mode for each model in the time interval from 0.2 to 0.7 s post-bounce, organized by nuclear EOS and colored by the cold neutron star remnant mass.
Paper: Gravitational Wave Eigenfrequencies from Neutrino-driven Core-collapse Supernovae
Authors: Noah E. Wolfe, Carla Fröhlich, Jonah M. Miller, Alejandro Torres-Forné, Pablo Cerdá-Durán
Figure caption: Histograms of the f-mode frequencies from the time interval from 0.2 to 0.7 s post-bounce for each model, organized by EOS (same data as in Figure 3). Each histogram (gray or colored) corresponds to one of our simulations. For each EOS, the colored histograms correspond to the models with the minimum, median, and maximum cold neutron star mass; these values are annotated in each panel. The histograms use equally spaced bins of 10 Hz in width and are normalized to have unit area. We note that a low-frequency peak appears in all models. However, only models resulting in higher masses exhibit a double-peak structure in the histogram, with a second, high-frequency peak or at least a high-frequency tail.
Paper: Gravitational Wave Eigenfrequencies from Neutrino-driven Core-collapse Supernovae
Authors: Noah E. Wolfe, Carla Fröhlich, Jonah M. Miller, Alejandro Torres-Forné, Pablo Cerdá-Durán
Figure caption: Eigenfrequencies for the s19.0_SFHo model as a function of the time after bounce. The fundamental mode (green), g 1-mode (blue), and other eigenmodes (gray) are identified using the Cowling scheme, determined by the number of zero-crossings n found in the η  r (r) function associated with each frequency.
Paper: Gravitational Wave Eigenfrequencies from Neutrino-driven Core-collapse Supernovae
Authors: Noah E. Wolfe, Carla Fröhlich, Jonah M. Miller, Alejandro Torres-Forné, Pablo Cerdá-Durán
Figure caption: Results from fitting frequency histograms to two-component Gaussian mixtures for models with the minimum (top), median (middle), and maximum (bottom) remnant mass across all our simulations. We plot the histogram of frequencies from 0.2 s until 0.7 s post-bounce (solid line), with bins 5 Hz in width and normalized to have an area of one. The Gaussian mixture fit to each frequency histogram via expectation-maximization (dashed line) is shown with a 2σ confidence interval (shaded region around the dashed line). Vertical lines associated with the lower- and higher-frequency peaks indicate the respective positions of μ 1 and μ 2.
Paper: Gravitational Wave Eigenfrequencies from Neutrino-driven Core-collapse Supernovae
Authors: Noah E. Wolfe, Carla Fröhlich, Jonah M. Miller, Alejandro Torres-Forné, Pablo Cerdá-Durán
Figure caption: Late-time characteristic frequency μ 2 vs. the g 1-mode frequency at four times post-bounce (t pb) approximately before the avoided crossing between the f- and g 1-mode frequencies. At each time, there are clear regions of this frequency–frequency space that exclude a majority of the EOS studied in this work.
Paper: Structure, Kinematics, and Observability of the Large Magellanic Cloud’s Dynamical Friction Wake in Cold versus Fuzzy Dark Matter
Authors: Hayden R. Foote, Gurtina Besla, Philip Mocz, Nicolás Garavito-Camargo, Lachlan Lancaster, Martin Sparre, Emily C. Cunningham, Mark Vogelsberger, Facundo A. Gómez, Chervin F. P. Laporte
Figure caption: All-sky maps of the overdensity of stars in the Fiducial simulations after 0.7 Gyr of integration. Each panel shows a Mollweide projection in Galactic coordinates as defined by the Astropy convention, and includes stars with distances between 70 and 100 kpc. White lines show the paths of the LMC from our GC19 reference simulation (dashed) and in our windtunnel (solid). As in Figure 13, the contour in each panel encloses the region with a response greater than the half-maximum of the CDM simulation with self-gravity, which is δ ρ * > 0.34 here. Panels show different DM models, with CDM without self-gravity on the left, CDM with self-gravity shown in the central panel, and FDM on the right. In all three panels, the wake appears as an overdensity covering nearly an entire octant of the sky, from l ∈ ∼ [0, 120] and b ∈ ∼ [−80, 0]. The addition of self-gravity extends the contoured region to b ≈ 0, while without self-gravity the wake decays to below the contour by b ≈ −20. The extent of the stellar wake is similar in CDM and FDM when self-gravity is included.
