adsabs/AstroCLIMB huggingface dataset:
Paper: Be Star Demographics: A Comprehensive Study of Thousands of Light Curves in the Magellanic Clouds
Authors: André Luiz Figueiredo, Alex C. Carciofi, Jonathan Labadie-Bartz, Matheus L. Pinho, Tajan H. de Amorim, Pedro Ticiani dos Santos, Igor Soszyński, Andrzej Udalski
Figure caption: Same as Figure 8, but for the DC (left panel) and DDC (right panel).
Paper: Be Star Demographics: A Comprehensive Study of Thousands of Light Curves in the Magellanic Clouds
Authors: André Luiz Figueiredo, Alex C. Carciofi, Jonathan Labadie-Bartz, Matheus L. Pinho, Tajan H. de Amorim, Pedro Ticiani dos Santos, Igor Soszyński, Andrzej Udalski
Figure caption: Scatter plot showing the correlation between buildup and dissipation times for the LMC (purple symbols) and SMC (yellow symbols). Shown are data extracted by fitting Equations (5) and (6) to each disk event. The respective median values are represented by dotted lines. A power-law fit for each distribution is shown as dashed–dotted lines with the same color above, while the identity line is shown in red. In the upper and right parts of the figure are the histograms for buildup and dissipation times, respectively. In the upper-right part of the plot, the number of events is shown, as well as the Pearson coefficients.
Paper: Be Star Demographics: A Comprehensive Study of Thousands of Light Curves in the Magellanic Clouds
Authors: André Luiz Figueiredo, Alex C. Carciofi, Jonathan Labadie-Bartz, Matheus L. Pinho, Tajan H. de Amorim, Pedro Ticiani dos Santos, Igor Soszyński, Andrzej Udalski
Figure caption: Same as Figure 12, but for the photometric amplitudes (upper panel), buildup and dissipation times (second and third panels), and the total duration of the disk event, in the bottom part.
Paper: X-Ray Polarimetry in the Low-statistics Regime Using the Bayesian Approach Reveals Polarization Angle Variations
Authors: Hong Li, Qing-Chang Zhao, Hua Feng, Lian Tao, Sergey S. Tsygankov
Figure caption: Examples of bivariate posterior distributions of (p0, Ψ0 − Ψm) at different pm and MDPs. The contours represent the 68%, 90%, and 99% confidence levels. A modulation factor μ = 0.3 is assumed.
Paper: X-Ray Polarimetry in the Low-statistics Regime Using the Bayesian Approach Reveals Polarization Angle Variations
Authors: Hong Li, Qing-Chang Zhao, Hua Feng, Lian Tao, Sergey S. Tsygankov
Figure caption: Credibility intervals of p0 and Ψ0 at different confidence levels (similar to Figures 11 and 12 in D. Maier et al. 2014). The dashed lines in the bottom panel represent the corresponding PA uncertainties assuming Gaussianization in the high-statistics regime (F. Kislat et al. 2015).
Paper: Be Star Demographics: A Comprehensive Study of Thousands of Light Curves in the Magellanic Clouds
Authors: André Luiz Figueiredo, Alex C. Carciofi, Jonathan Labadie-Bartz, Matheus L. Pinho, Tajan H. de Amorim, Pedro Ticiani dos Santos, Igor Soszyński, Andrzej Udalski
Figure caption: Rms measure from baseline phases of group 2 and 3 stars as a function of their respective median absolute brightness value. Left: LMC. Right: SMC. The black line shows the third-degree polynomial fit, with respective parameters shown in the upper part of each panel.
Paper: X-Ray Polarimetry in the Low-statistics Regime Using the Bayesian Approach Reveals Polarization Angle Variations
Authors: Hong Li, Qing-Chang Zhao, Hua Feng, Lian Tao, Sergey S. Tsygankov
Figure caption: Posterior distributions of p0/MDP (similar to Figure 9 in D. Maier et al. 2014) and Ψ0 at different low statistical levels, with pm/MDP =  0.2, 0.4, 0.6, and 0.8.
