adsabs/AstroCLIMB huggingface dataset:
Paper: Charting Galactic Accelerations with Stellar Streams and Machine Learning
Authors: Jacob Nibauer, Vasily Belokurov, Miles Cranmer, Jeremy Goodman, Shirley Ho
Figure caption: Schematic outline of the stream unwrapping procedure. Top left: Input phase-space data, where subsequent points in the data set are connected by blue lines. Top middle: We implement a nearest-neighbors algorithm to connect tracers that have a small Euclidean distance in phase space. There is an added momentum condition, which encourages the nearest-neighbors graph edges in the position space to fall roughly tangent to the local direction of motion of the stream. The stream is color coded by the initial ordering, γ init. Top right: The momentum condition inevitably leaves out a number of stream members from the nearest-neighbors graph, requiring a flexible interpolation to assign an ordering (i.e., γ value) to tracers that were initially left out of the graph. Interpolation is performed with a neural network, which outputs a membership probability for tracers in addition to the ordering parameter, γ. Bottom right: Output of the interpolation neural network, color coded by the interpolated γ values across the stream. Blue points indicate tracers with the lowest probability membership, though all stars have membership probability >0.99 as they are stream members. Bottom middle: The interpolation neural network (top right) is connected to a new neural network called Param-Net, which takes the ordering parameter γ as an input and outputs the mean position along the stream. γ values are further refined using the same momentum condition as before: namely, that increasing γ corresponds to motion along the stream from trailing to leading arm. Bottom left: Example output of the final unwrapped stream, color coded by the final γ values.
Paper: Charting Galactic Accelerations with Stellar Streams and Machine Learning
Authors: Jacob Nibauer, Vasily Belokurov, Miles Cranmer, Jeremy Goodman, Shirley Ho
Figure caption:  N-body realization of a stellar stream in an axisymmetric halo potential. In the left panel, we plot a projection of the N-body stream in angular coordinates. In the right panel, the stream is plotted in the space of energy and the z-component of the angular momentum, both of which are integrals of motion in a stationary axisymmetric potential. These quantities are plotted relative to the progenitor cluster, shaded in gray. Outside of the progenitor, tracers are color coded by their position angle, ϕ 1, in the left panel. This angle increases monotonically along the stream, demonstrating that stream stars have locally similar integrals of motion at slightly different phase angles. This figure is provided only for conceptual purposes; our method does not model the energy distribution of stellar streams directly, nor does it work in the space of integrals of motion.
Paper: Charting Galactic Accelerations with Stellar Streams and Machine Learning
Authors: Jacob Nibauer, Vasily Belokurov, Miles Cranmer, Jeremy Goodman, Shirley Ho
Figure caption: Top row: Mock stellar stream generated in a triaxial logarithmic potential using the “particle-spray” method introduced in Fardal et al. (2015). ϕ 1 and ϕ 2 are the angular coordinates, which are rotated with respect to the standard equatorial frame. Stream particles are binned by their angular positions and color coded by the mean energy relative to the progenitor (around ϕ 1 ≈ −75°). For a small band of width δ ϕ 1, tracers have a locally similar mixture of energies at slightly different phase angles. Middle row: We fit an orbit to the stream illustrated in the top row using a standard χ 2 fitting routine. The binned stream measurements are illustrated by the black points with 1σ error bars, while the red curve is the best-fit orbit in the logarithmic potential from Equation (15). Bottom row: The black points with error bars and the gray curve are the same as the points and red curve in the middle panel (orbit fitting). We overplot our stream parameterization, color coded by the energy of the stream track in the ground-truth potential, relative to the progenitor. The color bar for the bottom row is the same as in the top row. Our method does not require that the stream traces a path of constant energy in any potential and captures the slowly evolving energy gradient seen among the stream in the top row.