Paper: Structure, Kinematics, and Observability of the Large Magellanic Cloud’s Dynamical Friction Wake in Cold versus Fuzzy Dark Matter
Authors: Hayden R. Foote, Gurtina Besla, Philip Mocz, Nicolás Garavito-Camargo, Lachlan Lancaster, Martin Sparre, Emily C. Cunningham, Mark Vogelsberger, Facundo A. Gómez, Chervin F. P. Laporte
Figure caption: Time-averaged median wake densities (as in Figure 14) in the observable frame with observational errors. In each panel, we sample a different number of stars from the entire sky with distances between 70 and 100 kpc to compute the median wake density. Each point shows the average and standard deviation (computed via bootstrapping) of the median density across all sampled snapshots. Black circles show the simulation data with no errors. The red triangles (blue squares) have simulated distance errors of 10% (20%). With no observational errors at our highest sampling rate (1.5 × 104 stars; left panel), the stellar wake is δ ρ * ∼ 0.05 higher when the CDM wake’s gravity is included, and the stellar wake in the FDM simulation is δ ρ * ∼ 0.07 higher than in the CDM simulation with self-gravity. As observational errors increase, the measured overdensity of the wake decreases but the same trend between all three simulations remains. With 104 stars (middle panel), the differences between DM models are lower but still distinguishable with 20% distance errors. With only 103 stars (right panel), the DM models are indistinguishable.
Paper: Structure, Kinematics, and Observability of the Large Magellanic Cloud’s Dynamical Friction Wake in Cold versus Fuzzy Dark Matter
Authors: Hayden R. Foote, Gurtina Besla, Philip Mocz, Nicolás Garavito-Camargo, Lachlan Lancaster, Martin Sparre, Emily C. Cunningham, Mark Vogelsberger, Facundo A. Gómez, Chervin F. P. Laporte
Figure caption:  z-velocity dispersion of the stellar wakes in the Fiducial simulations (similar to Figure 7 but for the stars). Comparing the CDM simulations, we see that the addition of the DM wake’s gravity widens the contour by ∼20 kpc. While the contour extends roughly 180 kpc behind the LMC in both CDM simulations, the wake tapers more quickly without the DM self-gravity. Comparing the FDM simulation to the CDM simulation with self-gravity, the FDM wake tapers more slowly than either CDM simulation, though it reaches a similar maximum width to the CDM simulation with self-gravity.
Paper: Structure, Kinematics, and Observability of the Large Magellanic Cloud’s Dynamical Friction Wake in Cold versus Fuzzy Dark Matter
Authors: Hayden R. Foote, Gurtina Besla, Philip Mocz, Nicolás Garavito-Camargo, Lachlan Lancaster, Martin Sparre, Emily C. Cunningham, Mark Vogelsberger, Facundo A. Gómez, Chervin F. P. Laporte
Figure caption: Median densities of the stellar wakes in the Fiducial simulations, averaged over 100 Myr of evolution from t = 0.6 −0.7 Gyr. Error bars show the standard deviation of the median density during this time period. The stellar wake’s density is increased by δ ρ * ∼ 0.1 when the gravity of the DM wake is added. The stellar wake is less dense in response to an FDM wake than a CDM wake, but this difference is small, only δ ρ * ∼ 0.02.
Paper: Structure, Kinematics, and Observability of the Large Magellanic Cloud’s Dynamical Friction Wake in Cold versus Fuzzy Dark Matter
Authors: Hayden R. Foote, Gurtina Besla, Philip Mocz, Nicolás Garavito-Camargo, Lachlan Lancaster, Martin Sparre, Emily C. Cunningham, Mark Vogelsberger, Facundo A. Gómez, Chervin F. P. Laporte
Figure caption: Time-averaged median radial velocity dispersion enhancement (same as Figure 20 but showing Δσ  r*) of the stars in our toy observational model. In addition to distance errors, the red triangles (blue squares) have simulated radial velocity errors of 1 (10) km s−1. With 1.5 × 104 stars and no observational errors, the velocity dispersion of the stellar wake is ∼0.6 km s−1 higher than the simulation without self-gravity with the CDM wake’s gravity, and ∼1.5 km s−1 higher with the FDM wake’s gravity. Adding observational errors reduces the measured velocity dispersion enhancement, though the differences between the simulations remain above 1σ. With 104 stars, the simulations are still distinguishable, but the differences reach just above 1σ with 10 km s−1 and 20% distance errors. Sampling 103 stars is insufficient to distinguish the simulations at any error level.
