adsabs/AstroCLIMB huggingface dataset:
Paper: A Catalog of Nearby Accelerating Star Candidates in Gaia DR3
Authors: Marc L. Whiting, Joshua B. Hill, Benjamin C. Bromley, Scott J. Kenyon
Figure caption: The CMD from the HGCA. The left panel is the full catalog from Brandt (2021) with 115,346 stars. As described in the text, we search for counterparts in the Gaia DR2 catalog and find matches for all but 186 sources. The right panel shows the CMD for the reduced HGCA catalog containing only accelerating stars with χ 2 ≥ 28.75 that have crossmatches in DR2 and EDR3. The distributions of spectral types within the full catalog and the subset of accelerating stars are similar; however, no significant acceleration is attributed to white dwarfs (lower left in the left CMD, near [11, −0.2]). Given that roughly a third of the stars show motion inconsistent with linear drift, there may also be a dearth of accelerating hot subdwarfs (the cluster of stars near [4, −0.3] in the right CMD, as compared to the same region in the left panel).
Paper: A Catalog of Nearby Accelerating Star Candidates in Gaia DR3
Authors: Marc L. Whiting, Joshua B. Hill, Benjamin C. Bromley, Scott J. Kenyon
Figure caption: The ruwe of sources in the GNASC vs. the predicted χ 2 testing the null hypothesis for stellar acceleration. The horizontal dashed line is at a value of ruwe = 1.3, which nominally delimits binary sources (above the line) and single sources (below) in the Gaia data. The left and right panels are for the full catalog and for only those stars with a neighbor inside of 200 au identified in the Gaia archive. The contours are at containment thresholds of 5%, 20%, 50%, 80%, and 95%.
Paper: A Catalog of Nearby Accelerating Star Candidates in Gaia DR3
Authors: Marc L. Whiting, Joshua B. Hill, Benjamin C. Bromley, Scott J. Kenyon
Figure caption: The ruwe from Gaia EDR3 vs. the χ 2 value testing the hypothesis in the HGCA. The horizontal dashed line is at a value of ruwe = 1.3, which nominally delimits binary sources (above the line) and single sources (below) in the Gaia data. The vertical dotted line is at a value of 28.75, marking 5σ outliers in the distribution of χ 2 values.
Paper: A Catalog of Nearby Accelerating Star Candidates in Gaia DR3
Authors: Marc L. Whiting, Joshua B. Hill, Benjamin C. Bromley, Scott J. Kenyon
Figure caption: The ruwe vs. the predicted χ 2 for binaries in the GNASC, similar to Figure 5. The gold “x” symbols mark the 139 binaries that appear in the SIMBAD Astronomical Database, while the light cyan circles are the 172 new binaries in our catalog. Each pair is connected with a thin line. The overall distributions of both known and new binaries are similar to each other and to the underlying distribution of all sources in the catalog (light gray points in the background). Notably, seven pairs lie below the 1.3 ruwe threshold for binarity.
Paper: Planetary Parameters, XUV Environments, and Mass-loss Rates for Nearby Gaseous Planets with X-Ray-detected Host Stars
Authors: Riccardo Spinelli, Elena Gallo, Francesco Haardt, Andrea Caldiroli, Federico Biassoni, Francesco Borsa, Emily Rauscher
Figure caption: K-reduced mass outflow rates obtained with ATES, plotted as a function of the ratio of planetary density to irradiation (F EUV/ρ  p ) for the planet sample under consideration. The parameter K accounts for the star contribution to the gravitational potential experienced by the atmosphere. For those cases that were also considered by S16, we compare the outflow rates derived with the new (GDR2) planetary parameters (color symbols) to those derived based on the “old” values (black circles). Systems with two symbols represent those whose host star exhibits X-ray variability.
Paper: Planetary Parameters, XUV Environments, and Mass-loss Rates for Nearby Gaseous Planets with X-Ray-detected Host Stars
Authors: Riccardo Spinelli, Elena Gallo, Francesco Haardt, Andrea Caldiroli, Federico Biassoni, Francesco Borsa, Emily Rauscher
Figure caption: Ratio of stellar X-ray to bolometric luminosity as a function of Rossby number, adapted from Wright et al. (2018). The full sample of Wright et al. (2018) is shown in gray, with their best-fitting relation in blue, while the black circles/triangles refer to our target sample (triangles indicate upper limits). The red segments connect different measurements in the case of X-ray variable stars.
Paper: Planetary Parameters, XUV Environments, and Mass-loss Rates for Nearby Gaseous Planets with X-Ray-detected Host Stars
Authors: Riccardo Spinelli, Elena Gallo, Francesco Haardt, Andrea Caldiroli, Federico Biassoni, Francesco Borsa, Emily Rauscher
Figure caption: EPIC-pn and ACIS-S (binned) X-ray spectra for the X-ray-detected FKG-type host stars. Count rates are shown in blue/red with error bars; the green/orange histograms represent the best-fit (one-, two-, or three-temperature) APEC model. For targets with multiple epochs and significant variability we show the highest and the lower flux cases.
Paper: Planetary Parameters, XUV Environments, and Mass-loss Rates for Nearby Gaseous Planets with X-Ray-detected Host Stars
Authors: Riccardo Spinelli, Elena Gallo, Francesco Haardt, Andrea Caldiroli, Federico Biassoni, Francesco Borsa, Emily Rauscher
Figure caption: Revised masses and radii (in Jovian units) for the planet sample under consideration are shown as large symbols and compared against the values reported in the exoplanet.eu catalog, shown as smaller symbols.
Paper: Planetary Parameters, XUV Environments, and Mass-loss Rates for Nearby Gaseous Planets with X-Ray-detected Host Stars
Authors: Riccardo Spinelli, Elena Gallo, Francesco Haardt, Andrea Caldiroli, Federico Biassoni, Francesco Borsa, Emily Rauscher
Figure caption: Revised densities for the planet sample under consideration as a function of the Gaia DR2 distances. When applicable, these are compared to the values adopted by S16 (black circles). The gray circles in the background illustrate all the known planets within 150 pc.
Paper: Planetary Parameters, XUV Environments, and Mass-loss Rates for Nearby Gaseous Planets with X-Ray-detected Host Stars
Authors: Riccardo Spinelli, Elena Gallo, Francesco Haardt, Andrea Caldiroli, Federico Biassoni, Francesco Borsa, Emily Rauscher
Figure caption: Same as Figure 1, but for M-type hosts.
Paper: Planet Eclipse Mapping with Long-term Baseline Drifts
Authors: Everett Schlawin, Ryan Challener, Megan Mansfield, Emily Rauscher, Arthur Adams, Jacob Lustig-Yaeger
Figure caption: Forward lightcurve models and simulated data with 6 ppm per minute precision for an idealized planet (left) and 31 ppm per minute precision for HD 189733 b (right). The simulated lightcurves with a flat baseline trend (other than the astrophysical variations from the rotation of the planet) are shown with light brown data points. It is assumed that the planet is observed only near eclipse but with sufficient baseline prior to ingress and following egress for baseline characterization. We add a cubic polynomial trend (left) and a quadratic polynomial trend (right) that could be caused by instrument artifacts or astrophysical variability (dark brown points) to understand which aspects of the recovered maps are affected by nonflat baseline trends.
Paper: Planet Eclipse Mapping with Long-term Baseline Drifts
Authors: Everett Schlawin, Ryan Challener, Megan Mansfield, Emily Rauscher, Arthur Adams, Jacob Lustig-Yaeger
Figure caption: Posterior lightcurves for the nonflat baselines, separated into the full Gaussian-process model (orange shaded region) and the astrophysical component (gray shaded region). The simulated data as well as the residuals are shown in dark brown. For both the idealized planet (left) and the JWST NIRCam HD 189733 b simulation (right), the model uncertainty grows during ingress and egress due to the map uncertainty and the fact that some mapping components only exhibit variations during eclipse. Different maps create a range of astrophysical lightcurves and these lightcurves (encompassed in the gray region) also have a range of astrophysical baselines that grow increasingly uncertain away from mideclipse. These astrophysical lightcurves can appear similar to systematic baseline trends, but are constrained more by the ingress/egress signatures of the maps.
