adsabs/AstroCLIMB huggingface dataset:
Paper: Under Pressure: Decoding the Effect of High Densities on Derived Nebular Properties
Authors: Zorayda Martinez, Danielle A. Berg, Bethan L. James, Karla Z. Arellano-Córdova, Daniel P. Stark, Peter Senchyna, Evan D. Skillman, Noah S. J. Rogers, John Chisholm
Figure caption: The emissivities of N IV] λλ1483,1487, N III] λ1750, and O III] λλ1661,1666, determined with PyNeb, are shown in the left column, while the right column shows the same for the emissivities of [O II] λλ3727,3730, [N II] λ6584, and [O II] λλ7321,7332. The upper panels show emissivities as a function of Te (5,000 to 25,000 K), and the lower panels describe these emissivities as a function of ne (102–109 cm−3). Note that we show the full range of densities used in photoionization models to show the different ranges each line is sensitive over. The top panels illustrate that ne has a larger impact on optical lines that have lower critical ne, while the bottom panels show that UV lines are more impacted by Te than the optical lines given that they have higher excitation energies.
Paper: Under Pressure: Decoding the Effect of High Densities on Derived Nebular Properties
Authors: Zorayda Martinez, Danielle A. Berg, Bethan L. James, Karla Z. Arellano-Córdova, Daniel P. Stark, Peter Senchyna, Evan D. Skillman, Noah S. J. Rogers, John Chisholm
Figure caption: Comparison of different diagnostics of ionization parameter from Cloudy photoionization models (see Section 4). The plots contains models that span metallicities from 0.05 Z⊙ to 0.4 Z⊙, as indicated by the color coding, while the size of the circle markers corresponds to burst ages between 106.0 and 107.0. The spread in models by varying ne = 102–106 cm−3 is indicated by the shaded regions, where the dashed line represents the maximum ne = 106 cm−3 model. Left: the UV N43﹩\mathrm{log}{U}_{\mathrm{high}}﹩ diagnostic versus the classic optical O32﹩\mathrm{log}{U}_{\mathrm{int}.}﹩ diagnostic. The large spread is due to the O32 dependence on density, indicating it is a less reliable diagnostic of ionization parameter when the density in the high-ionization zone is unknown. Right: the UV N43﹩\mathrm{log}{U}_{\mathrm{high}}﹩ diagnostic versus the optical Ar43﹩\mathrm{log}{U}_{\mathrm{high}}﹩ diagnostic introduced by D. A. Berg et al. (2021). The tight relationship between N43 and Ar43 is nearly density independent, suggesting N43 can be used as a robust ﹩\mathrm{log}{U}_{\mathrm{high}}﹩ diagnostic.
Paper: Under Pressure: Decoding the Effect of High Densities on Derived Nebular Properties
Authors: Zorayda Martinez, Danielle A. Berg, Bethan L. James, Karla Z. Arellano-Córdova, Daniel P. Stark, Peter Senchyna, Evan D. Skillman, Noah S. J. Rogers, John Chisholm
Figure caption: A grid of plots displaying different sets of Cloudy photoionization models at various relative N/O abundances. Every plot contains models that span metallicities from 0.05 Z⊙ to 0.4 Z⊙, which correspond to different color models going from darkest (lowest metallicity) to lightest (highest metallicity). Each panel has a different emission line ratio on the y-axis. From left to right, these are N3O3, N4O3, and N2O2. In each of the plots, circles correspond to models at ne of 102.0, triangles are models at 104.0, and squares are models at 107.0. Additionally, the size of the circle markers corresponds to burst ages between 106.0 and 107.0. Finally, the spread in models from ﹩\mathrm{log}U﹩ of −2.0 to −1.0 is indicated by points of decreasing opacity. The N/O tracers each increase monotonically with relative N/O abundance and experience varying degrees of spread at a given N/O due to metallicity, ionization parameter, density, and burst age.