Paper: Charting Galactic Accelerations with Stellar Streams and Machine Learning
Authors: Jacob Nibauer, Vasily Belokurov, Miles Cranmer, Jeremy Goodman, Shirley Ho
Figure caption: Inferred acceleration field in the neighborhood of the stream in Figure 6 for two methods: orbit fitting (red and cyan), our approach (green), while the ground-truth acceleration  a (γ) is plotted in black. The red curve, derived from orbit fitting, assumes the correct model for the galactic potential. The cyan curve assumes an incorrect axisymmetric functional form for the potential. We find that orbit fitting can yield a biased estimate of the acceleration field along the stream, as it incorrectly assumes that the stream is characterized by an isoenergy curve in phase space. Adopting an imperfect model for the galactic potential is also found to yield biased estimates of the acceleration field. Our method is less restrictive and captures the slowly evolving energy gradient among stream particles as illustrated in Figure 6 (bottom row). We also do not require an intermediate model for the galactic potential.
Paper: Charting Galactic Accelerations with Stellar Streams and Machine Learning
Authors: Jacob Nibauer, Vasily Belokurov, Miles Cranmer, Jeremy Goodman, Shirley Ho
Figure caption: Reconstructed acceleration vectors along the tracks of six stellar streams. Each column is a different stream, while the three rows are the Cartesian components of the acceleration vector. The black points depict the ground-truth acceleration at the specified position, while the red points depict our reconstruction from directly fitting the streams. Streams are parameterized in terms of the scalar parameter γ, which increases monotonically along the stream. The missing regions typically centered near γ = 0 are where the progenitor is located. We remove the progenitor from this analysis, as these regions of the stream (if observable) lead to sharp changes in morphology (see Section 3.2).
Paper: Charting Galactic Accelerations with Stellar Streams and Machine Learning
Authors: Jacob Nibauer, Vasily Belokurov, Miles Cranmer, Jeremy Goodman, Shirley Ho
Figure caption: Top row: Mock stellar stream plotted in galactocentric x, y, and z coordinates (black scatter points). The bulk motion and position of the stream is parameterized with a flexible neural network,  x   θ (γ). We illustrate this parameterization with the colored curve, color coded by the γ value along the stream. Bottom row: For the same mock stream, we plot the unit-vector trajectories of tracers in the x, y, and z direction (black scatter points). The red curve is our parameterization of these points, taken as the derivative of the colorful curve in the top panel with respect to γ and normalized. The parameterized curves in this figure are generated from a single neural network. Streams are unwrapped using the method described in Appendix A.
Paper: Charting Galactic Accelerations with Stellar Streams and Machine Learning
Authors: Jacob Nibauer, Vasily Belokurov, Miles Cranmer, Jeremy Goodman, Shirley Ho
Figure caption: Flexible potential reconstruction using six stellar streams and their inferred acceleration field, illustrated in Figure 5. Top row: The left panel is the ground-truth potential in a galactocentric frame with z fixed to 5 kpc. The middle panel is the flexible reconstruction, and the right panel illustrates fractional errors. Bottom row: Same as the top row, but for y = −6 kpc.
Paper: Charting Galactic Accelerations with Stellar Streams and Machine Learning
Authors: Jacob Nibauer, Vasily Belokurov, Miles Cranmer, Jeremy Goodman, Shirley Ho
Figure caption: Constraints on model parameters for the logarithmic potential in Equation (15). The parameter constraints are derived from the estimated acceleration field along the six mock streams analyzed in Section 3.2. The contours correspond to regions of 68% and 95% confidence, and gray lines depict the true underlying parameter values.
Paper: Charting Galactic Accelerations with Stellar Streams and Machine Learning
Authors: Jacob Nibauer, Vasily Belokurov, Miles Cranmer, Jeremy Goodman, Shirley Ho
Figure caption: Black scatter points depict the speed of tracer particles for the unwrapped stellar stream illustrated in Figure 3 (top and bottom panels). The red curve is our parameterization of the speed, fit with a neural network v  φ (γ).