Paper: Planet Eclipse Mapping with Long-term Baseline Drifts
Authors: Everett Schlawin, Ryan Challener, Megan Mansfield, Emily Rauscher, Arthur Adams, Jacob Lustig-Yaeger
Figure caption: The spherical harmonic maps (top) and lightcurves (bottom) are shown up to degree 3. The three terms most affected by baseline trends (Y 1,1, Y 2,1, and Y 3,1) are highlighted. The baseline primarily affects the horizontal distribution of the planet. While the Y 1,1 and Y 2,1 terms have strong linear baselines, the Y 3,1 spherical harmonic lightcurve correlates strongly with Y 1,1 and Y 2,1 as shown in Figure 6.
Paper: Planet Eclipse Mapping with Long-term Baseline Drifts
Authors: Everett Schlawin, Ryan Challener, Megan Mansfield, Emily Rauscher, Arthur Adams, Jacob Lustig-Yaeger
Figure caption: Top: as in Figure 3, the arbitrary forward map is shown with the location of the peak brightness as a blue circle. Middle: starry map mean and uncertainty for the HD 189733 b where the baseline is flat showing low errors (less than 25% along the equator and the best constraint at the substellar point). Bottom: starry map mean and uncertainty for HD 189733 b where the lightcurve has a quadratic polynomial trend, which decreases the precisions at the eastern and western limbs. As in Figure 3, we show the locations of peak brightness for individual map draws as black points and the location of peak brightness of the mean map as a plus symbol.
Paper: Planet Eclipse Mapping with Long-term Baseline Drifts
Authors: Everett Schlawin, Ryan Challener, Megan Mansfield, Emily Rauscher, Arthur Adams, Jacob Lustig-Yaeger
Figure caption: Posterior distributions for all mapping variables and the lightcurve standard deviation. The posteriors for a flat baseline are shown in light brown whereas the posteriors with a baseline trend are shown in dark brown while the inputs for the forward model are shown as blue vertical dashed lines. At the lower signal to noise used for this JWST HD 189733 b simulation compared to the ideal case shown in Figure 4, the BIC favors a second degree spherical harmonic, but the results are similar to the idealized planet. The m = 1 spherical harmonics significantly lower precision constraints when there is a baseline trend fit with a Gaussian process model.
Paper: Planet Eclipse Mapping with Long-term Baseline Drifts
Authors: Everett Schlawin, Ryan Challener, Megan Mansfield, Emily Rauscher, Arthur Adams, Jacob Lustig-Yaeger
Figure caption: Top: arbitrary forward-map model for the HD 189733 b, the same shown in Figure 7. Middle: starry map mean, uncertainty and residuals for HD 189733 b where the model has no Gaussian process or polynomial component and attempts to fit the baseline trends with planet map components only and thus has an incorrect map. Bottom: the posterior lightcurve and residuals are most noticeable during eclipse where the lightcurve should be flat, thus indicating that a baseline model such as a Gaussian process or polynomial is favored in fitting the lightcurve, as also revealed by the two BICs of 686.1 in Figure 5 (right) and 824 in this figure.
Paper: Planet Eclipse Mapping with Long-term Baseline Drifts
Authors: Everett Schlawin, Ryan Challener, Megan Mansfield, Emily Rauscher, Arthur Adams, Jacob Lustig-Yaeger
Figure caption: Top: arbitrary map model for the hot Jupiter planet, which is actually from an Earth map up to spherical harmonic degree 3 just to provide complicated structures. The location of peak brightness is shown with a blue circle. Middle: starry map mean, uncertainty, and residuals for the idealized planet where the baseline is flat. Bottom: starry map mean, uncertainty and residuals for the idealized planet where the lightcurve has a cubic polynomial trend. Black points show the locations of peak brightness for individual map samples drawn from the posterior and the green plus shows the peak brightness Gaussian fit centroid to the mean map. The added baseline does not significantly affect the mean or error map, but does affect the precision of the peak brightness location as well as the residuals.
