adsabs/AstroCLIMB huggingface dataset:
Paper: Optical Strong Line Ratios Cannot Distinguish between Stellar Populations and Accreting Black Holes at High Ionization Parameters and Low Metallicities
Authors: Nikko J. Cleri, Grace M. Olivier, Bren E. Backhaus, Joel Leja, Casey Papovich, Jonathan R. Trump, Pablo Arrabal Haro, Véronique Buat, Denis Burgarella, Emilie Burnham, Antonello Calabrò, Jonathan H. Cohn, Justin W. Cole, Kelcey Davis, Mark Dickinson, Steven L. Finkelstein, Ray Garner, Michaela Hirschmann, Weida Hu, Taylor A. Hutchison, Dale D. Kocevski, Anton M. Koekemoer, Rebecca L. Larson, Zach J. Lewis, Michael V. Maseda, Lise-Marie Seillé, Raymond C. Simons
Figure caption: The [N II]-BPT diagram shown with our suite of photoionization models colored by ionization parameter (top left) and gas-phase metallicity (bottom left). The right panels show the posteriors P(θ∣data) for the ionization parameter (top right) and gas-phase metallicity (bottom right) for a mock observation at the respective point in the [N II]-BPT plane, where the color shows the mean of the posterior.
Paper: Lost in the FoG: Pitfalls of Models for Large-scale Hydrogen Distributions
Authors: Calvin K. Osinga, Benedikt Diemer, Francisco Villaescusa-Navarro
Figure caption: A deconstructed example H I-galaxy cross-power spectrum, providing insight into the contribution of each model ingredient. The linear matter power spectrum is shown with the black dashed line in the top panel, with the wiggles at k ∼ 0.05 h cMpc−1 corresponding to baryonic acoustic oscillations. We then add each ingredient from Equation (13) to the linear power spectrum sequentially, lightening the color as each is added (see text for ingredient descriptions). The z = 1 matter power spectrum (black) and H I-galaxy cross-power spectrum (salmon) for TNG300 are shown in dotted lines, in fair agreement with the corresponding model values. The bottom panel shows the ratio of the power spectra with and without that component in order to more easily visualize its individual contribution.
Paper: Ionization Sources of the Local Interstellar Clouds: Two B Stars, Three White Dwarfs, and the Local Hot Bubble
Authors: J. Michael Shull, Rachel M. Curran, Michael W. Topping, Jonathan D. Slavin
Figure caption: Modeled spectral distribution of the flux, ﹩\mathrm{log}{F}_{\lambda }﹩ (in erg cm−2 s−1 Å−1), of ionizing (EUV) photons produced in the LHB, calculated using the CHIANTI code for plasma at three temperatures. We assume a constant electron density ne = 0.004 cm−3, with EUV emissivity integrated out to a bubble radius R = 85 pc from the Sun. The emissivities of Fe and Ne ions decline with temperature over the range ﹩\mathrm{log}T=5.9,6.0,6.1﹩, with color-coded fluxes (blue, orange, green) as labeled in the legend. Prominent EUV emission lines are noted. Top: fluxes with solar metal abundances including [Fe/H] =6.46 ± 0.04 (M. Asplund et al. 2021). Bottom: fluxes with refractory elements (Fe, Mg, Si) reduced in abundance by a factor of 5, due to depletion into dust grains. Neon is not depleted, and its lines remain strong. The underlying continuum is from bremsstrahlung and radiative recombination.
Paper: Ionization Sources of the Local Interstellar Clouds: Two B Stars, Three White Dwarfs, and the Local Hot Bubble
Authors: J. Michael Shull, Rachel M. Curran, Michael W. Topping, Jonathan D. Slavin
Figure caption: Model of a constant-density cloud (nH = 0.2 cm−3, T = 7000 K) using ionizing fluxes from all five stellar sources (two B stars, three white dwarfs) but not the hot bubble. Fluxes are attenuated by mean column densities NH I = 1018 cm−2 and NHe I = 1017 cm−2. Spectra and ionization fractions are shown at various depths into the cloud, with distance intervals from step 0 (external surface) to step 20 (entering heliosphere) and step length ΔL = 5 × 1017 cm. Top: attenuated spectra with depth into the local cloud, with the bottom spectrum (black) showing the attenuated flux seen at Earth. Bottom: ionization fractions of H and He with depth.
Paper: Ionization Sources of the Local Interstellar Clouds: Two B Stars, Three White Dwarfs, and the Local Hot Bubble
Authors: J. Michael Shull, Rachel M. Curran, Michael W. Topping, Jonathan D. Slavin
Figure caption: FUV and EUV spectra for β CMa from a model atmosphere computed with the non-LTE line-blanketed code WM-basic for effective temperature Teff = 25,000 K and surface gravity ﹩\mathrm{log}g=3.70﹩. Left: flux distribution ﹩\mathrm{log}{F}_{\lambda }﹩ from 500 to 1200 Å, showing the LL decrement at 912 Å. Right: flux distribution from 228 to 550 Å. The absence of an edge at the He I ionization limit (504 Å) is a result of non-LTE effects from back-warming of the upper atmosphere from a wind in early B-type stars.
Paper: Ionization Sources of the Local Interstellar Clouds: Two B Stars, Three White Dwarfs, and the Local Hot Bubble
Authors: J. Michael Shull, Rachel M. Curran, Michael W. Topping, Jonathan D. Slavin
Figure caption: The location of β CMa on the Hertzsprung–Russell diagram is shown for our derived parameters, ﹩\mathrm{log}(L/{L}_{\odot })=4.41\pm 0.06﹩ and Teff = 25,180 ± 1120 K, based on new radius R = 8.44 ± 0.56 R⊙ and parallax distance d = 151 ± 5 pc. The evolutionary tracks are from L. L. Brott et al. (2011) with Milky Way metallicities and initial masses labeled from 7 to 30 M⊙. The location of ϵ CMa (J. M. Shull et al. 2025) is shown for comparison.
Paper: Ionization Sources of the Local Interstellar Clouds: Two B Stars, Three White Dwarfs, and the Local Hot Bubble
Authors: J. Michael Shull, Rachel M. Curran, Michael W. Topping, Jonathan D. Slavin
Figure caption: Locations of the five stars (yellow circles) that dominate the ionization of the local clouds, shown in Galactic coordinates (ℓ, b) centered on (0, 0). Locations are plotted on the All-sky New Horizons Alice Lyα map (G. R. Gladstone et al. 2025) taken at 57 au from the Sun. Wavy lines indicate the outlines of four of the important local interstellar clouds (LIC in red, Aql in green, Blue in blue, and G in tan). The map also indicates locations of the Sun (right edge), north and south ecliptic poles (NEP, SEP), notable stars and galaxies, and the “upstream and downstream” directions of flow of interstellar H I through the solar system and interplanetary medium (IPM). Black circles show the ∼90,000 stars in the M. A. Velez et al. (2024) catalog of potential sources of FUV emission.
Paper: Ionization Sources of the Local Interstellar Clouds: Two B Stars, Three White Dwarfs, and the Local Hot Bubble
Authors: J. Michael Shull, Rachel M. Curran, Michael W. Topping, Jonathan D. Slavin
Figure caption: Model of attenuated EUV spectrum and ionization fractions of H and He. Parameters are the same as in Figure 4, but we now include the line emission from the LHB (solar abundances) along with the five stellar sources. This produces elevated He+ ionization fractions deeper into the cloud. Spectra and ionization are shown at various depths, with distance intervals from step 0 (external surface) to step 20 (entering heliosphere) and step length ΔL = 5 × 1017 cm. Top: ionizing spectra at several distances into the cloud, from surface to Earth. Bottom: ionization fractions of H and He with depth.
Paper: Lost in the FoG: Pitfalls of Models for Large-scale Hydrogen Distributions
Authors: Calvin K. Osinga, Benedikt Diemer, Francisco Villaescusa-Navarro
Figure caption: Comparison of the strength of FoG suppression for H I (σHI) and matter (σm) at different scales, with lighter colors corresponding to larger scales. The isopower contour lines delineate, at some k, PHI(k∥ = k, k⊥ = k) and Pm(k∥ = k, k⊥ = k) such that they intersect at points along the dotted line. Defining contours in this way enables easier comparisons of the contour shapes, although the matter and H I contours represent different power values and spacings. We smooth the contours with a Gaussian filter (σ = 0.8) to reduce noise, which does not impact our conclusions. H I contour lines are more vertically stretched than matter at k ≲ 0.75 h cMpc−1, implying stronger FoG suppression. Conversely, contour lines starting at k ≳ 0.75 h cMpc−1 exhibit the opposite trend: matter is stretched more than H I.
Paper: Lost in the FoG: Pitfalls of Models for Large-scale Hydrogen Distributions
Authors: Calvin K. Osinga, Benedikt Diemer, Francisco Villaescusa-Navarro
Figure caption: The contribution of shot noise to tracer biases, determined by comparing two bias definitions: our fiducial definition with shot noise included (darker colors, Equation (2)) and an alternative without shot noise (lighter colors, Equation (B2)). The large-scale values agree between the two definitions for all tracers at all redshifts, although the biases without shot noise are more scale dependent. The differences between the definitions are small for large populations with small shot noise terms, such as red galaxies. Both definitions produce the same errors, although they can alter what errors we associate with assuming a constant bias. Definitions with shot noise mitigate the scale-dependence of the bias, which reduces constant-bias error.
Paper: GX 340+0: In and Out of Focus
Authors: S. Li, R. M. Ludlam, D. J. K. Buisson, M. Sudha, S. Rossland, G. Mastroserio, M. C. Brumback, J. A. García, B. W. Grefenstette, F. La Monaca, E. A. Saavedra, A. Di Marco
Figure caption: HID for the focused observations. Only data from FPMA is shown for clarity. Left panel shows observations from 2018, right panel shows observations from 2024. The blue boxes/lines indicate how the different branches are divided. The hardness ratio is defined as the hard energy band from 10–16 keV divided by the soft energy band from 3–10 keV, while the total intensity is the 3–16 keV band. The HID is created with light curves binned at 128 s time bins. Naming scheme for the focused observations is provided in Table A1.
Paper: Lost in the FoG: Pitfalls of Models for Large-scale Hydrogen Distributions
Authors: Calvin K. Osinga, Benedikt Diemer, Francisco Villaescusa-Navarro
Figure caption: Comparisons of the H I (brown) and galaxy (blue and red) biases from the primary volumes of TNG100 (dark colors) and TNG300 (light). The galaxy biases agree between the two resolutions, particularly at early redshifts and for red galaxies. Conversely, the TNG100 H I bias is vertically offset by ∼25% from TNG300, although their scale-dependencies agree. Our predictions of model errors are robust against the vertical offset because they are not dependent on the precise value of the H I bias.
Paper: Lost in the FoG: Pitfalls of Models for Large-scale Hydrogen Distributions
Authors: Calvin K. Osinga, Benedikt Diemer, Francisco Villaescusa-Navarro
Figure caption: Comparison of the models for the H I autopower and H I × Blue cross-power spectra at z = 1, with lighter colors corresponding to simpler models. H I × Blue deviates from the cross-power spectrum comparably to or by less than equivalent H I autopower spectrum models, suggesting that H I × Blue may be easier to model than the H I autopower spectra.
Paper: GX 340+0: In and Out of Focus
Authors: S. Li, R. M. Ludlam, D. J. K. Buisson, M. Sudha, S. Rossland, G. Mastroserio, M. C. Brumback, J. A. García, B. W. Grefenstette, F. La Monaca, E. A. Saavedra, A. Di Marco
Figure caption: The long-term MAXI hardness ratio (top) and Burst Alert Telescope (BAT) 15–50 keV light curve (bottom) of GX 340+0. Vertical solid green lines indicate focused NuSTAR observations, whereas dashed black lines are SL observations. Note that some lines are thicker because multiple observations occurred close together.
Paper: Lost in the FoG: Pitfalls of Models for Large-scale Hydrogen Distributions
Authors: Calvin K. Osinga, Benedikt Diemer, Francisco Villaescusa-Navarro
Figure caption: Redshift evolution of the ratio of the H I autopower spectra from each model over the one calculated directly from TNG300, with earlier redshifts shown in darker colors. The top two panels have logarithmic y-axes due to their large errors. All models perform worse at later redshifts due to the increasing presence of nonlinearities and baryonic effects. The z = 1 H I bias remains constant at small scales, allowing tK+cB+FoG to agree within 10% of the actual power spectrum until k ∼ 1 h cMpc−1.
Paper: Lost in the FoG: Pitfalls of Models for Large-scale Hydrogen Distributions
Authors: Calvin K. Osinga, Benedikt Diemer, Francisco Villaescusa-Navarro
Figure caption: Redshift evolution of the ratio of H I × Blue from each model over the one calculated directly from TNG300, with earlier redshifts shown in dark colors. All models perform worse at later redshifts, particularly at z = 0, similar to the trend in Figure 14.
Paper: GX 340+0: In and Out of Focus
Authors: S. Li, R. M. Ludlam, D. J. K. Buisson, M. Sudha, S. Rossland, G. Mastroserio, M. C. Brumback, J. A. García, B. W. Grefenstette, F. La Monaca, E. A. Saavedra, A. Di Marco
Figure caption: Ratio of the data to the double thermal continuum model on the Fe line region for all focused observations (first four rows in red) and three select SL observations (final row in blue). The SL data have lower S/N than the focused data, as evidenced by the larger 1σ error bars on the data points. Given the large number of SL observations considered, only one example in each branch is provided for clarity.
Paper: GX 340+0: In and Out of Focus
Authors: S. Li, R. M. Ludlam, D. J. K. Buisson, M. Sudha, S. Rossland, G. Mastroserio, M. C. Brumback, J. A. García, B. W. Grefenstette, F. La Monaca, E. A. Saavedra, A. Di Marco
Figure caption: Variation in blackbody temperature kTBB (upper) and disk temperature kTin (lower) over time for observations from 2013 to 2024. The two panels display the temperatures for each observation, arranged sequentially along the x-axis with equal spacing between points to emphasize individual observation order. Colors and marker shapes represent different branches: the horizontal branch (HB) is in red, normal branch (NB) in orange, soft apex (SA) in blue, and flaring branch (FB) in purple. Within the HB and NB, the upper horizontal (UH) is denoted by a square, lower horizontal (LH) by a downward pointing triangle, upper normal (UN) by a diamond, and lower normal (LN) sections by a pentagon. Observations from stray light (SL) in the HB and NB are marked by a circle and hexagon. For additional distinction between observation types, shaded regions indicate focused observations. Note that Figure 1 shows the time separation of the observations in MJD.
Paper: GX 340+0: In and Out of Focus
Authors: S. Li, R. M. Ludlam, D. J. K. Buisson, M. Sudha, S. Rossland, G. Mastroserio, M. C. Brumback, J. A. García, B. W. Grefenstette, F. La Monaca, E. A. Saavedra, A. Di Marco
Figure caption: HID for SL observations. The HID is constructed using the same energy bands as Figure 2 with light curves using 512 s time bins. The combined plot on the bottom right shows the HID of all 25 observations concurrently. The red boxes indicate how the different branches are divided (HB, NB, and FB). Information (including naming scheme) for each SL observation is provided in Table A1.
Paper: GX 340+0: In and Out of Focus
Authors: S. Li, R. M. Ludlam, D. J. K. Buisson, M. Sudha, S. Rossland, G. Mastroserio, M. C. Brumback, J. A. García, B. W. Grefenstette, F. La Monaca, E. A. Saavedra, A. Di Marco
Figure caption: The relation between reflection fraction (frefl) and ionization parameter (﹩\mathrm{log}(\xi )﹩) from the focused observations. The Spearman rank correlation factor is 0.55, indicating that there may be a weak correlation between higher reflection fractions and increased ionization.
Paper: GX 340+0: In and Out of Focus
Authors: S. Li, R. M. Ludlam, D. J. K. Buisson, M. Sudha, S. Rossland, G. Mastroserio, M. C. Brumback, J. A. García, B. W. Grefenstette, F. La Monaca, E. A. Saavedra, A. Di Marco
Figure caption: Example SL images for GX 340+0 considered herein. The shaded area indicates the general SL illumination pattern. The green circle marks the specific SL region used for spectral extraction of GX 340+0, which also serves as the background region, as detailed in Section 2.2. Regions marked by blue circles are excluded from the analysis. Additional illumination patterns on the detectors are from a different SL source. See Table A1 for more information about the SL observations.
Paper: GX 340+0: In and Out of Focus
Authors: S. Li, R. M. Ludlam, D. J. K. Buisson, M. Sudha, S. Rossland, G. Mastroserio, M. C. Brumback, J. A. García, B. W. Grefenstette, F. La Monaca, E. A. Saavedra, A. Di Marco
Figure caption: An example SL spectrum (black) showing the background components modeled by NUSKYBGD. Red dashed–dotted line is the aperture CXB, green dashed line is focused CXB, blue dotted line is the internal line emission, and orange solid line is the internal continuum.
Paper: GX 340+0: In and Out of Focus
Authors: S. Li, R. M. Ludlam, D. J. K. Buisson, M. Sudha, S. Rossland, G. Mastroserio, M. C. Brumback, J. A. García, B. W. Grefenstette, F. La Monaca, E. A. Saavedra, A. Di Marco
Figure caption: Example spectra in various branches to illustrate the quality of the data for focused and SL observations. The top two rows show an example spectrum for focused observations in each branch. The bottom row shows an example spectrum of SL observations in each branch. The count rate per energy bin in SL data is more than 10 times lower than in the focused observations.
Paper: GX 340+0: In and Out of Focus
Authors: S. Li, R. M. Ludlam, D. J. K. Buisson, M. Sudha, S. Rossland, G. Mastroserio, M. C. Brumback, J. A. García, B. W. Grefenstette, F. La Monaca, E. A. Saavedra, A. Di Marco
Figure caption: Ratio of the data to the overall model including reflection in focused and select SL observations to demonstrate the goodness of fit. The top six panels show the ratio plot for all focused observations, while the lower three panels show an example of the ratio plot for each branch of the SL data.
Paper: GX 340+0: In and Out of Focus
Authors: S. Li, R. M. Ludlam, D. J. K. Buisson, M. Sudha, S. Rossland, G. Mastroserio, M. C. Brumback, J. A. García, B. W. Grefenstette, F. La Monaca, E. A. Saavedra, A. Di Marco
Figure caption: Example of unfolded spectra for focused observations in each branch to show the contribution of the reflection (blue dotted–dashed line) and disk (green dashed line) components.
Paper: Utilizing Maximum Variability to Discern TDE Emission from AGN Flares
Authors: Samaresh Mondal, K. Decker French
Figure caption: The distribution of sampling time in days for Swift-XRT and XMM-Newton AGN light curves. The x-axis represents the time difference between two consecutive measurements in the light curves. The colors represent light curves with varying numbers of observation points.
Paper: Utilizing Maximum Variability to Discern TDE Emission from AGN Flares
Authors: Samaresh Mondal, K. Decker French
Figure caption: Comparison of MaxVar for AGNs and TDEs. The red continuous line indicates the MaxVar computed from simulated light curves with a regular cadence of 5 days, and the shaded regions indicate the 1σ, 2σ, and 3σ confidence regions.
Paper: Utilizing Maximum Variability to Discern TDE Emission from AGN Flares
Authors: Samaresh Mondal, K. Decker French
Figure caption: Comparison of different models fit to Swift-XRT AGN SF (top panel in log–log scale). A broken power-law model provides a better fit compared to a simple power-law model, which is visible in the data/model plot.
Paper: Utilizing Maximum Variability to Discern TDE Emission from AGN Flares
Authors: Samaresh Mondal, K. Decker French
Figure caption: The MaxVar computed for a single TDE following flux ﹩\propto \,{t}^{-\frac{5}{3}}﹩ law. The bottom panel shows the effect of the observational gap after the first 30 days of regular monitoring. For the data set with gaps, we rebinned the MaxVar with bin size ﹩{\rm{\Delta }}{\rm{log}}({\rm{\Delta }}t)=0.2﹩ for smoothing.
Paper: Utilizing Maximum Variability to Discern TDE Emission from AGN Flares
Authors: Samaresh Mondal, K. Decker French
Figure caption: The ratio of MaxVar obtained from light curves with 70% and no gap for the case of AGNs and TDEs. The effect of gaps is stronger at shorter timescales, which can significantly reduce the MaxVar in the case of AGNs.
Paper: Utilizing Maximum Variability to Discern TDE Emission from AGN Flares
Authors: Samaresh Mondal, K. Decker French
Figure caption: The comparison of MaxVar between AGNs and TDEs for the different data sets. At a longer timescale, the MaxVar of TDEs is much higher than AGNs due to the fact that TDEs follow a monotonic decline.
Paper: Utilizing Maximum Variability to Discern TDE Emission from AGN Flares
Authors: Samaresh Mondal, K. Decker French
Figure caption: SF (in log–log scale) of the AGN sample computed from the XMM-Newton and Swift-XRT data sets. The continuous lines indicate a simple power-law model fit to the data. The dashed lines indicate a slightly different power-law index obtained in a similar study by F. Vagnetti et al. (2011) using XMM-Newton and Swift-XRT data sets.
Paper: Utilizing Maximum Variability to Discern TDE Emission from AGN Flares
Authors: Samaresh Mondal, K. Decker French
Figure caption: The line connected with dots indicates the MaxVar obtained from the actual Swift-XRT light curves of AGNs, and the lines without dots indicate the MaxVar obtained from simulated light curves.
Paper: Utilizing Maximum Variability to Discern TDE Emission from AGN Flares
Authors: Samaresh Mondal, K. Decker French
Figure caption: Comparison of different models fit to AGN SF (top panel in log–log scale) for XMM-Newton data sets. There is a significant improvement in the fit after incorporating a broken power-law model over a simple power-law model, which can be seen in the data/model plot.
Paper: Signatures of Black Hole Seeding on the M•–σ Relation: Predictions from the BRAHMA Simulations
Authors: Jonathan Kho, Aklant Kumar Bhowmick, Paul Torrey, Alex M. Garcia, Niusha Ahvazi, Laura Blecha, Mark Vogelsberger
Figure caption: The M•–σ, M•–M*, and M*–σ relations for the four BRAHMA boxes and TNG. Each plot shows the relation for redshifts z = 7, 5, 3, 1, 0 to provide a sense of their redshift evolution. Redshifts greater than z = 7 are not included because of the poor statistics our relatively small volumes would provide at these times. The M•–σ and M•–M* columns show the local relations as reported by KH13 and RV15, and the M•–M* plots additionally show the high-z inferred relation found by P23. The red shaded region is the rms scatter of the RV15 relation. These columns also show high-z AGN as reported by M24b and J25.
Paper: Signatures of Black Hole Seeding on the M•–σ Relation: Predictions from the BRAHMA Simulations
Authors: Jonathan Kho, Aklant Kumar Bhowmick, Paul Torrey, Alex M. Garcia, Niusha Ahvazi, Laura Blecha, Mark Vogelsberger
Figure caption: Comparison of the BRAHMA and TNG simulations’ M•–σ relations at z = 5, 0. The local relation found by KH13 is plotted in both panels for reference, and high-z AGN candidates found by M24b and J25 are shown in purple and blue in the z = 5 panel. With the exception of our most lenient seed model, the simulations all begin undermassive to the local relation at high-z and converge to this relation by z = 0. The different BRAHMA seed models are clearly differentiable for all σ’s at z = 5 via their different normalizations, and are still differentiable for 101.7 km s−1  ≲ σ ≲ 101.9 km s−1at z = 0.