Paper: Be Star Demographics: A Comprehensive Study of Thousands of Light Curves in the Magellanic Clouds
Authors: André Luiz Figueiredo, Alex C. Carciofi, Jonathan Labadie-Bartz, Matheus L. Pinho, Tajan H. de Amorim, Pedro Ticiani dos Santos, Igor Soszyński, Andrzej Udalski
Figure caption: Same as Figure 4, but for Σ0 = 1.67 (top left), 0.69 (top right), 0.29 (bottom left), and 0.12 g cm−2 (bottom right).
Paper: Four Elements to Rule Them All: Abundances Are Rigidly Coupled in the Milky Way Disk
Authors: Jennifer Mead, Rebeca De La Garza Evia, Melissa K. Ness
Figure caption: Fiducial model predictions on the B18 data, colored by [Fe/H]. The blue dashed line in each plot indicates the value for a model that perfectly predicts the data, with the gray dashed line denoting the 1σ spread in model residuals. Inferred values with model residuals greater than 3σ are outlined in red.
Paper: X-Ray Polarimetry in the Low-statistics Regime Using the Bayesian Approach Reveals Polarization Angle Variations
Authors: Hong Li, Qing-Chang Zhao, Hua Feng, Lian Tao, Sergey S. Tsygankov
Figure caption: Temporal variation of polarization properties and source count rate in the three IXPE observations of GX 13+1. Error bars indicate the 68% credible intervals. Filled points indicate pm/MDP ≥ 1. In Obs1, the green data points are calculated using the binning scheme in A. Bobrikova et al. (2024b). The blue lines represent the three best-fit models: constant (solid), linear (dotted), and bimodal (dashed).
Paper: Four Elements to Rule Them All: Abundances Are Rigidly Coupled in the Milky Way Disk
Authors: Jennifer Mead, Rebeca De La Garza Evia, Melissa K. Ness
Figure caption: Fiducial model predictions on the B14 and B16 data, colored by [Fe/H]. The blue dashed line in each plot indicates the value for a model that perfectly predicts the data, with the gray dashed line denoting the 1σ spread in model residuals. Inferred values with model residuals greater than 3σ are outlined in red.
Paper: X-Ray Polarimetry in the Low-statistics Regime Using the Bayesian Approach Reveals Polarization Angle Variations
Authors: Hong Li, Qing-Chang Zhao, Hua Feng, Lian Tao, Sergey S. Tsygankov
Figure caption: PA variation as a function of source count rate for Sco X-1. The source flux is quoted in 2–8 keV, while the polarization is calculated in 3.5–8 keV. The gray line and shaded region represent the time-averaged IXPE result (F. La Monaca et al. 2024), and the yellow line and shaded region represent the PolarLight measurement (X. Long et al. 2022). Error bars indicate the 68% credible intervals. Filled points indicate pm/MDP ≥ 1.
Paper: Four Elements to Rule Them All: Abundances Are Rigidly Coupled in the Milky Way Disk
Authors: Jennifer Mead, Rebeca De La Garza Evia, Melissa K. Ness
Figure caption: [X/H] vs. [Fe/H] for elements in B14 and B16, colored by Teff. The average error bars on [X/H] are show in the lower right of each plot.
Paper: X-Ray Polarimetry in the Low-statistics Regime Using the Bayesian Approach Reveals Polarization Angle Variations
Authors: Hong Li, Qing-Chang Zhao, Hua Feng, Lian Tao, Sergey S. Tsygankov
Figure caption: Temporal variation of polarization properties and source count rate in the two IXPE observations of XTE J1701−462, in the same format as in Figure 4. Error bars indicate the 68% credible intervals. Filled points indicate pm/MDP ≥ 1.
Paper: X-Ray Polarimetry in the Low-statistics Regime Using the Bayesian Approach Reveals Polarization Angle Variations
Authors: Hong Li, Qing-Chang Zhao, Hua Feng, Lian Tao, Sergey S. Tsygankov
Figure caption: Energy spectra of GX 13+1 in the two states with different PAs, where PA1 ≈ −43° and PA2 ≈ 26°. Only the IXPE DU1 data are plotted for clarity.
