adsabs/AstroCLIMB huggingface dataset:
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: Same as Figure 11, but for the Infall case after 2 Gyr of evolution. As in Figure 11, the divergence traces the boundary of the wake. However, in all cases, the converging regions behind the LMC illustrate a wider opening angle than in the Fiducial case. This results directly from the lower wind speed for the Infall case. In the Infall case, the wake’s self-gravity is not sufficient to erase the diverging flow at the center of the wake, although it is slightly narrower with self-gravity on, i.e., at y = 150 kpc, the diverging region is ∼160 kpc wide with self-gravity, compared to ∼180 kpc wide without self-gravity. Meanwhile, the differences between the FDM simulation and its CDM counterparts are similar to those in Figure 11: the resistance of FDM granules to strong accelerations washes out the coherent velocity signature seen in CDM.
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: Density profile (same as Figure 4), but for the Infall orbit case after ∼2 Gyr of evolution, averaged over five snapshots spanning 100 Myr. The CDM wake with self-gravity reaches a peak overdensity of ∼1.6, much higher than in the Fiducial case (∼0.56; see Figure 4). Removing self-gravity lowers the peak overdensity only by ∼3% in the Infall case, showing that the wake’s self-gravity is relatively unimportant in this regime. The FDM density continues to oscillate about the CDM density with an amplitude of δ ρ ∼ 0.05.
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 for the Infall orbit case simulations, where the simulations are evolved for 2 Gyr. The two CDM simulations agree closely due to the reduced importance of the wake’s self-gravity at this lower wind speed and density. The velocity dispersion within the FDM wake is lower than in all CDM wakes, as the region enclosed by the contour is ∼30 kpc shorter and thinner in the FDM case. Overall, the velocity dispersion enhancement is larger in the Infall case than the Fiducial case, as particles spend more time near the LMC, owing to the lower orbital speed (120.5 km s−1 vs. 313.6 km s−1). Consequently, the DM is more deflected by the LMC.
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: Profile plots of the z-velocity dispersion across the wake in the Infall simulations. The CDM simulations agree closely, with the self-gravity-on version having a slightly larger (δ σ  z  ∼ 0.01) peak. The FDM wake is now much colder than either CDM wake, with a peak δ σ  z  ∼ 0.07 lower than either CDM simulation.
Paper: DiskMINT: A Tool to Estimate Disk Masses with CO Isotopologues
Authors: Dingshan Deng, Maxime Ruaud, Uma Gorti, Ilaria Pascucci
Figure caption: Synthetic C18O (2–1) and (3–2) luminosity vs. M gas. In both panels, the black horizontal line marks the luminosity inferred from the data and the gray shades show their uncertainties: the (2–1) line is from Huang et al. (2020) and the (3–2) line is from Ansdell et al. (2016). The VHSE models introduced in this work are shown with the points and the lines in brown. The Gaussian models are presented with squares and the lines in blue. In each modeling scenario in this work, four models with Δgd = 5, 10, 50, 100 were simulated, and one additional best-fit model was simulated at the crossmatch “×” point with observations.
Paper: DiskMINT: A Tool to Estimate Disk Masses with CO Isotopologues
Authors: Dingshan Deng, Maxime Ruaud, Uma Gorti, Ilaria Pascucci
Figure caption: Top panel: observed photometry compared to modeled SEDs. The uncertainties of the observation are shown in the gray shade. The VHSE and Gaussian models are shown with brown and blue lines, respectively. Lower panels: C18O (2–1) velocity profile (left) and radial cut (right) in black compared to modeled profiles. The color-coding for the models is as in the top panel.
Paper: DiskMINT: A Tool to Estimate Disk Masses with CO Isotopologues
Authors: Dingshan Deng, Maxime Ruaud, Uma Gorti, Ilaria Pascucci
Figure caption: Synthetic C18O (2–1) and (3–2) luminosity vs. M gas. The observation results are presented in black. Two best-fit models are simulated at the crossmatch point, with observations represented by “×” in brown and blue, following the colors in Figure 4. All possible results from the full VHSE models in RGH22 are shown in the magenta shadings. The Gaussian models without grain surface chemistry from Miotello et al. (2017) are shown in the green shadings. The median values of all possible estimated luminosities for each M gas are presented by the dashed magenta and green lines, respectively. Our model predicts a relatively large gas disk mass (∼1 × 10−2 M ⊙) between the model grid of RGH22 and Miotello et al. (2017).