Paper: Planet Eclipse Mapping with Long-term Baseline Drifts
Authors: Everett Schlawin, Ryan Challener, Megan Mansfield, Emily Rauscher, Arthur Adams, Jacob Lustig-Yaeger
Figure caption: Posterior distributions for all mapping variables and the lightcurve standard deviation. The posteriors for a flat baseline are shown in light brown, the posteriors with a baseline trend are shown in dark brown, and the inputs for the forward model are shown as blue vertical dashed lines. The most-affected parameters are the m = 1 spherical harmonics. The amplitude, shown in the top, is the integrated flux of the planet over 4π compared to the integrated flux of the star, with units in percentage. The lightcurve error is in units of ppm and the spherical harmonic coefficients are unitless because they are ratios to the Y 0,0 term.
Paper: Planet Eclipse Mapping with Long-term Baseline Drifts
Authors: Everett Schlawin, Ryan Challener, Megan Mansfield, Emily Rauscher, Arthur Adams, Jacob Lustig-Yaeger
Figure caption: Posterior distributions for the four model parameters most affected by the baseline trend for the idealized planet lightcurve shown in Figure 1. The Y 1,1, Y 2,1, and Y 3,1 terms are highly correlated, so uncertainty in Y 1,1 and Y 2,1 from the baseline trend also increases the uncertainty in Y 3,1 for the case where there is a baseline trend (dark brown). A lightcurve with no baseline trend and pure-astrophysical signal (light brown posteriors) gives much tighter constraints.
Paper: Planet Eclipse Mapping with Long-term Baseline Drifts
Authors: Everett Schlawin, Ryan Challener, Megan Mansfield, Emily Rauscher, Arthur Adams, Jacob Lustig-Yaeger
Figure caption: Eigenmap components (left) of the best-fitting ThERESA model when using a quadratic baseline and their associated eigencurves (right). The eigenmaps are normalized to highlight differences in structure, with the best-fitting coefficients listed with the corresponding eigenmaps. The vertical black lines denote the range of longitudes visible during the observation.
Paper: Planet Eclipse Mapping with Long-term Baseline Drifts
Authors: Everett Schlawin, Ryan Challener, Megan Mansfield, Emily Rauscher, Arthur Adams, Jacob Lustig-Yaeger
Figure caption: Each curve shows the variation during the eclipse lightcurve due to one spherical harmonic component if the integrated flux of the planet with that spherical harmonic component was 0.001 times the integrated flux of the star. We selected impact parameters with b > 0.5 in order to have significant contributions from the latitudinal terms Y 1,−1, Y 2,−1 and Y 2,−2.
Paper: Planet Eclipse Mapping with Long-term Baseline Drifts
Authors: Everett Schlawin, Ryan Challener, Megan Mansfield, Emily Rauscher, Arthur Adams, Jacob Lustig-Yaeger
Figure caption: Top: forward-map model calculated from a GCM for HD 189733 b. Middle: starry map mean, uncertainty and residuals for HD 189733 b where the baseline is flat. Bottom: starry map mean, uncertainty and residuals for HD 189733 b with a cubic polynomial added to the forward model and then fit with a Gaussian process.
Paper: Planet Eclipse Mapping with Long-term Baseline Drifts
Authors: Everett Schlawin, Ryan Challener, Megan Mansfield, Emily Rauscher, Arthur Adams, Jacob Lustig-Yaeger
Figure caption: Posterior distributions for all mapping variables and the lightcurve standard deviation for a GCM forward map. Results are similar to Figure 8, where a different forward map was used.
Paper: Planet Eclipse Mapping with Long-term Baseline Drifts
Authors: Everett Schlawin, Ryan Challener, Megan Mansfield, Emily Rauscher, Arthur Adams, Jacob Lustig-Yaeger
Figure caption: Best-fitting maps using ThERESA (Challener & Rauscher 2022) with different baseline models. We have restricted the x-axis to only show longitudes visible during the observation (−106.°2–106.°2). Note the different scales on the colorbars.