Paper: Four Elements to Rule Them All: Abundances Are Rigidly Coupled in the Milky Way Disk
Authors: Jennifer Mead, Rebeca De La Garza Evia, Melissa K. Ness
Figure caption: [X/H] vs. [Fe/H] for elements in B18, colored by Teff. Five times the average error bar is shown in the lower right of each plot.
Paper: Four Elements to Rule Them All: Abundances Are Rigidly Coupled in the Milky Way Disk
Authors: Jennifer Mead, Rebeca De La Garza Evia, Melissa K. Ness
Figure caption: The intrinsic scatter of conditional abundance residuals between the inferred and measured data of B18. Shown are the intrinsic scatter for the fiducial model (green circles) as well as the intrinsic scatter for our full, four-source model (purple stars), which includes, in addition to the fiducial model, contributions from a representative first-peak s-process element ([Y/H]) and a representative second-peak s-process element ([Ce/H]).
Paper: Four Elements to Rule Them All: Abundances Are Rigidly Coupled in the Milky Way Disk
Authors: Jennifer Mead, Rebeca De La Garza Evia, Melissa K. Ness
Figure caption: Pearson correlation coefficients of the [X/H] conditional abundance residuals from the fiducial model with every other [X/H] abundance residual. Red colors indicate positive correlation, blue colors indicate negative correlation, and darker shades indicate stronger (anti-)correlations.
Paper: Four Elements to Rule Them All: Abundances Are Rigidly Coupled in the Milky Way Disk
Authors: Jennifer Mead, Rebeca De La Garza Evia, Melissa K. Ness
Figure caption: The intrinsic scatter of the residuals for each predicted s-process element (x-axis) for each possible three-source model (Equation (6); y-axis), in order to highlight how the choice of the third source abundance impacts the accuracy of the model’s predictions for each of the predicted abundances. Purple and blue shaded squares indicate lower intrinsic scatter and thus higher accuracy. Models using a first-peak s-process element as a predictor are better able to predict other first-peak s-process elements, but not other s- and r- process elements, and second-peak s-process elements are better able to predict other second-peak s-process elements, but do not do as well with first-peak s-process or r-process elements. r-process abundances used in the three-source model do not notably improve predictions for s- or r-process abundances.
Paper: Four Elements to Rule Them All: Abundances Are Rigidly Coupled in the Milky Way Disk
Authors: Jennifer Mead, Rebeca De La Garza Evia, Melissa K. Ness
Figure caption: The intrinsic scatter of conditional abundance residuals between the inferred and measured data of B18. Shown are the intrinsic scatter for the fiducial model (green circles) as well as the intrinsic scatter for three-source models that demonstrate the impact on the intrinsic scatter of including a first-peak s-process element ([Y/H]; purple squares), a second-peak s-process element ([Ce/H]; orange triangles), and an r-process element ([Eu/H]; blue diamonds).
Paper: Four Elements to Rule Them All: Abundances Are Rigidly Coupled in the Milky Way Disk
Authors: Jennifer Mead, Rebeca De La Garza Evia, Melissa K. Ness
Figure caption: Ratio of the standard deviation of element abundances to the mean uncertainty. Top panel: B14 and B16 data. Bottom panel: B18 data. Due to the high precision (low uncertainty) of the B18 data, the mean uncertainty is a factor of 4 smaller than the standard deviation for nearly all elements, a higher ratio than for any element from B14 or B16.
Paper: Four Elements to Rule Them All: Abundances Are Rigidly Coupled in the Milky Way Disk
Authors: Jennifer Mead, Rebeca De La Garza Evia, Melissa K. Ness
Figure caption: The intrinsic scatter of conditional abundance residuals between the inferred and measured data of B18. Shown are the intrinsic scatter for the fiducial model (green circles), as well as alterations on the fiducial model: substituting [Mg/H] for [Si/H] as a representative α element (purple squares), and substituting [Mn/H] (orange triangles) and [Ni/H] (blue diamonds) for [Fe/H] as a representative Fe-peak element.