Paper: DiskMINT: A Tool to Estimate Disk Masses with CO Isotopologues
Authors: Dingshan Deng, Maxime Ruaud, Uma Gorti, Ilaria Pascucci
Figure caption: Gas density distribution, gas temperature, C18O density distribution, and C18O (2–1) and (3–2) line emitting layers (normalized to the total luminosity) are presented from left to right, with the VHSE model in the top row and the Gaussian model in the bottom row. In the first two panels, the dashed black lines mark the boundaries of the C18O location where n(C18O) ≥ 0.1 and the emitting region, and the upper and lower white lines represent A V ∼ 1 and 10, respectively. While the C18O (3–2) flux is higher than the (2–1), the emitting layers are very similar.
Paper: DiskMINT: A Tool to Estimate Disk Masses with CO Isotopologues
Authors: Dingshan Deng, Maxime Ruaud, Uma Gorti, Ilaria Pascucci
Figure caption: Top panel: SED fitting results for the VHSE model. The same notations used in Figure 3 are adopted. The median SED from Taurus (Furlan et al. 2006) is added here with a blue shade. Lower panel: normalized cumulative dust continuum fluxes for the best-fit VHSE models as a function of the distance from the star at different wavelengths. Note that even at 90 μm, 80% of the flux arises within 10 au.
Paper: Gravitational Instability, Spiral Substructure, and Modest Grain Growth in a Typical Protostellar Disk: Modeling Multiwavelength Dust Continuum Observations of TMC1A
Authors: Wenrui Xu, Satoshi Ohashi, Yusuke Aso, Hauyu Baobab Liu
Figure caption: The m = 1 spiral substructure in TMC1A. (a) Observed T b map at 0.9 mm. (b) Deprojecting the observation to face-on. To ensure that the beam does not introduce asymmetry, we also make the (effective) synthesized beam circular as follows. After the deprojection, which also stretches the synthesized beam, we convolve the image with a 1D Gaussian kernel along the minor axis of the stretched beam. The width of this second Gaussian is chosen so that the combined effect of the stretched synthesized beam and this new Gaussian kernel is equivalent to a circular 2D Gaussian beam. This produces a circular beam with a width (FWHM) of 59 au. (c) Residual T b after subtracting the azimuthal average. Markers show the peak and trough of the m = 1 spiral, whose locations are defined by local extrema in the radial direction. (d) Comparison between the observed spiral geometry (markers) and our model’s prediction (black lines). The model prediction is computed from the linear dispersion relation (Equation (6)) using the radial surface density and sound speed profiles in our model. The good agreement between the two suggests that the spiral is likely excited by GI.
Paper: Gravitational Instability, Spiral Substructure, and Modest Grain Growth in a Typical Protostellar Disk: Modeling Multiwavelength Dust Continuum Observations of TMC1A
Authors: Wenrui Xu, Satoshi Ohashi, Yusuke Aso, Hauyu Baobab Liu
Figure caption: Comparison between observations and our model (with fiducial parameters) at different wavelengths. The first row shows the observed brightness temperature (T b) maps, the second row shows the mock observations produced by our axisymmetric disk model, and the third row shows the residual maps (observation−model). We label the disk center (black plus signs), the rms noise σ rms, and the 5σ rms contours (white in the first two rows, black in the third row) for reference. The fourth row shows cuts along the major axis; here the observation (black lines) has been averaged between the two sides of the major axis, and the shaded areas show the model and observational uncertainties (see Appendix A). Our model agrees relatively well with observations at all four wavelengths, correctly capturing the radial and wavelength dependences of the brightness temperature profile. Note that we only model the axisymmetric component of the emission here; the asymmetry in the outer part of the ALMA images is mainly the result of an m = 1 spiral substructure, which we discuss in Section 4 and Figure 4. We also include results from a full radiative transfer calculation (red dotted lines) to demonstrate that ignoring protostellar irradiation in our model does not cause significant error.
Paper: Gravitational Instability, Spiral Substructure, and Modest Grain Growth in a Typical Protostellar Disk: Modeling Multiwavelength Dust Continuum Observations of TMC1A
Authors: Wenrui Xu, Satoshi Ohashi, Yusuke Aso, Hauyu Baobab Liu
Figure caption: Posterior distribution of the grain size (﹩{a}_{\max }﹩). Profiles corresponding to fiducial values and 68% confidence intervals of ﹩{a}_{\max }^{10\,\mathrm{au}}﹩ and ﹩{a}_{\max }^{100\,\mathrm{au}}﹩ are shown with solid and dashed black lines, respectively. The fragmentation barrier for our disk model at a fragmentation threshold velocity of v frag = 1 m s−1 is plotted for reference (red dashed line). The grain size remains small beyond a few au, and the main branch of the posterior shows a steep radial dependence consistent with the fragmentation barrier.