Paper: Structure, Kinematics, and Observability of the Large Magellanic Cloud’s Dynamical Friction Wake in Cold versus Fuzzy Dark Matter
Authors: Hayden R. Foote, Gurtina Besla, Philip Mocz, Nicolás Garavito-Camargo, Lachlan Lancaster, Martin Sparre, Emily C. Cunningham, Mark Vogelsberger, Facundo A. Gómez, Chervin F. P. Laporte
Figure caption: Time-averaged median enhancement of the z-velocity dispersion in the stellar wakes. The stellar wake’s velocity dispersion is raised by δ σ  z* ∼ 0.01 when adding the gravity of the DM wake. The stellar wake is heated δ σ  z* ∼ 0.01 more by an FDM wake than a CDM wake.
Paper: Structure, Kinematics, and Observability of the Large Magellanic Cloud’s Dynamical Friction Wake in Cold versus Fuzzy Dark Matter
Authors: Hayden R. Foote, Gurtina Besla, Philip Mocz, Nicolás Garavito-Camargo, Lachlan Lancaster, Martin Sparre, Emily C. Cunningham, Mark Vogelsberger, Facundo A. Gómez, Chervin F. P. Laporte
Figure caption: All-sky maps of the change in the radial velocity dispersion with respect to the shell average, ﹩{\rm{\Delta }}{\sigma }_{r* }={\sigma }_{r* }-\bar{{\sigma }_{r* }}﹩, for the fiducial simulations after 0.7 Gyr. Similar to the simulation-box projection (Figure 15), the wake signature is an enhancement of the stars’ radial velocity dispersion. The location of the velocity dispersion response is similar to the location of the density response in Figure 19. Without self-gravity, the wake decays below the contour by b ≈ −30. Both FDM and CDM with self-gravity extend the stellar wake to b ≈ 0.
Paper: Structure, Kinematics, and Observability of the Large Magellanic Cloud’s Dynamical Friction Wake in Cold versus Fuzzy Dark Matter
Authors: Hayden R. Foote, Gurtina Besla, Philip Mocz, Nicolás Garavito-Camargo, Lachlan Lancaster, Martin Sparre, Emily C. Cunningham, Mark Vogelsberger, Facundo A. Gómez, Chervin F. P. Laporte
Figure caption: Schematic showing the location of the Fiducial windtunnel wake in our toy observational model in comparison to the LMC’s orbit from the GC19 reference simulation. As in Figure 1, we show both orbits in Galactocentric coordinates, projected onto the y–z plane. The MW center of mass is denoted by the cross, the GC19 orbit is shown by the red line, and the black line shows the path of the LMC in our windtunnel simulations (equivalent to the y-axis in our simulation box). Arrows at the head of each path show the present-day location of the LMC. A blue dot shows the location at which the LMC is at a Galactocentric distance of 70 kpc, which is where we draw our Fiducial wind parameters. The path of the LMC in the windtunnel is tangent to the GC19 orbit at this location.
Paper: Structure, Kinematics, and Observability of the Large Magellanic Cloud’s Dynamical Friction Wake in Cold versus Fuzzy Dark Matter
Authors: Hayden R. Foote, Gurtina Besla, Philip Mocz, Nicolás Garavito-Camargo, Lachlan Lancaster, Martin Sparre, Emily C. Cunningham, Mark Vogelsberger, Facundo A. Gómez, Chervin F. P. Laporte
Figure caption: Divergence of the x–y velocity field for the stars in the Fiducial simulations. As in Figure 11, the star particles in the no-self-gravity CDM simulation (left) converge just behind the LMC and then continue on relatively straight paths, forming a divergent region farther downstream. Turning on DM gravity in the other panels largely eliminates this diverging region just as it does for the DM. This demonstrates how the DM wake enhances the density of the stellar wake and keeps it coherent for larger distances behind the LMC (see Figure 13), but there are no discernible differences between CDM and FDM here.
Paper: Discovery of a Variable Multiphase Outflow in the X-Ray-emitting Tidal Disruption Event ASASSN-20qc
Authors: P. Kosec, D. Pasham, E. Kara, F. Tombesi
Figure caption: XMM-Newton RGS spectrum of ASASSN-20qc. RGS 1 and RGS 2 spectra are stacked and overbinned for visual purposes only. The best-fitting ionized absorption model, consisting of two photoionized components is shown in red. The most notable elemental transitions are shown with green labels. “Fe UTA” denotes the unresolved transition array of Fe absorption lines.
