adsabs/AstroCLIMB huggingface dataset:
Paper: Constraining Inputs to Realistic Kilonova Simulations through Comparison to Observed r-process Abundances
Authors: Marko Ristić, Erika M. Holmbeck, Ryan T. Wollaeger, Oleg Korobkin, Elizabeth Champion, Richard O'Shaughnessy, Chris L. Fryer, Christopher J. Fontes, Matthew R. Mumpower, Trevor M. Sprouse
Figure caption: Top: 2D distribution of residuals calculated as in Equation (1) by comparing ﹩\mathrm{log}{X}_{\odot }﹩ to ﹩\mathrm{log}{X}_{\mathrm{sim}}﹩ using the dynamical and wind compositions matching those in Ristic et al. (2022), represented by the asterisk in Table 1. The residual grid is composed of 50 mass values equally log-spaced between ﹩-3\leqslant \mathrm{log}{M}_{\odot }\leqslant -1﹩ for both dynamical and wind mass. The black lines indicate contours of equally spaced residual values. The dashed red lines indicate a wind-to-mass ratio of 1 and serve purely as a visual aid. Bottom: mass fractions of individual ejecta components compared to the best-fit mass fraction ﹩{X}_{\mathrm{sim}}﹩ obtained from comparison to X ⊙. The red and blue lines are the initial unweighted dynamical (X  d ) and wind (X  w ) ejecta mass fractions, respectively, scaled by C to match the solar mass fraction at Z = 46. The gray line is the solar mass fraction X ⊙, and the blue shaded region is the 90% confidence interval for all the mass-weighted mass fractions ﹩\mathrm{log}{X}_{\mathrm{sim}}﹩. The dynamical ejecta mass fraction only exceeds ﹩\mathrm{log}X=0﹩ owing to the scale matching at Z = 46.
Paper: Constraining Inputs to Realistic Kilonova Simulations through Comparison to Observed r-process Abundances
Authors: Marko Ristić, Erika M. Holmbeck, Ryan T. Wollaeger, Oleg Korobkin, Elizabeth Champion, Richard O'Shaughnessy, Chris L. Fryer, Christopher J. Fontes, Matthew R. Mumpower, Trevor M. Sprouse
Figure caption: Elemental mass fraction ratios relative to iron of a sample of r-process-enriched metal-poor stars. [X/Fe] > 0 implies enhanced abundance of element X compared to the solar system with respect to iron. We assume all elements that are significantly enhanced compared to iron to have been introduced post-supernova, exclusively from neutron star mergers. The region of enhanced elements (Z ≥ 37, highlighted in blue) is the focus of our comparison to solar composition. The iron-peak elements and supernova r-process are not strongly enhanced compared to solar (highlighted in yellow). Stellar elemental abundances are obtained from JINAbase (Abohalima & Frebel 2018), with the respective stars reported in Westin et al. (2000), Hill et al. (2002), Cowan et al. (2002), Sneden et al. (2003), Ivans et al. (2006), and Hayek et al. (2009).
Paper: Constraining Inputs to Realistic Kilonova Simulations through Comparison to Observed r-process Abundances
Authors: Marko Ristić, Erika M. Holmbeck, Ryan T. Wollaeger, Oleg Korobkin, Elizabeth Champion, Richard O'Shaughnessy, Chris L. Fryer, Christopher J. Fontes, Matthew R. Mumpower, Trevor M. Sprouse
Figure caption: Top: same 2D distribution as described in Figure 5, except with the compositions that yielded the lowest residual in comparison to the solar abundance pattern X ⊙ (top row of Table 1). Bottom: mass fractions of individual ejecta components compared to the best-fit mass fraction ﹩{X}_{\mathrm{sim}}﹩ obtained from comparison to X ⊙. The line colors represent the same quantities as in Figure 5. The minimum residual was identified as the smallest residual across all the mass pairs considered for a given composition ﹩{X}_{\mathrm{sim}}﹩.