Paper: Gravitational Instability, Spiral Substructure, and Modest Grain Growth in a Typical Protostellar Disk: Modeling Multiwavelength Dust Continuum Observations of TMC1A
Authors: Wenrui Xu, Satoshi Ohashi, Yusuke Aso, Hauyu Baobab Liu
Figure caption: Top panels: summary of our posteriors (see definitions of parameters in Sections 2.2 and 2.3). The vertical axes show the probability of each bin. Solid and dashed lines mark the fiducial value (peak of posterior distribution) and 1σ (68%) confidence interval, respectively. Most parameters are relatively well constrained. Bottom panels: radial profiles of surface density Σ (left), midplane temperature T mid (middle), and optical depth for each observed wavelength (right) for our fiducial disk parameters. We caution that we cannot accurately determine the inner radius where these profiles remain valid (R in) because varying R in barely affects the dust continuum observation when R in remains unresolved and optically thick at all observed wavelengths. Light green lines in the left and middle panels correspond to disk parameters sampled from the posterior distribution. We also show power-law fits of the radial profiles of Σ and T mid for reference.
Paper: Gravitational Instability, Spiral Substructure, and Modest Grain Growth in a Typical Protostellar Disk: Modeling Multiwavelength Dust Continuum Observations of TMC1A
Authors: Wenrui Xu, Satoshi Ohashi, Yusuke Aso, Hauyu Baobab Liu
Figure caption: Amplitude of the m = 1 spiral wave in the deprojected 0.9 mm image (Figure 4(b)). Gray shades show the region with a high line-of-sight optical depth, where the relative amplitude of T b perturbation can be much lower than that of the underlying surface density perturbation. Red dashed lines show the estimated amplitude of T b perturbation after correcting for finite resolution (Section 4.2) in the optically thin region.
Paper: Gravitational Instability, Spiral Substructure, and Modest Grain Growth in a Typical Protostellar Disk: Modeling Multiwavelength Dust Continuum Observations of TMC1A
Authors: Wenrui Xu, Satoshi Ohashi, Yusuke Aso, Hauyu Baobab Liu
Figure caption: Comparison of midplane temperature (top panel) and brightness temperature at 0.9 mm (bottom panel; other wavelengths show similar results) between our model (see Xu 2022) and the RADMC-3D radiative transfer calculations. The radiative transfer results are overall similar to our model. The temperature and emission of the disk are mainly determined by internal heating as opposed to protostellar irradiation.
Paper: Gravitational Instability, Spiral Substructure, and Modest Grain Growth in a Typical Protostellar Disk: Modeling Multiwavelength Dust Continuum Observations of TMC1A
Authors: Wenrui Xu, Satoshi Ohashi, Yusuke Aso, Hauyu Baobab Liu
Figure caption: Comparison between observational properties of TMC1A (this work and Kristensen et al. 2012) and the disk population from the VANDAM Orion survey (Tobin et al. 2020). To make an apples-to-apples comparison, we follow the definitions in Tobin et al. (2020) and compute the apparent radius and flux from the best-fit Gaussian profile. (Apparent radius is defined as 2σ of the Gaussian.) For the right panel, we label the median and 16th/84th percentiles of the spectral index distribution of the VANDAM Orion sample for reference. All properties of TMC1A are quite typical compared to those of the VANDAM Orion sample.
Paper: Gravitational Instability, Spiral Substructure, and Modest Grain Growth in a Typical Protostellar Disk: Modeling Multiwavelength Dust Continuum Observations of TMC1A
Authors: Wenrui Xu, Satoshi Ohashi, Yusuke Aso, Hauyu Baobab Liu
Figure caption: Apparent disk size of TMC1A at different wavelengths. We show three commonly used definitions of apparent size: 2σ from a Gaussian fit and 68th and 95th percentiles from a Nuker fit. Because the emission profile is steep in the optically thin outer disk, the apparent disk size is generally smaller than the actual disk size and shows a trend to decrease toward longer wavelengths.
Paper: On the Decline of Star Formation during the Evolution of Galaxies
Authors: Adelheid Teklu, Rolf-Peter Kudritzki, Klaus Dolag, Rhea-Silvia Remus, Lucas Kimmig
Figure caption: The colors and lines encode the mean values of the galaxies in the different stellar mass bins, with mean ﹩{\mathrm{log}}_{10}{M}_{* }/{M}_{\mathrm{sol}}﹩ values of 9.3, 9.66, 9.95, 10.14, 10.33, 10.59, and 11.15 (from light blue representing the lowest mass bin to dark blue showing the most massive bin). Top: the cold gas mass increases with time for the three lowest mass bins, whereas for the higher-mass bins it remains relatively constant after the first steep increase. Middle: the fraction of the star-forming gas mass compared to the cold gas content decreases continuously, where there is no difference between the mass bins except for the two lowest ones. Bottom: initially, the mass of the star-forming gas increases for the high mass bins and then decreases, while it decreases for the low-mass bins.
Paper: Simple Convective Accretion Flows (SCAFs): Explaining the ≈ −1 Density Scaling of Hot Accretion Flows around Compact Accretors
Authors: Wenrui Xu, 文睿 许
Figure caption: Observational estimates of normalized accretor size and accretion rate in two SMBHs and a number of wind-fed SgXBs, compared against our empirical accretion rate scaling ﹩{\alpha }_{\dot{M}}\approx 0.7﹩ (based on γ = 5/3 simulations; black line). Our simulation result shows good agreement with observation. Here, observational estimates of r acc and ﹩\dot{M}﹩ are normalized by the characteristic radius and accretion rate of Bondi or Bondi–Hoyle–Lyttleton accretion. Details of these estimates are presented in Appendix B. For Sgr A* and M87*, the error bars show uncertainty in the accretion rate, which is the main source of uncertainty. For SgXBs, we do not show error bars because the uncertainties are difficult to quantify.
Paper: On the Decline of Star Formation during the Evolution of Galaxies
Authors: Adelheid Teklu, Rolf-Peter Kudritzki, Klaus Dolag, Rhea-Silvia Remus, Lucas Kimmig
Figure caption: The evolution of the mean temperature–density diagram for the gas of the galaxies in the highest mass bin. The intensity of the red color encodes the fraction of gas resolution elements in a grid cell. The dashed vertical line represents the star formation threshold, and the horizontal line the temperature cut for cold gas. For examples of different mass bins, see Figure 13 in the Appendix. Note that we chose to show only six representative time steps in this figure different than in other figures depicting time evolution in this study, as in these mean stacked evolution plots the overall trend is important to see and individual smaller time steps in this case do not differ strongly but rather demonstrate a smooth trend as can clearly be seen from the six time steps shown here. Also note that the color bar changes according to the maximum fraction of the shown time step.
Paper: Simple Convective Accretion Flows (SCAFs): Explaining the ≈ −1 Density Scaling of Hot Accretion Flows around Compact Accretors
Authors: Wenrui Xu, 文睿 许
Figure caption: Structure function of the 1.3 mm luminosity of Sgr A* (gray, taken from Dexter et al. 2014), in comparison with the theoretical expectation for SCAFs, which is a log–linear relation between time lag and variance (black dashed line) at larger Δt. We also show the structure function of ﹩\dot{M}﹩ from our ﹩{l}_{\max }=14﹩ vacuum sink simulation (orange) for comparison; we scale it by a factor of 0.18 to fit observation. Physically, allowing this extra factor is reasonable because the slope of the structure function could depend on the detailed physics of the flow (e.g., magnetic field, cooling) and, more importantly, the 1.3 mm luminosity is generally not a linear function of ﹩\dot{M}﹩ because the spectrum of emission can shift with ﹩\dot{M}﹩ (see Witzel et al. 2018).
Paper: On the Decline of Star Formation during the Evolution of Galaxies
Authors: Adelheid Teklu, Rolf-Peter Kudritzki, Klaus Dolag, Rhea-Silvia Remus, Lucas Kimmig
Figure caption: The evolution of the Kennicutt–Schmidt relation for the galaxies in the highest mass bin. The black triangles represent the mean star formation rate density and mean gas surface density within the gas surface density bins, for the star-forming gas. The small data points represent mean values within radial bins of single galaxies, note that one galaxy can have up to 16 data points. Blue diamonds are the cold gas including star-forming gas and turquoise triangles are only star-forming gas.
Paper: On the Decline of Star Formation during the Evolution of Galaxies
Authors: Adelheid Teklu, Rolf-Peter Kudritzki, Klaus Dolag, Rhea-Silvia Remus, Lucas Kimmig
Figure caption: The mean logarithmic mass density of cold gas as function of look-back time, where the different mass bins are color-coded as in Figure 5. The black dashed line represents the threshold for star formation.