Paper: Detailed Chemical Abundances of Stars in the Outskirts of the Tucana II Ultrafaint Dwarf Galaxy 
Authors: Anirudh Chiti, Anna Frebel, Alexander P. Ji, Mohammad K. Mardini, Xiaowei Ou, Joshua D. Simon, Helmut Jerjen, Dongwon Kim, John E. Norris
Figure caption: [X/Fe] vs. [Fe/H] trends for stars in our Tucana II sample (large blue squares), stars in the inner region of Tucana II (red squares), and other UFDs (brown circles) for carbon, odd-Z elements (Na, Al, Sc), α-elements (Mg, Si, Ca, Ti), and Cr. The Ret II and Segue 1 UFDs are shown as red circles and orange circles, respectively, due to their interesting chemical signatures (e.g., exceptional r-process enhancement in Ret II, and a flat α-element abundance trend in Segue 1). The gray data points correspond to abundances for MW halo stars from the compilation of Abohalima & Frebel (2018). The abundances largely follow the overall UFD trends, with the exception of a low Ca abundance for the most metal-poor star in the system and a low Mg and Sc abundance in the most metal-rich star in the system. UFD chemical abundance data are from Koch et al. (2008), Feltzing et al. (2009), Norris et al. (2010a), Norris et al. (2010b), Simon et al. (2010), Frebel et al. (2010), Lai et al. (2011), Gilmore et al. (2013), Koch et al. (2013), Frebel et al. (2014), Ishigaki et al. (2014a), Roederer & Kirby (2014), François et al. (2016), Ji et al. (2016c), Frebel et al. (2016), Ji et al. (2016c), Roederer et al. (2016), Hansen et al. (2017), Kirby et al. (2017), Chiti et al. (2018a), Nagasawa et al. (2018), Spite et al. (2018), Ji et al. (2019), Marshall et al. (2019), Hansen et al. (2020), and Ji et al. (2020b).
Paper: Detailed Chemical Abundances of Stars in the Outskirts of the Tucana II Ultrafaint Dwarf Galaxy 
Authors: Anirudh Chiti, Anna Frebel, Alexander P. Ji, Mohammad K. Mardini, Xiaowei Ou, Joshua D. Simon, Helmut Jerjen, Dongwon Kim, John E. Norris
Figure caption: [X/Fe] vs. [Fe/H] trends of stars in our Tucana II sample (large blue circles), stars in the inner region of Tucana II (red circles), and other UFDs for the iron-peak elements Mn, Co, and Ni and the neutron-capture elements Sr, Ba, and Eu. The UFD data are plotted with the same legend as in Figure 3. Our newly characterized Tucana II stars show deficiency in Sr and Ba abundances, as is typical for UFD stars, confirming their association with the system. The iron-peak abundances largely follow trends seen in other UFDs and the MW halo, except for the most metal-rich Tucana II star that appears to be deficient in Mn.
Paper: Detailed Chemical Abundances of Stars in the Outskirts of the Tucana II Ultrafaint Dwarf Galaxy 
Authors: Anirudh Chiti, Anna Frebel, Alexander P. Ji, Mohammad K. Mardini, Xiaowei Ou, Joshua D. Simon, Helmut Jerjen, Dongwon Kim, John E. Norris
Figure caption: Left: color–magnitude diagram of stars in the Tucana II UFD. Blue circles correspond to stars observed with high-resolution spectroscopy presented in this work; green squares correspond to stars with high-resolution spectroscopy presented in previous works (Ji et al. 2016b; Chiti et al. 2018a); black circles correspond to stars with no high-resolution spectroscopy (Walker et al. 2016; Chiti et al. 2021). A MIST isochrone of 10 Gyr and [Fe/H] = −2.2 (Paxton et al. 2011, 2013, 2015; Choi et al. 2016; Dotter 2016; Paxton et al. 2018) is overplotted at the distance modulus of Tucana II (m − M = 18.8; Bechtol et al. 2015), for reference. Each star observed in this study is labeled by its identifier in Table 1. Right: spatial location of stars with respect to the center of Tucana II. Dashed circles correspond to 1, 3, and 5 times the half-light radius as presented in Bechtol et al. (2015).
Paper: Detailed Chemical Abundances of Stars in the Outskirts of the Tucana II Ultrafaint Dwarf Galaxy 
Authors: Anirudh Chiti, Anna Frebel, Alexander P. Ji, Mohammad K. Mardini, Xiaowei Ou, Joshua D. Simon, Helmut Jerjen, Dongwon Kim, John E. Norris
Figure caption: Top panel: abundance pattern of TucII-305 (red squares) with the best-fitting SN yield model (blue) and other SN yield models within 2σ of the best-fitting χ 2 value (gray) overplotted. The best-fitting progenitor SN is low mass (∼11 M ⊙) and low energy (E ∼ 0.3 × 1051 ergs), though the abundances are consistent with a broad range of acceptable parameters. Bottom left panel: distribution of the progenitor masses of consistent models. While there is a preference for low masses, the range of acceptable masses does extend to the high-mass regime. Bottom right panel: dilution mass vs. explosion energy of the models with the best-fitting model shown in blue. The red dashed line indicates the minimum dilution mass for the given SN energy (see Section 5.2 in Ji et al. 2020b); models below this line are excluded.
Paper: Detailed Chemical Abundances of Stars in the Outskirts of the Tucana II Ultrafaint Dwarf Galaxy 
Authors: Anirudh Chiti, Anna Frebel, Alexander P. Ji, Mohammad K. Mardini, Xiaowei Ou, Joshua D. Simon, Helmut Jerjen, Dongwon Kim, John E. Norris
Figure caption: Top panel: spectrum of TucII-309 (black line) around the Mn λ4030.7 absorption feature, with synthetic spectra at [Mn/Fe] = −1.5, −1.0, and −0.5 overlaid along with a reference MIKE spectrum of the metal-poor halo star 2MASS J00011195+0321051 (purple) from Ezzeddine et al. (2020). 2MASS J00011195+0321051 has similar stellar parameters (T eff = 4909 K, ﹩\mathrm{log}\,g﹩ = 1.75, v micro = 1.85, [Fe/H] = −1.99; Ezzeddine et al. 2020) to TucII-309 but a [Mn/Fe] = −0.36, in line with the halo trend (see Figure 4). Bottom panel: same as the top panel, but around the Mn λ4754 absorption feature. The 2MASS J00011195+0321051 Mn λ4754 absorption feature is clearly visible, but the feature is not detected in TucII-309, demonstrating the low Mn abundance of TucII-309. Note that the Mn abundance from the λ4754 feature in Ezzeddine et al. (2020) for 2MASS J00011195+0321051 is [Mg/H] = −2.51, consistent with the above synthesis.
Paper: Detailed Chemical Abundances of Stars in the Outskirts of the Tucana II Ultrafaint Dwarf Galaxy 
Authors: Anirudh Chiti, Anna Frebel, Alexander P. Ji, Mohammad K. Mardini, Xiaowei Ou, Joshua D. Simon, Helmut Jerjen, Dongwon Kim, John E. Norris
Figure caption: Left: spatial location of members of Tucana II with respect to the center of Tucana II. Stars are colored by their heliocentric radial velocity measurements, as presented in Walker et al. (2016), Chiti et al. (2021), and this study; stars that show evidence of binarity (TucII-078 and TucII-309; see Section 3.1) are displayed as black squares. The arrow corresponds to the axis defined by the angle (θ 1) along which the most distant member lies. The green arrow denotes the direction of Tucana II orbit from Chiti et al. (2021). Right: heliocentric radial velocities of Tucana II members as a function of projected distance along the axis on which the most distant member lies. We find no evidence of a radial velocity gradient along this axis, deriving a slope of ﹩{{dv}}_{\mathrm{helio}}/d{\theta }_{1}\,=\,-{2.5}_{-2.9}^{+2.9}﹩ km s−1 deg−1.
Paper: Detailed Chemical Abundances of Stars in the Outskirts of the Tucana II Ultrafaint Dwarf Galaxy 
Authors: Anirudh Chiti, Anna Frebel, Alexander P. Ji, Mohammad K. Mardini, Xiaowei Ou, Joshua D. Simon, Helmut Jerjen, Dongwon Kim, John E. Norris
Figure caption: Left: [C/Fe] of Tucana II stars as a function of their distance from the center of the UFD. Right: [Mg/Fe] of Tucana II stars as a function of their distance from the center of the UFD. The spatial distributions of both of these abundances do not show strong statistical evidence for spatial correlations (see Sections 4.1 and 4.2).