Paper: Short GRB Host Galaxies. II. A Legacy Sample of Redshifts, Stellar Population Properties, and Implications for Their Neutron Star Merger Origins
Authors: Anya E. Nugent, Wen-Fai Fong, Yuxin Dong, 雨欣 董, Joel Leja, Edo Berger, Michael Zevin, Ryan Chornock, Bethany E. Cobb, Luke Zoltan Kelley, Charles D. Kilpatrick, Andrew Levan, Raffaella Margutti, Kerry Paterson, Daniel Perley, Alicia Rouco Escorial, Nathan Smith, Nial Tanvir
Figure caption: From left to right, top to bottom: CDFs of all (purple), star-forming (blue), and transitioning and quiescent (pink) short GRB hosts for log(M */M ⊙), t  m  in Gyr, log(SFR) in M ⊙ yr−1, log(Z */Z ⊙), and A  V  in mag. Thick solid lines represent medians on the CDF, while 5000 realizations of the CDF in each distribution are plotted as thin lines to demonstrate the spread in each distribution. The probability distributions of all hosts are shown in the panel above the CDFs. Medians in each distribution are denoted by color-coded arrows from the bottom, and are also denoted in the legend. We find that the median short GRB hosts tend to be massive (∼109–1010 M ⊙), moderately old (∼0.8 Gyr), albeit with large difference in ages between the star-forming and transitioning/quiescent hosts, have moderately low ongoing SFR (∼1.5 M ⊙ yr−1), have a uniform distribution of stellar metallicities, and have low dust attenuation (∼0.4 mag).
Paper: Short GRB Host Galaxies. II. A Legacy Sample of Redshifts, Stellar Population Properties, and Implications for Their Neutron Star Merger Origins
Authors: Anya E. Nugent, Wen-Fai Fong, Yuxin Dong, 雨欣 董, Joel Leja, Edo Berger, Michael Zevin, Ryan Chornock, Bethany E. Cobb, Luke Zoltan Kelley, Charles D. Kilpatrick, Andrew Levan, Raffaella Margutti, Kerry Paterson, Daniel Perley, Alicia Rouco Escorial, Nathan Smith, Nial Tanvir
Figure caption: 3D-HST and COSMOS2015 Prospector derived sSFRs and stellar masses (Brammer et al. 2012; Laigle et al. 2016; Momcheva et al. 2016; Leja et al. 2022) compared to the short GRB host Prospector-derived sSFRs and stellar masses over 0.0 < z < 3.0. The 3D-HST and COSMOS2015 data is plotted as a normalized histogram in gray. We use the definitions of star-forming (blue circles), transitioning (yellow squares), and quiescent (red triangles) galaxies from Tacchella et al. (2022) to plot the short GRB host data. Upper limits are shown as triangles, and hosts with photometric redshifts are shown as white-filled shapes. We also circle the host of GRB 170817 (NGC4993). We plot the broken-power-law SFMS equations derived in Leja et al. (2022) for each redshift bin. Across all redshifts, short GRB hosts track the SFMS well, implying they are good tracers of star formation given their stellar mass. The bottom-right plot shows the star-forming (SF) and quiescent/transitioning (Q/T) fractions of short GRBs in comparison to those of the 3D-HST and COSMOS2015 field galaxies. The short GRB host star-forming and non-star-forming fractions are comparable to the field galaxy’s fraction at all redshifts, with a slight dominance of non-star-forming hosts at z < 0.25.
Paper: Short GRB Host Galaxies. II. A Legacy Sample of Redshifts, Stellar Population Properties, and Implications for Their Neutron Star Merger Origins
Authors: Anya E. Nugent, Wen-Fai Fong, Yuxin Dong, 雨欣 董, Joel Leja, Edo Berger, Michael Zevin, Ryan Chornock, Bethany E. Cobb, Luke Zoltan Kelley, Charles D. Kilpatrick, Andrew Levan, Raffaella Margutti, Kerry Paterson, Daniel Perley, Alicia Rouco Escorial, Nathan Smith, Nial Tanvir
Figure caption: The mass-weighted ages (t  m ) of short GRB hosts normalized by the age of the universe at their redshift (t  H (z)) vs. redshifts, color-coded by their host type (blue is star-forming, yellow is transitioning, and red is quiescent). White-filled symbols are photometric redshifts and single color symbols are spectroscopic redshifts. We find that closer to the epoch of star formation (z = 2), there are more hosts that are much younger than t  H (z). As redshift decreases, we see that the population of hosts begins to be dominated by those with ages closer to t  H (z). This would imply that production of the short GRB progenitors is decreasing with redshift, as the short GRBs found at lower redshifts likely formed closer to the epoch of star formation and have a longer delay time.