Paper: On the Decline of Star Formation during the Evolution of Galaxies
Authors: Adelheid Teklu, Rolf-Peter Kudritzki, Klaus Dolag, Rhea-Silvia Remus, Lucas Kimmig
Figure caption:  r-band mock images of an example disk galaxy from the high mass bin sample, at 10 different redshift bins from z = 0 (upper left) to z = 2 (lower right). First and third row show the face-on view, while second and fourth row show the edge-on views. Mock images were made using the code by Martin et al. (2022).
Paper: On the Decline of Star Formation during the Evolution of Galaxies
Authors: Adelheid Teklu, Rolf-Peter Kudritzki, Klaus Dolag, Rhea-Silvia Remus, Lucas Kimmig
Figure caption: The evolution of the temperature–density diagram for one example galaxy, where each data point represents the physical properties within a resolution element. Red is gas without any star-forming component, star-forming gas ranges from turquoise and blue tones to dark blue (with increasing activity). The dashed vertical line represents the star formation threshold, and the horizontal line the temperature cut for cold gas.
Paper: On the Decline of Star Formation during the Evolution of Galaxies
Authors: Adelheid Teklu, Rolf-Peter Kudritzki, Klaus Dolag, Rhea-Silvia Remus, Lucas Kimmig
Figure caption: The evolution of the mean temperature vs. density diagram for the galaxies in the lowest (top panels) and intermediate (bottom panels) mass bins of mean values of ﹩{\mathrm{log}}_{10}{M}_{* }/{M}_{\odot }=9.28﹩ and 10.16, respectively. The intensity of the red color encodes the fraction of gas resolution elements in a grid cell. The vertical dashed line represents the star formation threshold, while the horizontal line shows the temperature cut made for cold gas.
Paper: On the Decline of Star Formation during the Evolution of Galaxies
Authors: Adelheid Teklu, Rolf-Peter Kudritzki, Klaus Dolag, Rhea-Silvia Remus, Lucas Kimmig
Figure caption: The redshift evolution of the mean mass of the cold gas without SF gas divided by the mean mass of the SF gas only. The observational data (red squares) for z ≈ 1 and z ≈ 1.3 were presented in Chowdhury et al. (2022) and the estimated observational value for M atomic and M molecular at z ≈ 0 were taken from Catinella et al. (2018) and Saintonge et al. (2017), respectively. The colors encode the lowest (light blue) and highest (dark blue) as well as the mass bin corresponding approximately to the mass the observations covered (blue dashed–dotted line).
Paper: On the Decline of Star Formation during the Evolution of Galaxies
Authors: Adelheid Teklu, Rolf-Peter Kudritzki, Klaus Dolag, Rhea-Silvia Remus, Lucas Kimmig
Figure caption: The same as Figure 5 but only the lowest, intermediate, and highest mass bins are shown in order to illustrate the standard deviation.
Paper: On the Decline of Star Formation during the Evolution of Galaxies
Authors: Adelheid Teklu, Rolf-Peter Kudritzki, Klaus Dolag, Rhea-Silvia Remus, Lucas Kimmig
Figure caption: The “global” density of the cold gas over time (i.e., the cold gas mass within a sphere divided by the sphere’s volume), colored by the final stellar mass as in Figure 5.
Paper: On the Decline of Star Formation during the Evolution of Galaxies
Authors: Adelheid Teklu, Rolf-Peter Kudritzki, Klaus Dolag, Rhea-Silvia Remus, Lucas Kimmig
Figure caption: The KS relation for all selected star-forming disk galaxies.
Paper: On the Decline of Star Formation during the Evolution of Galaxies
Authors: Adelheid Teklu, Rolf-Peter Kudritzki, Klaus Dolag, Rhea-Silvia Remus, Lucas Kimmig
Figure caption: The evolution of the spatial distribution of stars (yellow), hot gas (red), cold gas (blue), and star-forming gas (turquoise) for one example galaxy. The circle indicates 5 · R 1/2.
Paper: On the Decline of Star Formation during the Evolution of Galaxies
Authors: Adelheid Teklu, Rolf-Peter Kudritzki, Klaus Dolag, Rhea-Silvia Remus, Lucas Kimmig
Figure caption: Left: the radial profile of the mean logarithmic mass density of cold gas for the highest mass bin, where the different colors and lines represent the different look-back times and the dashed line represents the threshold for star formation. Right: the radial profile of the mean logarithmic surface density of cold gas.