Paper: Four Elements to Rule Them All: Abundances Are Rigidly Coupled in the Milky Way Disk
Authors: Jennifer Mead, Rebeca De La Garza Evia, Melissa K. Ness
Figure caption: The intrinsic scatter of conditional abundance residuals between the inferred and measured data of B14. Shown are the intrinsic scatter for the fiducial two-source model (green circles) and intrinsic scatter for a three-source model that includes one representative first-peak s-process element, [Y/H] (purple squares).
Paper: Four Elements to Rule Them All: Abundances Are Rigidly Coupled in the Milky Way Disk
Authors: Jennifer Mead, Rebeca De La Garza Evia, Melissa K. Ness
Figure caption: Pearson correlation coefficients of the [X/H] residuals from the four-source model with every other [X/H] abundance residual.
Paper: Four Elements to Rule Them All: Abundances Are Rigidly Coupled in the Milky Way Disk
Authors: Jennifer Mead, Rebeca De La Garza Evia, Melissa K. Ness
Figure caption: Standard deviation of Pearson correlation coefficients from noise-perturbed data.
Paper: The Role of Environment in Triggering Active Galactic Nuclei—Evidence for a Change at z ∼ 1
Authors: Jason R. Reeves, Anna Sajina, Henry Adair, Duncan Farrah, Mark Lacy
Figure caption: Redshift vs. luminosity of the X-ray sources. The gray band illustrates the X-ray AGN sample from G. Yang et al. (2018), who do a similar study to ours (see Section 4 for further discussion). The color of the bin represents the type of dependence seen in this regime of redshift and AGN luminosity. Blue bins represent regimes of antidependence with more dense environments having a lower percentage of galaxies hosting an AGN. Red bins represent regimes of positive correlation between the AGN occurrence and extragalactic environmental density. Gray or pale colored bins represent regimes with no dependence between the AGN occurrence and extragalactic density. The weak coloring of the bins for X-ray detected sources represents the lack of dependence seen in either bin of redshift and luminosity considered in this study. Overlaid on each bin is the significance of the score (see Section 3.1).
Paper: The Role of Environment in Triggering Active Galactic Nuclei—Evidence for a Change at z ∼ 1
Authors: Jason R. Reeves, Anna Sajina, Henry Adair, Duncan Farrah, Mark Lacy
Figure caption: Redshift vs. luminosity of the IR-only sample. Similar to Figures 4 and 5, the color of the bins correspond to the type of dependence seen in a bin of redshift and AGN luminosity, with the significance of the score overlaid in each bin. Like Figure 5, the two bins switch with respect to the type of dependence exhibited between the occurrence of AGN detected in the IR only and the density of their extragalactic environments. At z = 1.2, the dependence turns from a positive dependence to a negative one.
Paper: The Role of Environment in Triggering Active Galactic Nuclei—Evidence for a Change at z ∼ 1
Authors: Jason R. Reeves, Anna Sajina, Henry Adair, Duncan Farrah, Mark Lacy
Figure caption: Redshift vs. luminosity of the full IR sample. Similar to Figure 4, the color of the bins correspond to the type of dependence seen in a bin of redshift and AGN luminosity, with the significance of the score overlaid in each bin. Between the two bins, the type of dependence exhibited for IR AGN switches at z = 1.2, such that it turns from a positive dependence to a negative one.
Paper: The Role of Environment in Triggering Active Galactic Nuclei—Evidence for a Change at z ∼ 1
Authors: Jason R. Reeves, Anna Sajina, Henry Adair, Duncan Farrah, Mark Lacy
Figure caption: The redshift vs. luminosity plots for the X-ray-detected AGN (left) and IR-detected AGN (right) after removing sources matched to host galaxies with stellar masses ﹩{\mathrm{log}}(\frac{{M}_{* }}{{M}_{\odot }})\lt 9.3﹩ and ﹩{\mathrm{log}}(\frac{{M}_{* }}{{M}_{\odot }})\gt 12.0﹩, being outside the mass bins used in our study. Unfilled circles in the IR plot represent IR-detected AGN without a matched X-ray source.