Paper: Under Pressure: Decoding the Effect of High Densities on Derived Nebular Properties
Authors: Zorayda Martinez, Danielle A. Berg, Bethan L. James, Karla Z. Arellano-Córdova, Daniel P. Stark, Peter Senchyna, Evan D. Skillman, Noah S. J. Rogers, John Chisholm
Figure caption: Cloudy models of Te-sensitive [O III] emission line ratios versus a range of ne =102–107 cm−3. The circle markers are the [O III] λ4364/[O III] λ5008 ratio, the triangles are O III] λ1666/[O III] λ5008, and the diamonds are O III] λ1666/[O III] λ4364. The color bar on the right indicates the Te in each model. The O III] λ1666/[O III] λ4364 line ratio is nearly constant over this density range due to the high critical densities of both lines. However, the two ratios involving [O III] λ5008 both change significantly above ne ≳ 105 cm−3 due to its lower critical density.
Paper: Under Pressure: Decoding the Effect of High Densities on Derived Nebular Properties
Authors: Zorayda Martinez, Danielle A. Berg, Bethan L. James, Karla Z. Arellano-Córdova, Daniel P. Stark, Peter Senchyna, Evan D. Skillman, Noah S. J. Rogers, John Chisholm
Figure caption: The modeled emission line ratios, O3, O2, and O32, from Cloudy across ne =102–107 cm−3, the range over which we expect these diagnostics to be sensitive. The circles show O3, the diamonds are O2, and the triangles describe O32. The colors show different metallicities ranging from 0.05 Z⊙ and 0.40 Z⊙ given in the color bar on the right. O3 and O2 begin to change rapidly after the ne,crit of [O III] and [O II], respectively, and, as a result, the O32 ratio changes drastically at ne  > 103 cm−3.
Paper: Under Pressure: Decoding the Effect of High Densities on Derived Nebular Properties
Authors: Zorayda Martinez, Danielle A. Berg, Bethan L. James, Karla Z. Arellano-Córdova, Daniel P. Stark, Peter Senchyna, Evan D. Skillman, Noah S. J. Rogers, John Chisholm
Figure caption: The Cloudy model relationship between both O32 (upper) and N43 (lower) and ionization parameter, U. The left column shows 3D plots of the bicubic fits for each grid of models. Marker color corresponds to ne ranging from 102 to 106 cm−3. In the right column, we show a 2D projection where the range of ne is shown by the shaded region. The metallicities range between 0.05 Z⊙ and 0.40 Z⊙ as indicated by the color bar in the upper-right plot. Clearly, ne has a large impact on O32; however, N43 is much more robust to extreme ne.
Paper: Under Pressure: Decoding the Effect of High Densities on Derived Nebular Properties
Authors: Zorayda Martinez, Danielle A. Berg, Bethan L. James, Karla Z. Arellano-Córdova, Daniel P. Stark, Peter Senchyna, Evan D. Skillman, Noah S. J. Rogers, John Chisholm
Figure caption: We show the ionization fractions as a function of ﹩\mathrm{log}U﹩ for both O (left) and N (right). The different marker shapes correspond to the different ionization species, where circles are neutral, squares are singly ionized, diamonds are doubly ionized, and triangles are triply ionized species. The colors differentiate models of varying metallicity from 0.05 Z⊙ to 0.40 Z⊙. The marker size represents varying burst ages between 106.0 and 107.0 yr. Finally, the lines follow a single set of models at burst age of 106.7 yr and metallicity of 0.20  Z⊙. The dashed line distinguishes the model at 102 cm−3 from the model at 106 cm−3, which is described by a dotted line.
Paper: Under Pressure: Decoding the Effect of High Densities on Derived Nebular Properties
Authors: Zorayda Martinez, Danielle A. Berg, Bethan L. James, Karla Z. Arellano-Córdova, Daniel P. Stark, Peter Senchyna, Evan D. Skillman, Noah S. J. Rogers, John Chisholm
Figure caption: Rest-UV spectra for the Low-z Sample (see Section 2.1 and Table 1). The detected N IV] λλ1483,1487 (left) and N III] λ1750 (right) emission profiles are shown; four galaxies have N IV] λλ1483,1487 emission, and five have N III] λ1750 emission, but none have both. We plot the emission line fits (blue line) for the eight of these galaxies without reported N IV] and N III] line fluxes in the literature.