Paper: Constraining Inputs to Realistic Kilonova Simulations through Comparison to Observed r-process Abundances
Authors: Marko Ristić, Erika M. Holmbeck, Ryan T. Wollaeger, Oleg Korobkin, Elizabeth Champion, Richard O'Shaughnessy, Chris L. Fryer, Christopher J. Fontes, Matthew R. Mumpower, Trevor M. Sprouse
Figure caption: Posterior distributions created using only the 2D r-process prior presented in Figure 6, with no electromagnetic information provided during sampling besides constraints on the opening angle (see Troja et al. 2020 and references therein). We apply a scale factor in our likelihood calculation during inference to prevent underflow from the large residual values. Note the recovery of the yellow band of lowest-residual mass pairs from Figure 6 in the M  w  vs. M  d  panel, as well as the flat velocity posteriors stemming from the lack of velocity constraints introduced by our mass-focused prior. Residual small-scale substructure in the one- and two-dimensional marginal distributions reflects sample size artifacts.
Paper: Constraining Inputs to Realistic Kilonova Simulations through Comparison to Observed r-process Abundances
Authors: Marko Ristić, Erika M. Holmbeck, Ryan T. Wollaeger, Oleg Korobkin, Elizabeth Champion, Richard O'Shaughnessy, Chris L. Fryer, Christopher J. Fontes, Matthew R. Mumpower, Trevor M. Sprouse
Figure caption: Posterior distributions for samples generated when using the grizyJHK bands considered in Ristic et al. (2022; black) and samples generated using the same bands along with the r-process prior from Figure 6 (red). The values reported at the top of each posterior distribution represent the inference results from this study. The composition prior effect is most evident in the wind mass posterior shift to lower ejecta mass.
Paper: Constraining Inputs to Realistic Kilonova Simulations through Comparison to Observed r-process Abundances
Authors: Marko Ristić, Erika M. Holmbeck, Ryan T. Wollaeger, Oleg Korobkin, Elizabeth Champion, Richard O'Shaughnessy, Chris L. Fryer, Christopher J. Fontes, Matthew R. Mumpower, Trevor M. Sprouse
Figure caption: Re-created Y  e  distribution for dynamical ejecta as presented in Figure 5 of Kiuchi et al. (2023). The analytic fit to the distribution, presented in Equation (2), is overlaid as a red line. The analytic fit was used to generate the Y  e -distribution compositions presented in Table 2.
Paper: Constraining Inputs to Realistic Kilonova Simulations through Comparison to Observed r-process Abundances
Authors: Marko Ristić, Erika M. Holmbeck, Ryan T. Wollaeger, Oleg Korobkin, Elizabeth Champion, Richard O'Shaughnessy, Chris L. Fryer, Christopher J. Fontes, Matthew R. Mumpower, Trevor M. Sprouse
Figure caption: Broadband light-curve predictions for the ejecta parameters recovered in Figure 8. The inclusion of the composition-based mass prior (top panel of Figure 6) reduces model prediction uncertainty compared to previous predictions (Ristic et al. 2022).
Paper: Beyond Two-dimensional Mass–Radius Relationships: A Nonparametric and Probabilistic Framework for Characterizing Planetary Samples in Higher Dimensions
Authors: Shubham Kanodia, Matthias Y. He, Eric B. Ford, Sujit K. Ghosh, Angie Wolfgang
Figure caption: We perform a four-dimensional fit to the sample of confirmed small 							planets (R  p  < 4R ⊕), and then condition it to show the variation in planetary 							bulk-density with insolation and stellar mass. For each panel, the 							bottom x-axis denotes the insolation flux 							received by the planet (same for all panels) while the top x-axis denotes the orbital period (which 							varies across the panels due to the different stellar masses). To 							convert insolation to orbital period, we adopt stellar luminosities from 							Table 6 in Cifuentes et al. (2020). The solid lines depict the expectation value (mean) 							of the prediction, whereas the shaded region shows the 16th—84th 							percentile region from 100 bootstrapped samples. For reference, we also 							plot the values for the mean bulk densities of Earth and Neptune as the 							dashed and dashed-dotted lines, respectively.
Paper: Beyond Two-dimensional Mass–Radius Relationships: A Nonparametric and Probabilistic Framework for Characterizing Planetary Samples in Higher Dimensions
Authors: Shubham Kanodia, Matthias Y. He, Eric B. Ford, Sujit K. Ghosh, Angie Wolfgang
Figure caption: Two-dimensional sample set with ∼180 planets. Joint distribution f(m, r) showing the masses and radii for the input data 						set, where the colors in the background represent the PDF, where blue is a 						higher probability, and red is lower.