Paper: Short GRB Host Galaxies. II. A Legacy Sample of Redshifts, Stellar Population Properties, and Implications for Their Neutron Star Merger Origins
Authors: Anya E. Nugent, Wen-Fai Fong, Yuxin Dong, 雨欣 董, Joel Leja, Edo Berger, Michael Zevin, Ryan Chornock, Bethany E. Cobb, Luke Zoltan Kelley, Charles D. Kilpatrick, Andrew Levan, Raffaella Margutti, Kerry Paterson, Daniel Perley, Alicia Rouco Escorial, Nathan Smith, Nial Tanvir
Figure caption: CDFs of the short GRB host stellar masses (teal) compared to the mass-weighted Schechter function of the COSMOS survey’s active galaxies (orange; Davidzon et al. 2017) across three redshift bins spanning 0 < z < 3.0. For the short GRB host mass distributions, we plot 5000 realizations on the CDF along with the median CDF (teal solid line). The Schechter function is used to represent the luminosity-corrected distribution of normal field galaxy stellar masses. Insets: we determine if the short GRB host and the mass-weighted Schechter functions are drawn from the same underlying distribution through an Anderson–Darling (AD) test, the distribution of P AD values for all realizations. The dashed lines in the insets show P AD  =  0.05, with arrows in the direction of the point below which we reject the null hypothesis that they are drawn from the same underlying mass distribution. Across all redshift bins, we can reject the null hypothesis that short GRB hosts trace the stellar mass distribution in galaxies.
Paper: Short GRB Host Galaxies. II. A Legacy Sample of Redshifts, Stellar Population Properties, and Implications for Their Neutron Star Merger Origins
Authors: Anya E. Nugent, Wen-Fai Fong, Yuxin Dong, 雨欣 董, Joel Leja, Edo Berger, Michael Zevin, Ryan Chornock, Bethany E. Cobb, Luke Zoltan Kelley, Charles D. Kilpatrick, Andrew Levan, Raffaella Margutti, Kerry Paterson, Daniel Perley, Alicia Rouco Escorial, Nathan Smith, Nial Tanvir
Figure caption: From top to bottom: median (star) and 8% confidence interval values (line) for z, t  m , ﹩\mathrm{log}({M}_{* }/{M}_{\odot })﹩, and SFR for the Gold, Silver, and Bronze Samples. There is little difference in the median and 68% confidence interval for the properties in each sample; however, redshift does appear to increase from the Gold to Bronze Samples. Fong et al. (2022) also showed that there are weaker associations to hosts as redshift increases, due to faintness of the galaxies.
Paper: Short GRB Host Galaxies. II. A Legacy Sample of Redshifts, Stellar Population Properties, and Implications for Their Neutron Star Merger Origins
Authors: Anya E. Nugent, Wen-Fai Fong, Yuxin Dong, 雨欣 董, Joel Leja, Edo Berger, Michael Zevin, Ryan Chornock, Bethany E. Cobb, Luke Zoltan Kelley, Charles D. Kilpatrick, Andrew Levan, Raffaella Margutti, Kerry Paterson, Daniel Perley, Alicia Rouco Escorial, Nathan Smith, Nial Tanvir
Figure caption: Stellar masses and mass-weighted ages of short GRB hosts, with the same color and shape schematic as in Figure 8. Hosts with photometric redshifts are represented with white-filled shapes. We mark NGC4993 and the hosts of GRBs 060614 and 211211A for reference. We find that quiescent host galaxies make up the oldest and most-massive hosts in the sample, and that the hosts of short GRBs span nearly the full range of galaxy properties.