Paper: Mid-infrared Extinction toward the Galactic Center
Authors: Sebastiano D. von Fellenberg, Joseph M. Michail, S. P. Willner, Braden Seefeldt-Gail, Tamojeet Roychowdhury, Macarena Garcia Marin, Giovanni G. Fazio, Nicole M. Ford, Daryl Haggard, Joseph L. Hora, Howard A. Smith, Zach Sumners, Gunther Witzel
Figure caption: Hydrogen recombination line measurements for two apertures, centered on Sgr A* (left) and the Mini-spiral (right). The colored lines show the observed spectra after continuum subtraction and fringing correction, and the semitransparent lines show the spectra before the residual fringing correction. Each plot shows one of the lines with sufficient S/N (orange and brown lines). The gray line shows the λline = 7.46 μm recombination line profile scaled by the expected line ratio as given in Table 1. The respective apertures are shown in Figure 8.
Paper: SPYGLASS. VII-A. The Demographics and Ages of Small Nearby Young Associations
Authors: Ronan Kerr, Facundo Peŕez Paolino, Jonathan C. Tan, Joshua S. Speagle, 佳士 沈, Adam L. Kraus, José G. Fernández-Trincado, Keivan G. Stassun, Julio Chanamé
Figure caption: IMF-based mass corrections to all 15 associations where demographics are possible. The dark blue histogram shows the distribution of association members, and a smoothed version of that is shown in light blue. The orange curve shows the G. Chabrier (2005) IMF. The missing mass, shown in red, is computed using the volume between the G. Chabrier (2005) IMF and the smoothed version of the stellar mass distribution curve. This is used to compute the corrective factors for mass and number (CM,lm and CN,lm, respectively), which are annotated on each panel.
Paper: Mid-infrared Extinction toward the Galactic Center
Authors: Sebastiano D. von Fellenberg, Joseph M. Michail, S. P. Willner, Braden Seefeldt-Gail, Tamojeet Roychowdhury, Macarena Garcia Marin, Giovanni G. Fazio, Nicole M. Ford, Daryl Haggard, Joseph L. Hora, Howard A. Smith, Zach Sumners, Gunther Witzel
Figure caption: Continuum model (top left) and extinction law (top right) derived from a fit to the spectrum in the Sgr A* pixel. The black line and dots show the binned spectrum with an artificially added 3% log-normally distributed uncertainty. The gray lines show posterior samples of the extincted dust model. The panel below shows the χ2 residual. The right plot shows the derived extinction curves (Aλ). The orange line shows the median posterior model, and the black line shows the posterior samples. The dashed gray line shows the extinction law derived by T. K. Fritz et al. (2011). That law is based on the ISO/SWS observations by D. Lutz et al. (1996), which had an effective beam size of 14″ × 16″.
Paper: Mid-infrared Extinction toward the Galactic Center
Authors: Sebastiano D. von Fellenberg, Joseph M. Michail, S. P. Willner, Braden Seefeldt-Gail, Tamojeet Roychowdhury, Macarena Garcia Marin, Giovanni G. Fazio, Nicole M. Ford, Daryl Haggard, Joseph L. Hora, Howard A. Smith, Zach Sumners, Gunther Witzel
Figure caption: Dust distribution functions Ψ(T, τ9.8) for the Sgr A* pixel (left), the Mini-spiral (center), and IRS 29 (right). The insets in the Sgr A* and Mini-spiral panels show zoom-ins on the peaks of the respective posterior distributions.
Paper: Mid-infrared Extinction toward the Galactic Center
Authors: Sebastiano D. von Fellenberg, Joseph M. Michail, S. P. Willner, Braden Seefeldt-Gail, Tamojeet Roychowdhury, Macarena Garcia Marin, Giovanni G. Fazio, Nicole M. Ford, