adsabs/AstroCLIMB huggingface dataset:
Paper: Dynamical Masses for 23 Pre-main-sequence Stars in Upper Scorpius: A Critical Test of Stellar Evolutionary Models
Authors: A. P. M. Towner, J. A. Eisner, P. D. Sheehan, L. A. Hillenbrand, Y.-L. Wu
Figure caption: Comparison of stellar masses returned by each PMS evolutionary model set to the dynamical masses we derive using pdspy. The color scheme is the same as in Figure 7. In all panels, the isochronal mass is shown on the y-axis, and the dynamical mass (same in all cases) is shown on the x-axis. The black dotted line represents a 1:1 relation in all panels. The ODR best-fit line slope (m) and intercept (b) are listed in each panel. Top row: BHAC15 (left), PARSEC v1.1 (A. Bressan et al. 2012; center), and PARSEC v1.2S (Y. Chen et al. 2014; right). Bottom row: nonmagnetic models of G. A. Feiden (2016; left) and magnetic models of G. A. Feiden (2016; center). The significant improvement in agreement of the magnetic models of G. A. Feiden (2016) with the dynamical masses, as compared to the other PMS evolutionary models tested here, can be clearly seen in the bottom-center panel. A figure covering the full range of masses can be found in Appendix C.
Paper: Dynamical Masses for 23 Pre-main-sequence Stars in Upper Scorpius: A Critical Test of Stellar Evolutionary Models
Authors: A. P. M. Towner, J. A. Eisner, P. D. Sheehan, L. A. Hillenbrand, Y.-L. Wu
Figure caption: Isochronal age and mass contour lines for each of the five model sets considered in this paper. The mass and age ranges are 0.1–1.4 M⊙ and 1–25 Myr in all panels. Black points show the L⋆ and Teff for our sample. Error bars come from the uncertainties listed in Table 1. The contours for each model are shown in a different color for ease of visual distinction; this color scheme is carried through all related figures for the rest of this paper. Top row: BHAC15 (I. Baraffe et al. 2015; left, in blue), PARSEC v1.1 (A. Bressan et al. 2012; center, in magenta), and PARSEC v1.2S (Y. Chen et al. 2014; right, in green). Bottom row: nonmagnetic models of G. A. Feiden (2016; left, in orange) and magnetic models of G. A. Feiden (2016; center, in red).
Paper: Dynamical Masses for 23 Pre-main-sequence Stars in Upper Scorpius: A Critical Test of Stellar Evolutionary Models
Authors: A. P. M. Towner, J. A. Eisner, P. D. Sheehan, L. A. Hillenbrand, Y.-L. Wu
Figure caption: Disk dust mass (see Table 8) vs. stellar mass for the 23 sources in our sample. Upper limits on dust masses are marked with downward arrows. Upper limits on stellar mass are marked with left-facing arrows. In both panels, the black points denote the stellar masses we derive via Keplerian fitting, and the blue points denote stellar masses derived from the best-fit BHAC15 PMS models using L⋆ and Teff. Left panel: disk mass vs. stellar mass assuming the disk dust temperature scales as 25 K (L⋆/L⊙)0.25. The best-fit lines using the dynamical and BHAC15 stellar masses are shown in black and blue, respectively; the best-fit slope (m) and intercept (b) for each case are shown in the upper-left corner. Median uncertainties are shown as error bars in the upper-right corner. Right panel: as for the left panel, except the disk dust masses were calculated assuming a constant dust temperature of 20 K.
Paper: Dynamical Masses for 23 Pre-main-sequence Stars in Upper Scorpius: A Critical Test of Stellar Evolutionary Models
Authors: A. P. M. Towner, J. A. Eisner, P. D. Sheehan, L. A. Hillenbrand, Y.-L. Wu
Figure caption: Corner plot showing the distribution of walker values for each parameter for the last 1000 steps. This example is for source J16082324−1930009. The “x0” and “y0” labels refer to the R.A. and decl. offsets, respectively. The data points are colored by their χ2 values, with darker colors indicating lower χ2. Median walker values are shown in black, with standard deviations shown as black error bars. The χ2 best-fit values are shown in red, with the Δχ2-based uncertainties shown as red error bars. The median- and χ2-based best-fit values typically agree within uncertainties, but can clearly disagree by up to ∼1 standard deviation. The potential underestimation of uncertainties from the standard deviation method as opposed to the Δχ2 method can be clearly seen.
Paper: Dynamical Masses for 23 Pre-main-sequence Stars in Upper Scorpius: A Critical Test of Stellar Evolutionary Models
Authors: A. P. M. Towner, J. A. Eisner, P. D. Sheehan, L. A. Hillenbrand, Y.-L. Wu
Figure caption: Representative example of the trace plots we used to determine fit convergence. The example shown is for source J16090075−1908526. In both panels, the first 1000 steps are excluded from plotting as they are considered burn-in steps. Top: the blue line is the median value of all walkers at each step. The blue-shaded region is the scaled median absolute deviation from the median (scaled MAD) at each step, and is used to weight the linear fit. The black dotted line shows the best-fit line for the last 1000 steps. The properties of the best-fit line are listed in the upper-right corner. Bottom: same as for the top panel, except that the blue line is the mean value of all walkers at each step and the blue-shaded region is the standard deviation at each step.
Paper: Dynamical Masses for 23 Pre-main-sequence Stars in Upper Scorpius: A Critical Test of Stellar Evolutionary Models
Authors: A. P. M. Towner, J. A. Eisner, P. D. Sheehan, L. A. Hillenbrand, Y.-L. Wu
Figure caption: Cumulative distribution functions (CDFs) of stellar mass for the five PMS evolutionary models considered in this work, along with the dynamical masses we derive using pdspy. In this figure, we include only those sources whose dynamical mass is ≤1 M⊙. A figure showing CDFs using the full sample can be found in Appendix C.
Paper: Dynamical Masses for 23 Pre-main-sequence Stars in Upper Scorpius: A Critical Test of Stellar Evolutionary Models
Authors: A. P. M. Towner, J. A. Eisner, P. D. Sheehan, L. A. Hillenbrand, Y.-L. Wu
Figure caption: Optical-infrared photometry (black points) and best-fit BT-Settl models (red curves) for 23 sources fit with BT-Settl models (J16113134−1838259 A and B were excluded; see Section 2.2). The y-axis error bars are the uncertainties used in the fit, and the x-axis “error” bars show the wavelength ranges used to calculate the model Sν for each observing band (≥50% of maximum transmission; see text). The best-fit parameters for each source are listed in Table 9.
Paper: Dynamical Masses for 23 Pre-main-sequence Stars in Upper Scorpius: A Critical Test of Stellar Evolutionary Models
Authors: A. P. M. Towner, J. A. Eisner, P. D. Sheehan, L. A. Hillenbrand, Y.-L. Wu
Figure caption: Moment 0 (top row) and moment 1 (bottom row) maps of the six sources whose continuum emission is reasonably well resolved. The moment maps show 12CO emission in all cases except J16113134−1838259 B, which show 13CO. 870 μm continuum contours are overlaid in black; the contours show the 0.5 × Ipeak level. The 12CO beams are shown in the bottom-left corner of the moment 1 images, and the continuum beams are shown in the bottom-right corner.
Paper: Probing Evolution of Long GRB Properties through their Cosmic Formation History Aided by Machine Learning–predicted Redshifts
Authors: Dhruv S. Bal, Aditya Narendra, Maria Giovanna Dainotti, Nikita S. Khatiya, Aleksander Ł. Lenart, Dieter H. Hartmann
Figure caption: The comparison of ρPS(z) and ρCS(z) in this study, with rate densities from the X-ray study of K25 and the optical study of D24a. All other data points/lines correspond to various SFRDs in the literature, as specified in the legend. All curves/data points are renormalized to the PS for better comparison.
Paper: First X-Ray and Radio Polarimetry of the Neutron Star Low-mass X-Ray Binary GX 17+2
Authors: Unnati Kashyap, Thomas J. Maccarone, Eliot C. Pattie, Mason Ng, Swati Ravi, Alexandra J. Tetarenko, Pau Bosch-Cabot, Herman L. Marshall
Figure caption: First panel: IXPE (2–8 keV) light curve of GX 17+2. Time bins of 128 s are used. Second panel: NICER (0.5–10 keV) light curve of GX 17+2. Time bins of 8 s are used. Third panel: NuSTAR (3.0–79.0 keV) light curve of GX 17+2. Time bins of 60 s are used. The source was observed by NICER and NuSTAR simultaneously with the IXPE observations.
Paper: Probing Evolution of Long GRB Properties through their Cosmic Formation History Aided by Machine Learning–predicted Redshifts
Authors: Dhruv S. Bal, Aditya Narendra, Maria Giovanna Dainotti, Nikita S. Khatiya, Aleksander Ł. Lenart, Dieter H. Hartmann
Figure caption: Left panel: the fit to σ of the PS with the best parameters derived from the sigmoid function. The best-fit parameters to this function are noted in the first row of Table 1. Right panel: the fit to σ of the CS with the best parameters derived from a piecewise function. The data points below zcut = 3.01 are best fit with a fourth-order polynomial, while the data points above zcut are best fit with a sigmoid. The best-fit parameters to these functions are noted in the second and third rows of Table 1.
Paper: Probing Evolution of Long GRB Properties through their Cosmic Formation History Aided by Machine Learning–predicted Redshifts
Authors: Dhruv S. Bal, Aditya Narendra, Maria Giovanna Dainotti, Nikita S. Khatiya, Aleksander Ł. Lenart, Dieter H. Hartmann
Figure caption: ρPS(z) for four flux threshold cases of −11.58, −11.4, −11.3, and −11.15. The filled circles indicate the LGRB-RD corrected for intrinsic luminosity evolution for the PS. The filled circles are color-coded with respect to the vertical dashed lines in the right panel of Figure 5. The black dashed lines show the SFRD from the MD14 study. The peak of SFRD is renormalized to the peak of LGRB-RD for easier comparison.
Paper: Probing Evolution of Long GRB Properties through their Cosmic Formation History Aided by Machine Learning–predicted Redshifts
Authors: Dhruv S. Bal, Aditya Narendra, Maria Giovanna Dainotti, Nikita S. Khatiya, Aleksander Ł. Lenart, Dieter H. Hartmann
Figure caption: Left panel: the z distribution of the total sample, which contains all GRBs with X-ray plateaus detected by Swift and the distribution of the PS. Right panel: the KS test of the two samples in the left panel. We include four cases of F﹩{}_{\mathrm{lim}}﹩ corresponding to a 5%, 10%, 15%, and 20% cut from left to right. The 5% cut has the highest p-value.
Paper: Probing Evolution of Long GRB Properties through their Cosmic Formation History Aided by Machine Learning–predicted Redshifts
Authors: Dhruv S. Bal, Aditya Narendra, Maria Giovanna Dainotti, Nikita S. Khatiya, Aleksander Ł. Lenart, Dieter H. Hartmann
Figure caption: ρCS(z) for four flux threshold cases of −11.85, −11.62, −11.4, and −11.3. The filled circles indicate the LGRB-RD corrected for intrinsic luminosity evolution for the CS. The filled circles are color-coded with respect to the vertical dashed lines in the right panel of Figure 7. The black dashed lines show the SFRD from the MD14 study. The peak of SFRD is renormalized to the peak of LGRB-RD for easier comparison.
Paper: Probing Evolution of Long GRB Properties through their Cosmic Formation History Aided by Machine Learning–predicted Redshifts
Authors: Dhruv S. Bal, Aditya Narendra, Maria Giovanna Dainotti, Nikita S. Khatiya, Aleksander Ł. Lenart, Dieter H. Hartmann
Figure caption: Left panel: the z distribution of the total sample, which contains all GRBs with X-ray plateaus detected by Swift and the distribution of the CS. Right panel: the KS test of the two samples in the left panel. We include four cases of F﹩{}_{\mathrm{lim}}﹩ corresponding to a 5%, 10%, 15%, and 20% cut from left to right.
Paper: Morphological Regimes of Rotating Moist Convection
Authors: Whitney T. Powers, Adrian E. Fraser, Evan H. Anders, Jeffrey S. Oishi, Benjamin P. Brown
Figure caption: Velocity stream lines for a single funnel from simulation 12 are shown over a plot of potential temperature fluctuations about the horizontal mean at z = 0.8 H. The color of the stream lines indicates the vertical velocity w. We observe counterclockwise rotating upflows diverging from the upflow column. Stream lines cross the spiral core and descend while crossing this feature. The cell boundaries form clockwise vortexes of descending fluid at the vertices of the hexagonal cells.
Paper: Morphological Regimes of Rotating Moist Convection
Authors: Whitney T. Powers, Adrian E. Fraser, Evan H. Anders, Jeffrey S. Oishi, Benjamin P. Brown
Figure caption: Velocity stream lines for a single cell are shown over a plot of potential temperature fluctuations about the horizontal mean at z = 0.8 H for simulation 11 (see Appendix B) in the cell regime. The color of the stream lines indicates the vertical velocity w. The stream lines have a cyclonic vorticity at the center of the cell, and at the periphery of the cell, the flows are anticyclonic. There are additionally cyclonic vortexes in the downflowing cell vertices.
Paper: Morphological Regimes of Rotating Moist Convection
Authors: Whitney T. Powers, Adrian E. Fraser, Evan H. Anders, Jeffrey S. Oishi, Benjamin P. Brown
Figure caption: The suite of simulations is shown on a plot of reduced Rayleigh number (﹩{ \mathcal R }\equiv {\rm{Ra}}\,{{\rm{Ek}}}^{4/3}﹩) against Ekman number Ek, as well as the critical reduced Rayleigh number curve in black. Note that if the Ekman number is changed while keeping ﹩{ \mathcal R }﹩ fixed, the freefall time changes. The color of the points indicates the dynamical regime for each simulation.
Paper: Cloud Tides Can Induce the Fast Disruption of Star Clusters and Offer an Explanation for Gaia Strings
Authors: Xiao-Tong Chen, Guang-Xing Li
Figure caption: Comparison with other studies. Blue triangles represent clusters with string structures from C. Zucker et al. (2022), and red triangles represent YSOs from J.-X. Zhou et al. (2022), whose sizes and velocities act as tracers of the cloud they are associated with. The Gaia string exhibits a velocity discrepancy relative to the molecular cloud, which can be attributed to cloud tides.
Paper: Cloud Tides Can Induce the Fast Disruption of Star Clusters and Offer an Explanation for Gaia Strings
Authors: Xiao-Tong Chen, Guang-Xing Li
Figure caption: A case of a star cluster under a cloud tide found in the Orion molecular cloud. The left Planck plot shows the distribution of gas and the star clusters that are under the influence of the cloud tide. Defining this radial direction as the y-axis, we calculated the velocity dispersion in all directions (right panel), showing significantly higher dispersion along the longer axis, which points to the nearby Orion B cloud.
Paper: Cloud Tides Can Induce the Fast Disruption of Star Clusters and Offer an Explanation for Gaia Strings
Authors: Xiao-Tong Chen, Guang-Xing Li
Figure caption: Cluster evolution in the absence and presence of cloud tide. The top panels show the slow evolution without the cloud tide effect, while the bottom panels show acceleration due to the cloud tide. A cloud tide can lead to significant expansion. In a few Myr, the star cluster can expand from a few parsecs to a few tens of parsecs.
Paper: Cloud Tides Can Induce the Fast Disruption of Star Clusters and Offer an Explanation for Gaia Strings
Authors: Xiao-Tong Chen, Guang-Xing Li
Figure caption: Diagram showing the entire evolutionary process of the cluster. Star clusters initially form within molecular clouds and remain embedded in them. After gas expulsion, the cluster becomes unbound, and gravity from the surrounding residual cloud stretches it into a stringlike structure until the cloud disperses.
Paper: Cloud Tides Can Induce the Fast Disruption of Star Clusters and Offer an Explanation for Gaia Strings
Authors: Xiao-Tong Chen, Guang-Xing Li
Figure caption: An illustration of a cloud tide. The sketch shows a cluster with density ρlocal different evolution under a cloud tide. Before gas expulsion, the tidal tensor is compressive. After gas expulsion, the cluster could be disrupted by its parent cloud.
Paper: Cloud Tides Can Induce the Fast Disruption of Star Clusters and Offer an Explanation for Gaia Strings
Authors: Xiao-Tong Chen, Guang-Xing Li
Figure caption: Cluster evolves with size-dominated (blue line) and velocity-dominated (orange line) initial preconditions. With a tidal timescale, the cluster is virialized.