Paper: Short GRB Host Galaxies. II. A Legacy Sample of Redshifts, Stellar Population Properties, and Implications for Their Neutron Star Merger Origins
Authors: Anya E. Nugent, Wen-Fai Fong, Yuxin Dong, 雨欣 董, Joel Leja, Edo Berger, Michael Zevin, Ryan Chornock, Bethany E. Cobb, Luke Zoltan Kelley, Charles D. Kilpatrick, Andrew Levan, Raffaella Margutti, Kerry Paterson, Daniel Perley, Alicia Rouco Escorial, Nathan Smith, Nial Tanvir
Figure caption: CDFs of observed physical (left) and host-normalized (right) offsets for star-forming (dark blue) and quiescent/transitioning (red) hosts. The CDFs produced from the Rice distributions are shown in the respective lighter colors for each host star formation classification. We show medians with the arrows and highlight the offset of GRB 170817 with a dashed black line. We find significant differences in physical offsets between the star-forming and non-star-forming hosts, but more similar distributions when looking at the host-normalized offsets. Taken together, this likely implies that short GRB progenitors in non-star-forming galaxies have migrated farther than those in star-forming hosts.
Paper: Short GRB Host Galaxies. II. A Legacy Sample of Redshifts, Stellar Population Properties, and Implications for Their Neutron Star Merger Origins
Authors: Anya E. Nugent, Wen-Fai Fong, Yuxin Dong, 雨欣 董, Joel Leja, Edo Berger, Michael Zevin, Ryan Chornock, Bethany E. Cobb, Luke Zoltan Kelley, Charles D. Kilpatrick, Andrew Levan, Raffaella Margutti, Kerry Paterson, Daniel Perley, Alicia Rouco Escorial, Nathan Smith, Nial Tanvir
Figure caption: The Gallazzi et al. (2005) stellar mass–metallicity relation (MZ; solid black lines represent the median and dashed black lines represent the 68% credible region) overplotted with short GRB hosts. The colors of both the 3D-HST and COSMOS field galaxies (small circles) and the short GRB hosts (large, outlined circles) denote their star formation classification, with blue representing star-forming, yellow representing transitioning, and pink representing quiescent galaxies. The open circles represent photometric redshift hosts. Short GRB hosts follow the MZ relation, fall within the expected range for their star formation classification, and span a wide range of metallicities. We also highlight NGC4993 and the host of GRB 211211A for reference, which occur in very different places in the MZ-plane. Overall, GRB-producing NS mergers form independently of the metallicity of their stellar populations.
Paper: Short GRB Host Galaxies. II. A Legacy Sample of Redshifts, Stellar Population Properties, and Implications for Their Neutron Star Merger Origins
Authors: Anya E. Nugent, Wen-Fai Fong, Yuxin Dong, 雨欣 董, Joel Leja, Edo Berger, Michael Zevin, Ryan Chornock, Bethany E. Cobb, Luke Zoltan Kelley, Charles D. Kilpatrick, Andrew Levan, Raffaella Margutti, Kerry Paterson, Daniel Perley, Alicia Rouco Escorial, Nathan Smith, Nial Tanvir
Figure caption: The T 90 and fluences of short GRBs, marked by the star formation classification of their hosts. We see that all types of hosts (star-forming, transitioning, and quiescent) span the full ranges, implying that host type does not influence these GRB properties. Short GRBs in quiescent hosts, however, do tend to have the lowest fluences. We mark GRBs 060614, 170817, and 211211A for reference.
Paper: Recipe for Inferring Subsurface Solar Magnetism via Local Mode Coupling Using Slepian Basis Functions
Authors: Srijan Bharati Das
Figure caption: Top panel: (A) same as the left panel in Figure 6 of Birch et al. (2019) showing ∇ ·  v   h  maps from the average of 57 emerging active regions 13.5 hr prior to emergence. (B) The corresponding reconstructed map using 27 Slepian functions. Similar to the nomenclature adopted in Figure 2, panel (AmB) indicates the difference between the map in (A) and that in (B). Bottom panel: the two lower panels show the first 16 basis functions and the concentration of energy in the spectral domain given by ﹩{\sum }_{\alpha =1}^{27}{\lambda }_{\alpha }\,{G}_{\alpha }^{2}({\boldsymbol{q}})﹩, in logarithmic scale. These basis functions’ subplots share the same x-, y-axes in units of Mm as that in panel (A). The physical space contour ﹩{ \mathcal R }﹩ is denoted by the closed black dashed curve, and the spectral space contour ﹩{ \mathcal Q }﹩ is denoted by the red circle.