Paper: Beyond Two-dimensional Mass–Radius Relationships: A Nonparametric and Probabilistic Framework for Characterizing Planetary Samples in Higher Dimensions
Authors: Shubham Kanodia, Matthias Y. He, Eric B. Ford, Sujit K. Ghosh, Angie Wolfgang
Figure caption: Similar to the previous figure, we condition the four-dimensional joint 							distribution to obtain the expectation value for planetary mass as a 							function of different planetary radii, insolation; and plotted across 							stellar mass. The shaded region depicts the 16th–84th percentile region 							from 100 bootstrapped samples.
Paper: Beyond Two-dimensional Mass–Radius Relationships: A Nonparametric and Probabilistic Framework for Characterizing Planetary Samples in Higher Dimensions
Authors: Shubham Kanodia, Matthias Y. He, Eric B. Ford, Sujit K. Ghosh, Angie Wolfgang
Figure caption: The CKS-X sample in plotted in period–planet radius–stellar mass (P-R  p -M ⋆), consisting of 1073 planets given our cuts as described in 							Section 3.2. Each point 							denotes a planet, where the color denotes its host stellar mass.
Paper: Beyond Two-dimensional Mass–Radius Relationships: A Nonparametric and Probabilistic Framework for Characterizing Planetary Samples in Higher Dimensions
Authors: Shubham Kanodia, Matthias Y. He, Eric B. Ford, Sujit K. Ghosh, Angie Wolfgang
Figure caption: Two-dimensional representations of the input sample in planetary mass–radius 						plane colored by stellar insolation and stellar mass respectively. It is 						evident that insolation and/or stellar mass dependent bulk-density trends 						are harder to tease out with conventional two-dimensional analysis.
Paper: Beyond Two-dimensional Mass–Radius Relationships: A Nonparametric and Probabilistic Framework for Characterizing Planetary Samples in Higher Dimensions
Authors: Shubham Kanodia, Matthias Y. He, Eric B. Ford, Sujit K. Ghosh, Angie Wolfgang
Figure caption: Comparing mass–radius distributions after incorporating additional 							dimensions for a 1.5 R ⊕ planet. Top: the various colored dashed lines represent the 							expectation value of f(m∣r, stm), whereas the black dashed line represents 							the prediction from a two-dimensional f(m∣r) distribution. The gray histogram shows the distribution 							of predictions from a Monte Carlo simulation on the input 							two-dimensional data set. Bottom: predicted planetary mass as a function 							of stellar mass and insolation flux where the color bar represents the 							expectation value for the planetary mass compared to the two-dimensional 							prediction of ∼4.5 M ⊕.
Paper: Beyond Two-dimensional Mass–Radius Relationships: A Nonparametric and Probabilistic Framework for Characterizing Planetary Samples in Higher Dimensions
Authors: Shubham Kanodia, Matthias Y. He, Eric B. Ford, Sujit K. Ghosh, Angie Wolfgang
Figure caption: Conditional mass distribution f(m∣r) for the joint 						distribution shown in Figure 1 						on three different radii to obtain the conditional distribution for masses. 						The dashed lines and the masses are the expected value (Equation (3)) for each radius, 						whereas the histogram shows the predictions from each Monte Carlo for 						illustrative purposes.
Paper: Beyond Two-dimensional Mass–Radius Relationships: A Nonparametric and Probabilistic Framework for Characterizing Planetary Samples in Higher Dimensions
Authors: Shubham Kanodia, Matthias Y. He, Eric B. Ford, Sujit K. Ghosh, Angie Wolfgang
Figure caption: Modeling the distribution of planets in three dimensions (period–planet 							radius–stellar mass) using the CKS-X planet sample. Joint planet 							radius–period distributions conditioned on various stellar masses (i.e., 								f(P, 								R  p ∣M ⋆), where M ⋆ = 0.6, 0.8, 1.0, and 1.2 M ⊙, as labeled above each panel). The model was fit to the 							CKS-X sample (1073 planets, as filtered in Section 3.2) with a fixed number of degrees in 							each dimension (d = 30, chosen from the 							cross-validation method). These distributions represent the 							modeled-observed distributions, as no detection biases were corrected 							for in any manner. The color-scale in each panel represents the 							conditional probability density such that each conditional distribution 							integrates to unity, as computed in ﹩\mathrm{log}{R}_{p}﹩-﹩\mathrm{log}P﹩ space.
Paper: Beyond Two-dimensional Mass–Radius Relationships: A Nonparametric and Probabilistic Framework for Characterizing Planetary Samples in Higher Dimensions
Authors: Shubham Kanodia, Matthias Y. He, Eric B. Ford, Sujit K. Ghosh, Angie Wolfgang
Figure caption: The effect of finite sample size on the joint P-R  p  distribution conditioned on a given stellar mass, f(P, R  p ∣M ⋆ = 0.80 M ⊙), from 100 bootstrap resamplings of the CKS-X data set 							(described in Section 3.2). Left: the mean divided by the standard deviation of 							the joint probability densities, ﹩{\mu }_{f(P,{R}_{p}| {M}_{\star })}/{\sigma }_{f(P,{R}_{p}| {M}_{\star })}﹩, over the bootstraps. Higher values denote regions 							where the model is more robust due to a greater density of data points. 							Right: the mean joint probability density of the bootstraps, with the 							regions ﹩{\mu }_{f(P,{R}_{p}| {M}_{\star })}/{\sigma }_{f(P,{R}_{p}| {M}_{\star })}\lt 3﹩ masked out.
Paper: Beyond Two-dimensional Mass–Radius Relationships: A Nonparametric and Probabilistic Framework for Characterizing Planetary Samples in Higher Dimensions
Authors: Shubham Kanodia, Matthias Y. He, Eric B. Ford, Sujit K. Ghosh, Angie Wolfgang
Figure caption: (a) Showing a two-dimensional grid of AIC for the M-R data set shown in 							(Figure 1), along with 							contours of similar AIC. In this case, the optimized degrees are roughly 							equal (20,23) and are marked with an “X.” (b) The change in conditional 							distribution f(m∣r = 12 R ⊕) as the degree choices are sampled from within the 							innermost AIC contour (a). We conclude that, for such a data set with a 							large amount of scatter, the conditional distribution is not too 							sensitive to the exact choice of degrees.
Paper: Beyond Two-dimensional Mass–Radius Relationships: A Nonparametric and Probabilistic Framework for Characterizing Planetary Samples in Higher Dimensions
Authors: Shubham Kanodia, Matthias Y. He, Eric B. Ford, Sujit K. Ghosh, Angie Wolfgang
Figure caption: Joint distribution of the stellar mass—disk dust mass distribution for 69 							disks in the Lupus complex as presented in Ansdell et al. (2016). Additionally, the 							red shaded region depicts the power-law fit from Ansdell et al. (2016) for reference.
Paper: Beyond Two-dimensional Mass–Radius Relationships: A Nonparametric and Probabilistic Framework for Characterizing Planetary Samples in Higher Dimensions
Authors: Shubham Kanodia, Matthias Y. He, Eric B. Ford, Sujit K. Ghosh, Angie Wolfgang
Figure caption: Conditional distribution predicting the disk dust mass for different 							stellar masses. The dashed lines and the masses are the expected value 							(Equation (3)) 							for each radius, whereas the histogram shows the predictions from the 							Monte Carlo simulation.
Paper: The RS Oph Outburst of 2021 Monitored in X-Rays with NICER
Authors: Marina Orio, Keith Gendreau, Morgan Giese, Gerardo Juan M. Luna, Jozef Magdolen, Tod E. Strohmayer, Andy E. Zhang, Diego Altamirano, Andrej Dobrotka, Teruaki Enoto, Elizabeth C. Ferrara, Richard Ignace, Sebastian Heinz, Craig Markwardt, Joy S. Nichols, Michael L. Parker, Dheeraj R. Pasham, Songpeng Pei, Pragati Pradhan, Ron Remillard, James F. Steiner, Francesco Tombesi
Figure caption: For the first 20 days: in the left upper panel, absorbed flux derived by model fitting; in the left lower panel, absolute flux; in the upper right, plasma temperature of the hotter component (or only component for the red points); in the lower right panel, column density N(H). NEI model fits were used in the first 5.5 days of observations, and their parameters are plotted in red. A second component from day 5.5 has a temperature around 0.9 keV in all exposures. The N(H) values in green are the ones of the partially covering absorber (see text for covering fraction), and the 2-component BVAPEC parameters have been plotted in black if there was the partially covering absorber, in purple if this addition was not necessary. The y-axis error bars show the largest of the 2σ error in the positive and negative direction, calculated assuming that the other parameters do not vary. The x-axis error bars show the time interval over which the spectrum was integrated. Individual short GTIs were chosen for spectra extraction and fitting when there was significant variability during the day.
Paper: The RS Oph Outburst of 2021 Monitored in X-Rays with NICER
Authors: Marina Orio, Keith Gendreau, Morgan Giese, Gerardo Juan M. Luna, Jozef Magdolen, Tod E. Strohmayer, Andy E. Zhang, Diego Altamirano, Andrej Dobrotka, Teruaki Enoto, Elizabeth C. Ferrara, Richard Ignace, Sebastian Heinz, Craig Markwardt, Joy S. Nichols, Michael L. Parker, Dheeraj R. Pasham, Songpeng Pei, Pragati Pradhan, Ron Remillard, James F. Steiner, Francesco Tombesi
Figure caption: Top: the light curves observed over few hours on day 21 (2021 August 30; left) and day 27 (2021 September 5; right). On day 21, new observations were resumed with XMM-Newton after about 3 hr. The light curve during that exposure shows a continuing decline in flux for the whole day (Orio et al. 2022a). The ≃ 35 s QPO on day 27 was very pronounced during this day. The bottom panels compare spectra during high and low count rate intervals. On the left, the spectrum measured on August 30 during the initial GTIs with higher count rate (black, first 130 minutes) compared with that of the last GITs with lower count rate on day 21 (red, last ≃360 minutes); and on the right, the spectrum of the third GTI of day 27 (in black, it lasted for about 400 s) and that of the GTI before the last (in red).
Paper: The RS Oph Outburst of 2021 Monitored in X-Rays with NICER
Authors: Marina Orio, Keith Gendreau, Morgan Giese, Gerardo Juan M. Luna, Jozef Magdolen, Tod E. Strohmayer, Andy E. Zhang, Diego Altamirano, Andrej Dobrotka, Teruaki Enoto, Elizabeth C. Ferrara, Richard Ignace, Sebastian Heinz, Craig Markwardt, Joy S. Nichols, Michael L. Parker, Dheeraj R. Pasham, Songpeng Pei, Pragati Pradhan, Ron Remillard, James F. Steiner, Francesco Tombesi
Figure caption: Predicted flux line ratios of Si XIII/Si XIV and  XV/S XVI (including all the merged lines for the He-like triplet) for a single temperature plasma region, under the assumption of collisional ionization equilibrium (CIE, in red) and assuming nonequilibrium (NEI, in black, like in the “VPSHOCK” XSPEC model, with ionization timescale parameter 1011 cm  ×  s). The dots indicate actual measurements in correlation with the maximum temperature of an acceptable fit to NICER spectra; the green dot in the lower panel shows a measurement with a resolved triplet, with the Chandra HETG grating from Orio et al. (2022a). In that paper, a very good fit to the overall spectrum was obtained assuming two regions at different temperature and in CIE, instead of a single region in NEI.
Paper: The RS Oph Outburst of 2021 Monitored in X-Rays with NICER
Authors: Marina Orio, Keith Gendreau, Morgan Giese, Gerardo Juan M. Luna, Jozef Magdolen, Tod E. Strohmayer, Andy E. Zhang, Diego Altamirano, Andrej Dobrotka, Teruaki Enoto, Elizabeth C. Ferrara, Richard Ignace, Sebastian Heinz, Craig Markwardt, Joy S. Nichols, Michael L. Parker, Dheeraj R. Pasham, Songpeng Pei, Pragati Pradhan, Ron Remillard, James F. Steiner, Francesco Tombesi
Figure caption: The average count rate spectra observed with NICER from day 1 to 7.5. The dates are 2021 August 10 (black, observation 4202300101), August 11 (red, obs. 4202300102), August 12 (green, obs. 4202300103), August 13 (dark blue, obs. 4202300104), August 14 (cyan, obs. 4202300105), August 15 (pink, obs. 4202300106), and August 16 (orange, obs. 4202300107). The prominent emission lines are marked.
Paper: The RS Oph Outburst of 2021 Monitored in X-Rays with NICER
Authors: Marina Orio, Keith Gendreau, Morgan Giese, Gerardo Juan M. Luna, Jozef Magdolen, Tod E. Strohmayer, Andy E. Zhang, Diego Altamirano, Andrej Dobrotka, Teruaki Enoto, Elizabeth C. Ferrara, Richard Ignace, Sebastian Heinz, Craig Markwardt, Joy S. Nichols, Michael L. Parker, Dheeraj R. Pasham, Songpeng Pei, Pragati Pradhan, Ron Remillard, James F. Steiner, Francesco Tombesi
Figure caption: The light curve (0.2–1 keV range, nonbackground subtracted) for the days of largest supersoft luminosity, between days 44 and 50, and in more detail for 2021 September 18–19 (day 46 of the outburst).
Paper: The RS Oph Outburst of 2021 Monitored in X-Rays with NICER
Authors: Marina Orio, Keith Gendreau, Morgan Giese, Gerardo Juan M. Luna, Jozef Magdolen, Tod E. Strohmayer, Andy E. Zhang, Diego Altamirano, Andrej Dobrotka, Teruaki Enoto, Elizabeth C. Ferrara, Richard Ignace, Sebastian Heinz, Craig Markwardt, Joy S. Nichols, Michael L. Parker, Dheeraj R. Pasham, Songpeng Pei, Pragati Pradhan, Ron Remillard, James F. Steiner, Francesco Tombesi
Figure caption: The average daily spectra observed with NICER in the period between days 8 and 29, plotted every 4 days. The colors’ sequence in order of date is black (2021 August 17), red (August 21), blue (August 25), green (August 29), cyan (September 3), pink (September 7).
Paper: The RS Oph Outburst of 2021 Monitored in X-Rays with NICER
Authors: Marina Orio, Keith Gendreau, Morgan Giese, Gerardo Juan M. Luna, Jozef Magdolen, Tod E. Strohmayer, Andy E. Zhang, Diego Altamirano, Andrej Dobrotka, Teruaki Enoto, Elizabeth C. Ferrara, Richard Ignace, Sebastian Heinz, Craig Markwardt, Joy S. Nichols, Michael L. Parker, Dheeraj R. Pasham, Songpeng Pei, Pragati Pradhan, Ron Remillard, James F. Steiner, Francesco Tombesi
Figure caption: The spectrum of the first GTI of day 28 (2021 September 6), during a quiet day after the flare described above. The red line traces the fit with model (3) of Table 3 (in red).
Paper: The RS Oph Outburst of 2021 Monitored in X-Rays with NICER
Authors: Marina Orio, Keith Gendreau, Morgan Giese, Gerardo Juan M. Luna, Jozef Magdolen, Tod E. Strohmayer, Andy E. Zhang, Diego Altamirano, Andrej Dobrotka, Teruaki Enoto, Elizabeth C. Ferrara, Richard Ignace, Sebastian Heinz, Craig Markwardt, Joy S. Nichols, Michael L. Parker, Dheeraj R. Pasham, Songpeng Pei, Pragati Pradhan, Ron Remillard, James F. Steiner, Francesco Tombesi
Figure caption: Two portions of the spectrum of a flare on day 37 (2021 September 15). The red line traces the fit with model (1) in Table 4.
Paper: The RS Oph Outburst of 2021 Monitored in X-Rays with NICER
Authors: Marina Orio, Keith Gendreau, Morgan Giese, Gerardo Juan M. Luna, Jozef Magdolen, Tod E. Strohmayer, Andy E. Zhang, Diego Altamirano, Andrej Dobrotka, Teruaki Enoto, Elizabeth C. Ferrara, Richard Ignace, Sebastian Heinz, Craig Markwardt, Joy S. Nichols, Michael L. Parker, Dheeraj R. Pasham, Songpeng Pei, Pragati Pradhan, Ron Remillard, James F. Steiner, Francesco Tombesi
Figure caption: For the fourth GTI of day 7, August 16, the top panels show the fits with a plasma that is not in equilibrium, and with two plasma components at different temperature and in collisional ionization equilibrium, respectively on the left and the right. The bottom panels show the corresponding models before convolution with the instrument response. The fit parameters are in Table 2. The fit on the right shows the hot component in red, the cool one in black, and the result is shown in blue.