Paper: Multiphase Gas Offsets in the Atmospheres of Central Galaxies and Their Consequences for SMBH Activation. I. The Hot and Warm Ionized Gas Phases
Authors: Francesco Ubertosi, Fabrizio Brighenti, Ewan O'Sullivan, Gerrit Schellenberger, Myriam Gitti, Simona Giacintucci, Pasquale Temi, Laurence P. David, Jan Vrtilek, Tiziana Venturi, Elisabetta Liuzzo, Marcella Massardi, Kamlesh Rajpurohit
Figure caption: Left: comparison between the SMBH–Hα peak offset and the SMBH–X-ray peak offset; the dashed line marks the line of 1:1 scaling between the two distances. Right: velocity of the warm gas, measured from the MUSE data within an extraction region centered on the Hα peak with radius 1.8 kpc, vs. the SMBH–Hα peak offset. The dashed lines show the times required to traverse the distance on the x-axis at various (constant) velocities on the y-axis. For example, the brown line indicates that for a velocity of 50 km s−1, the time needed to travel a distance of 6 kpc is approximately 100 Myr. Thus, depending on the warm-gas velocity and the offset of the Hα peak from the SMBH, each system lies along a different crossing timeline. In both panels, the open squares represent systems with a significant Hα offset, while the filled circles represent the remaining objects in the sample.
Paper: Multiphase Gas Offsets in the Atmospheres of Central Galaxies and Their Consequences for SMBH Activation. I. The Hot and Warm Ionized Gas Phases
Authors: Francesco Ubertosi, Fabrizio Brighenti, Ewan O'Sullivan, Gerrit Schellenberger, Myriam Gitti, Simona Giacintucci, Pasquale Temi, Laurence P. David, Jan Vrtilek, Tiziana Venturi, Elisabetta Liuzzo, Marcella Massardi, Kamlesh Rajpurohit
Figure caption:                         The same as Figure 6 but without the Hα contours. The red square and pink triangle mark the positions of the X-ray peaks in the broadband (0.5–7 keV) and soft-band (0.5–1.2 keV) X-ray images, respectively (see Appendix B.3 for details). The dashed red and pink contours outline “statistical confidence regions” for the positions of the X-ray peaks (in the broadband and soft-band X-ray images, respectively), defined as the area containing pixels with X-ray counts ﹩{N}_{C}\gt {N}_{C}^{P}-\sqrt{{N}_{C}^{P}}﹩, where ﹩{N}_{C}^{P}﹩ is the number of counts in the pixel corresponding to the X-ray peak. The vertical red line on the color bar indicates the count level that defines this contour (for the broadband). The black star marks the SMBH position (see Table 1). No contours are shown for ACT-CL J1521.8+0742 and A1644, as their X-ray surface brightness is below 1 count per pixel. In these cases, the statistical confidence region for the brightest pixel would formally extend to the edge of the Chandra image. As noted in Appendix B.3, these contours would represent the confidence regions for the positions of the X-ray peaks in terms of X-ray counts, but we consider in our results the more conservative astrometric uncertainty of the X-ray data. We also show the location of the centroid of the X-ray surface brightness distribution with a blue diamond (see Appendix B.3 for details).