Paper: A New Photoionization Model of the Narrow-line Region in Active Galactic Nuclei
Authors: Peixin Zhu, Lisa J. Kewley, Ralph S. Sutherland
Figure caption: Radiation fields of AGN produced by the OXAF model with a fixed photo index of Γ = 2.0 and a flux ratio of the nonthermal tail of p NT = 0.15 and peak energy of the accretion disk of ﹩\mathrm{log}{E}_{\mathrm{peak}}/(\mathrm{keV})\,=\,-1.5,\,-1.25,\,-1.0﹩, corresponding to E peak = 32 eV, 56 eV, 100 eV. The default AGN radiation field provided by CLOUDY is also presented for comparison.
Paper: A New Photoionization Model of the Narrow-line Region in Active Galactic Nuclei
Authors: Peixin Zhu, Lisa J. Kewley, Ralph S. Sutherland
Figure caption: Comparison of AGN models calculated by different photoionization codes on the standard optical diagnostic diagrams. Each model is presented with constant-metallicity lines (from left to right: ﹩12+\mathrm{log}({\rm{O}}/{\rm{H}})=8.43,8.70,8.89,8.96,9.09﹩) and constant-ionization-parameter lines (from bottom to top: ﹩\mathrm{log}(U)=-3.5,-3.0,-2.5,-2.0,-1.5,-1.0﹩) at a hydrogen density of n H = 1000 cm−3. The red dashed and solid blue grids represent the dust-free, isochoric-structure AGN model with solar-based abundance set and the CLOUDY default AGN radiation field calculated by CLOUDY v17 (Ferland et al. 2017) and MAPPINGS V (Sutherland et al. 2018).
Paper: Discovery of a Variable Multiphase Outflow in the X-Ray-emitting Tidal Disruption Event ASASSN-20qc
Authors: P. Kosec, D. Pasham, E. Kara, F. Tombesi
Figure caption: The best-fitting properties of the low-velocity absorbers (assuming photoionization balance) vs. the value of the cross-calibration constant between the RGS and EPIC-pn instruments. The left panels show the results for the UFO model, while the right panels show the double-blackbody model. The top two panels of each column show the column density and ionization parameter for the highly ionized absorber, while the lower two panels show the column density and the ionization parameter for the mildly ionized absorber phase.
Paper: Discovery of a Variable Multiphase Outflow in the X-Ray-emitting Tidal Disruption Event ASASSN-20qc
Authors: P. Kosec, D. Pasham, E. Kara, F. Tombesi
Figure caption: Variation of the best-fitting properties of the low-velocity absorbers during the 60 ks XMM-Newton observation, investigated by splitting it into two segments. The top two panels show the column density and the ionization parameter for the highly ionized absorber phase, while the lower two panels show the column density and the ionization parameter for the mildly ionized phase.
Paper: Discovery of a Variable Multiphase Outflow in the X-Ray-emitting Tidal Disruption Event ASASSN-20qc
Authors: P. Kosec, D. Pasham, E. Kara, F. Tombesi
Figure caption: The C-stat fit statistic for each model vs. the assumed value of the RGS–EPIC-pn cross-calibration constant. The UFO models are shown in red, while the double-blackbody models are in blue. The right y-axis shows the relative C-stat difference (in %) from the best-fitting UFO model assuming perfect RGS–EPIC-pn cross-calibration.
Paper: Dynamical Hotness, Star Formation Quenching, and Growth of Supermassive Black Holes
Authors: Hui Hong, Huiyuan Wang, H. J. Mo, Ziwen Zhang, Guangwen Chen, Wentao Luo, Tinggui Wang, Pengfei Li, Renjie Li, Yao Yao, Aoxiang Jiang
Figure caption: Left panel: σ in vs. M *. The pink solid line represents the SRDH (Equation (4)). Its slope is fixed to 0.3 and its amplitude is determined by massive (M * > 1011.5 M ⊙) elliptical galaxies (pink solid circles). Gray circles show all galaxies used in this paper and gray line corresponds to the 95% contour level. The black dashed (Gallazzi et al. 2006), dotted (Oh et al. 2020) lines are the Faber–Jackson relation taken from literature for comparison. Middle panel: Probability distribution functions of ﹩\mathrm{log}({\sigma }_{\mathrm{in}}/{\sigma }_{\mathrm{hot}})﹩ (gray solid line) and ﹩\mathrm{log}({\sigma }_{\mathrm{out}}/{\sigma }_{\mathrm{hot}})﹩ (gray dashed line) for all galaxies. Right panel: the Two-σ diagram, σ in/σ hot vs. σ out/σ hot. Symbols are the same as that in the left panel except that the black dashed line shows the 1:1 relation.
Paper: Dynamical Hotness, Star Formation Quenching, and Growth of Supermassive Black Holes
Authors: Hui Hong, Huiyuan Wang, H. J. Mo, Ziwen Zhang, Guangwen Chen, Wentao Luo, Tinggui Wang, Pengfei Li, Renjie Li, Yao Yao, Aoxiang Jiang
Figure caption: The sSFR as a function of ﹩\mathrm{log}({\sigma }_{\mathrm{in}}/{\sigma }_{\mathrm{hot}})﹩ for FQGs (red circles), PQGs (green triangles), and FSGs (blue squares). Galaxies of different stellar masses are shown in different panels.
Paper: Dynamical Hotness, Star Formation Quenching, and Growth of Supermassive Black Holes
Authors: Hui Hong, Huiyuan Wang, H. J. Mo, Ziwen Zhang, Guangwen Chen, Wentao Luo, Tinggui Wang, Pengfei Li, Renjie Li, Yao Yao, Aoxiang Jiang
Figure caption: The median quenched profiles (f q(R/R e)) for galaxies with different ﹩{\bar{f}}_{{\rm{q}}}﹩ bins as indicated in the figure. The shadows show the 16th and 84th percentiles of the distribution of f q. Note that galaxies with ﹩{\bar{f}}_{{\rm{q}}}\lt 0.05﹩ are FSGs (dark blue), galaxies with ﹩{\bar{f}}_{{\rm{q}}}\gt 0.95﹩ are FQGs (red), the rest galaxies are PQGs. We do not show galaxies with ﹩{\bar{f}}_{{\rm{q}}}=0﹩ or ﹩{\bar{f}}_{{\rm{q}}}=1﹩.
Paper: Dynamical Hotness, Star Formation Quenching, and Growth of Supermassive Black Holes
Authors: Hui Hong, Huiyuan Wang, H. J. Mo, Ziwen Zhang, Guangwen Chen, Wentao Luo, Tinggui Wang, Pengfei Li, Renjie Li, Yao Yao, Aoxiang Jiang
Figure caption: Central velocity dispersion (σ in) vs. stellar mass (M *) for three different classes of galaxies, FQGs (left: red circles), PQGs (middle: green triangles), and FSGs (right: blue squares). The pink solid line is the SRDH (Equation (4)). The black solid line shows the best fit for FQGs (Equation (5)), i.e., quenched galaxy scaling relation (QGSR). The black dashed lines represent the 1-Δ intrinsic scatter of this relation.
Paper: Dynamical Hotness, Star Formation Quenching, and Growth of Supermassive Black Holes
Authors: Hui Hong, Huiyuan Wang, H. J. Mo, Ziwen Zhang, Guangwen Chen, Wentao Luo, Tinggui Wang, Pengfei Li, Renjie Li, Yao Yao, Aoxiang Jiang
Figure caption: The σ in vs. M q for QCCs (purple) and the σ in vs. M * for PQGs in which QCCs are identified. The black solid lines show the QGSR (Equation (5)), and dashed lines show the intrinsic scatter. We show galaxies in different ﹩{\bar{f}}_{{\rm{q}}}﹩ bins in different panels. The parameters χ 2 presented in each panel are calculated using Equation (6) and show the distances of PQGs and QCCs to the QGSR. Please see the text for details.
Paper: Dynamical Hotness, Star Formation Quenching, and Growth of Supermassive Black Holes
Authors: Hui Hong, Huiyuan Wang, H. J. Mo, Ziwen Zhang, Guangwen Chen, Wentao Luo, Tinggui Wang, Pengfei Li, Renjie Li, Yao Yao, Aoxiang Jiang
Figure caption: Red circles: R e vs. M * for FQGs. Purple circles: R q vs. M q for QCCs. The solid and dashed–dotted lines show the best-fitting results for FQGs and QCCs, respectively.