Paper: Dynamical Masses of the Primary Be Star and Secondary sdB Star in the Single-lined Binary κ Dra (B6 IIIe)
Authors: Robert Klement, Dietrich Baade, Thomas Rivinius, Douglas R. Gies, Luqian Wang, Jonathan Labadie-Bartz, Pedro Ticiani dos Santos, John D. Monnier, Alex C. Carciofi, Antoine Mérand, Narsireddy Anugu, Gail H. Schaefer, Jean-Baptiste Le Bouquin, Claire L. Davies, Jacob Ennis, Tyler Gardner, Stefan Kraus, Benjamin R. Setterholm, Aaron Labdon
Figure caption: Flux-calibrated spectrophotometry of κ Dra overplotted in gray with a reddened (E(B − V) = 0.022 and R  V  = 3.1) Kurucz model spectrum representing the primary Be star (T eff = 13,982 kK, ﹩\mathrm{log}g=3.479﹩, R = 5.85 R ⊙, d = 142.7 pc). The mid-IR power-law slope of the IR excess from the circumstellar disk (typical for Be stars) is shown as a dotted gray line. The reddened model spectrum for the sdB companion (T eff = 16.7 kK, R = 0.69 R ⊙) renormalized to the measured flux in the H band (neglecting the possible contribution from the dissipating disk; see text) is shown in purple. The FUV flux ratio of 2.3% ± 0.5% determined from FUV spectra is shown as two dashed black horizontal lines signifying the edges of the derived confidence interval. From short to long wavelengths, the gray vertical bands indicate the FUV region, near-IR H band, and K band, respectively.
Paper: Dynamical Masses of the Primary Be Star and Secondary sdB Star in the Single-lined Binary κ Dra (B6 IIIe)
Authors: Robert Klement, Dietrich Baade, Thomas Rivinius, Douglas R. Gies, Luqian Wang, Jonathan Labadie-Bartz, Pedro Ticiani dos Santos, John D. Monnier, Alex C. Carciofi, Antoine Mérand, Narsireddy Anugu, Gail H. Schaefer, Jean-Baptiste Le Bouquin, Claire L. Davies, Jacob Ennis, Tyler Gardner, Stefan Kraus, Benjamin R. Setterholm, Aaron Labdon
Figure caption: Tomographic reconstructions of the CCFs for the Be star (PRI) and companion (SEC). The amplitude of the Be star CCF is reduced by a factor of 20 and offset by 0.005 for ease of comparison with the companion star CCF component. The signal from the companion is seen at a similar systemic velocity as the Be star (heliocentric frame), appears much narrower, and corresponds to a companion with a flux ratio of 2.3% ± 0.5% for the FUV range centered on 1500 Å.
Paper: Recipe for Inferring Subsurface Solar Magnetism via Local Mode Coupling Using Slepian Basis Functions
Authors: Srijan Bharati Das
Figure caption: Plot showing the λ  α  for the eigenfunctions used in the emerging active region demonstration in Figure 4. The red line indicates α = 27, which is used as the Shannon number N2D to calculate the effective number of eigenfunctions that are optimally concentrated within ﹩{ \mathcal R }﹩.
Paper: Dynamical Masses of the Primary Be Star and Secondary sdB Star in the Single-lined Binary κ Dra (B6 IIIe)
Authors: Robert Klement, Dietrich Baade, Thomas Rivinius, Douglas R. Gies, Luqian Wang, Jonathan Labadie-Bartz, Pedro Ticiani dos Santos, John D. Monnier, Alex C. Carciofi, Antoine Mérand, Narsireddy Anugu, Gail H. Schaefer, Jean-Baptiste Le Bouquin, Claire L. Davies, Jacob Ennis, Tyler Gardner, Stefan Kraus, Benjamin R. Setterholm, Aaron Labdon
Figure caption: Top: Hα line profiles recovered from the BeSS spectral database. The colors correspond to dates as shown in the bottom panel. Bottom: equivalent width (EW) measured for all Hα profiles. A continuous decrease in emission strength is apparent from around 2010 and still ongoing. Vertical lines show the epochs of our interferometric observations.