Paper: The Role of Environment in Triggering Active Galactic Nuclei—Evidence for a Change at z ∼ 1
Authors: Jason R. Reeves, Anna Sajina, Henry Adair, Duncan Farrah, Mark Lacy
Figure caption: The AGN percentage in different stellar mass and local density bins. Here, the top panels represent the lower-redshift bin (0.1 < z < 1.2), whereas the bottom three panels represent the higher-redshift bin (1.2 < z < 1.6). In all panels, we apply an additional luminosity cut as indicated in order to have luminosity-complete samples per redshift bin.
Paper: The Role of Environment in Triggering Active Galactic Nuclei—Evidence for a Change at z ∼ 1
Authors: Jason R. Reeves, Anna Sajina, Henry Adair, Duncan Farrah, Mark Lacy
Figure caption: Recreation of Figure 10 from G. Yang et al. (2018) using the X-ray sample described in Section 2.3, adopting their bins of redshift, stellar mass, and density. Density bins are created by splitting galaxies into percentile ranks, similar to Section 2.2. Here, density bins are divided by the 10th, 30th, 50th, 70th, and 90th percentile ranks of the extragalactic densities. In both bins of redshift, we recover their result showing no significant difference in occurrence as a function of extragalactic density.
Paper: The Role of Environment in Triggering Active Galactic Nuclei—Evidence for a Change at z ∼ 1
Authors: Jason R. Reeves, Anna Sajina, Henry Adair, Duncan Farrah, Mark Lacy
Figure caption: Probabilities of the scores from 1000 bootstrapped samples of IR and IR-only AGN in the redshift bins from Figure 5 (left) and Figure 6 (right). This analysis further strengthens our results of a reversal in the density dependence at z ∼ 1.2 with IR AGN preferring higher-density environments at z > 1.2 and lower-density environments at z < 1.2.
Paper: The Role of Environment in Triggering Active Galactic Nuclei—Evidence for a Change at z ∼ 1
Authors: Jason R. Reeves, Anna Sajina, Henry Adair, Duncan Farrah, Mark Lacy
Figure caption: The contour lines show the stellar mass vs. redshift for all galaxies in the parent catalog at levels of 0.1st, 1st, 10th, 50th, and 70th percentile galaxy counts. The points represent the three different AGN samples as indicated in the legend. Histograms on the top and right-hand side show the distributions of photometric redshifts and stellar masses of the host galaxies of the X-ray sources (in blue), IR sources (in bright red), and IR-only (dashed dark red), respectively.
Paper: The Role of Environment in Triggering Active Galactic Nuclei—Evidence for a Change at z ∼ 1
Authors: Jason R. Reeves, Anna Sajina, Henry Adair, Duncan Farrah, Mark Lacy
Figure caption: Probabilities of the scores from 1000 bootstrapped samples of X-ray AGN in the redshift bins from Figure 4. While there is still an offset in the peaks of the two distributions such that the higher-z bootstrapped samples prefer positive scores and the lower-z samples peak around zero, this offset is not statistically significant. Here, 23% of the z > 1.2 bootstrapped subsamples show negative scores.
Paper: What Physical Factors Influence the Transformation between Blue Supergiants and Red Supergiants?
Authors: Yun He, Hanfeng Song, Georges Meynet, Andre Maeder, Ruiyu Zhang, Ying Qin, Shitao Qi, Qingli Li, Qiong Zhan
Figure caption: Evolutionary tracks for the stars with different initial masses, rotational velocities, and metallicities on the H-R diagram . Panels (a1), (a2), (a3) are for 16 M⊙ stars with different initial rotational velocities and metallicities. Panels (b1), (b2), (b3) are the same but for 24 M⊙ stars. Panels (c1), (c2), (c3) are the same but for 32 M⊙ stars. Black, red, green, and blue lines indicate the models calculated with rotational velocities of 0 km s−1, 200 km s−1, 300 km s−1, and 400 km s−1, respectively. The initial metallicities are Z = 0.0047, 0.014, and 0.025. The hollow circle, square, diamond, and triangle along the tracks indicate the evolutionary points at which the core hydrogen has been exhausted, the core helium begins to ignite, the core helium has been exhausted, and the core carbon begins to ignite, respectively. The observations of blue supergiants (blue circles), yellow supergiants (yellow circles) and red supergiants (red circles) in panels (a1), (b1), and (c1) are taken from G. A. Wagle et al. (2020). The observations of blue supergiants (blue circles) and red supergiants (red circles) in panels (a2), (b2), and (c2) are taken from H. Saio et al. (2013) and E. M. Levesque et al. (2005), respectively. And blue supergiants shown as blue squares with error bars are from J. P. Sánchez Arias et al. (2023).
Paper: What Physical Factors Influence the Transformation between Blue Supergiants and Red Supergiants?
Authors: Yun He, Hanfeng Song, Georges Meynet, Andre Maeder, Ruiyu Zhang, Ying Qin, Shitao Qi, Qingli Li, Qiong Zhan
Figure caption: Left panels: the ratio of the duration as red supergiants to the duration of core helium burning for different initial stellar masses and rotational velocities. (a) Models with initial metallicity of Z = 0.0047 but with different initial rotational velocities and stellar masses. (b) The same but for models with Z = 0.014 . (c) The same but for models with Z = 0.025. Right panels: the evolution of surface effective temperature during the core helium burning. (a1) For 16 M⊙ stars with different initial metallicities and initial velocities. (b1) The same but for 24 M⊙ stars. (c1) The same but for 32 M⊙ stars. The shaded region indicates yellow supergiants at effective temperatures. Black, red, green, and blue lines indicate models calculated with different initial rotational velocities of vini = 0 km s−1, 200 km s−1, 300 km s−1, and 400 km s−1, respectively.
Paper: What Physical Factors Influence the Transformation between Blue Supergiants and Red Supergiants?
Authors: Yun He, Hanfeng Song, Georges Meynet, Andre Maeder, Ruiyu Zhang, Ying Qin, Shitao Qi, Qingli Li, Qiong Zhan
Figure caption: The profile of chemical composition for the models with and without rotation at core helium exhaustion. Chemical elements in nonrotating stars are marked by solid lines and these elements in rotating stars are marked by dashed lines. Panels (a1) and (a2) are for 16 M⊙ stars with different initial metallicities of Z = 0.0047 and 0.025, respectively. Panels (b1) and (b2) are the same but for 24 M⊙ stars. Panels (c1) and (c2) are the same but for 32 M⊙ stars.
Paper: What Physical Factors Influence the Transformation between Blue Supergiants and Red Supergiants?
Authors: Yun He, Hanfeng Song, Georges Meynet, Andre Maeder, Ruiyu Zhang, Ying Qin, Shitao Qi, Qingli Li, Qiong Zhan
Figure caption: Left panels: evolution of the surface equatorial rotational velocity v for stars with different initial masses, rotational velocities, and metallicities. Right panels: evolution of the ratio of the angular velocity to the break-up angular velocity Ω/Ωcrit for stars with different initial masses, rotational velocities, and metallicities. Black, red, green, and blue lines indicate the models calculated with initial rotational velocities of 0 km s−1, 200 km s−1, 300 km s−1, and 400 km s−1, respectively. The initial metallicities are Z = 0.0047, 0.014, and 0.025. Panels (a), (b), and (c) are for stars with different initial masses of M = 16, 24, and 32 M⊙, respectively.
Paper: What Physical Factors Influence the Transformation between Blue Supergiants and Red Supergiants?
Authors: Yun He, Hanfeng Song, Georges Meynet, Andre Maeder, Ruiyu Zhang, Ying Qin, Shitao Qi, Qingli Li, Qiong Zhan
Figure caption: The evolution of the convective core mass for models with different initial stellar masses, metallicities, and rotational velocities. Panels (a1), (a2), (a3) are for 16 M⊙ stars with different initial metallicities and rotational velocities. Panels (b1), (b2), (b3) are same but for 24 M⊙ stars. Panels (c1), (c2), (c3) are the same but for 32 M⊙ stars. Black, red, green, and blue tracks indicate the models calculated with different initial rotational velocities of 0 km s−1, 200 km s−1, 300 km s−1, and 400 km s−1, respectively.