Paper: Multiphase Gas Offsets in the Atmospheres of Central Galaxies and Their Consequences for SMBH Activation. I. The Hot and Warm Ionized Gas Phases
Authors: Francesco Ubertosi, Fabrizio Brighenti, Ewan O'Sullivan, Gerrit Schellenberger, Myriam Gitti, Simona Giacintucci, Pasquale Temi, Laurence P. David, Jan Vrtilek, Tiziana Venturi, Elisabetta Liuzzo, Marcella Massardi, Kamlesh Rajpurohit
Figure caption: Left: comparison between the positions of the radio cores in VLBA images and those in VLASS 3 GHz images for the 20 systems with VLBA detections (see Appendix B.1). The distribution is centered near zero, with a dispersion of ∼0﹩\mathop{.}\limits^{\unicode{x02033}}﹩16, consistent with the VLASS positional accuracy (∼0﹩\mathop{.}\limits^{\unicode{x02033}}﹩2). As noted in Appendix B.1, this supports using VLA observations to estimate SMBH positions in VLBA-undetected systems (i.e., ACT-CL J1521.8+0742, A133, A2495, and A2566). Center: comparison between the positions of the radio cores in VLBA images and the optical peaks of the galaxies in HST images for the 11 systems with both VLBA detections and available HST data (see Appendix B.1 for details). The distribution is centered around zero, with a dispersion of approximately 0﹩\mathop{.}\limits^{\unicode{x02033}}﹩05—comparable with the positional accuracy of HST (≤0﹩\mathop{.}\limits^{\unicode{x02033}}﹩1). As discussed in Appendix B.1, this validates the use of HST imaging to locate the SMBHs in VLBA-undetected systems (i.e., RX J0821.0+0752). Right: comparison between the X-ray peak positions reported in this work (Table 1) and those from D. S. Hudson et al. (2010) for 11 overlapping systems (see Appendix B.3). Points are color-coded by the ratio of the Chandra exposure times in this work and those of D. S. Hudson et al. (2010). As detailed in Appendix B.3, the agreement validates our X-ray peak identification method. The only outlier is A3581, with an offset of ΔR.A. = 5﹩\mathop{.}\limits^{\unicode{x02033}}﹩2 ± 4﹩\mathop{.}\limits^{\unicode{x02033}}﹩1 and Δdecl. =4﹩\mathop{.}\limits^{\unicode{x02033}}﹩9 ± 4﹩\mathop{.}\limits^{\unicode{x02033}}﹩1, which is likely explained by the 15 times deeper exposure used in our analysis.
Paper: Multiphase Gas Offsets in the Atmospheres of Central Galaxies and Their Consequences for SMBH Activation. I. The Hot and Warm Ionized Gas Phases
Authors: Francesco Ubertosi, Fabrizio Brighenti, Ewan O'Sullivan, Gerrit Schellenberger, Myriam Gitti, Simona Giacintucci, Pasquale Temi, Laurence P. David, Jan Vrtilek, Tiziana Venturi, Elisabetta Liuzzo, Marcella Massardi, Kamlesh Rajpurohit
Figure caption: The link between multiphase gas offsets and SMBH activation. Left: radio power at 5 GHz (from parsec-scale VLBA radio observations) of the 25 BCGs in our sample vs. the distance between the positions of the SMBH and of the hot-gas peak (from X-ray emission in Chandra data). Right: radio power at 5 GHz vs the distance between the positions of the SMBH and of the warm-gas peak (from the Hα emission lines in VLT/MUSE data). In both panels, the empty points represent systems with significant offsets (that is, for which the distance Δ between the SMBH and the gas peak is larger than the uncertainty δΔ), and the arrows represent the upper limits on the radio power.
Paper: Multiphase Gas Offsets in the Atmospheres of Central Galaxies and Their Consequences for SMBH Activation. I. The Hot and Warm Ionized Gas Phases
Authors: Francesco Ubertosi, Fabrizio Brighenti, Ewan O'Sullivan, Gerrit Schellenberger, Myriam Gitti, Simona Giacintucci, Pasquale Temi, Laurence P. David, Jan Vrtilek, Tiziana Venturi, Elisabetta Liuzzo, Marcella Massardi, Kamlesh Rajpurohit
Figure caption: Multiwavelength view of the four systems with a significant Hα peak–SMBH offset. The panels show smoothed X-ray Chandra maps of the hot gas, with grayscale contours of the Hα line from MUSE data. The red square marks the position of the X-ray peak, the purple circle shows the location of the Hα peak, and the black star shows the position of the SMBH (see Table 1).
Paper: A New Sample of Dwarf Galaxies with X-Ray-selected Active Galactic Nucleus Candidates from the eROSITA All-Sky Survey
Authors: John-Michael Eberhard, Amy E. Reines
Figure caption: Comparison of observed X-ray luminosities vs. the expected luminosity from XRBs, using the XRB relation from three different papers. The blue solid line shows the one-to-one relation, with the blue dashed lines showing the scatter in the XRB relation. The 1σ error bars of the actual X-ray luminosities are shown. Red points indicate galaxies that fall within 1σ scatter of the XRB relation, indicating that they have emission consistent with XRB populations. Left: XRB relation from B. D. Lehmer et al. (2010). Middle: XRB relation from B. D. Lehmer et al. (2019). Right: XRB relation from R. Geda et al. (2024).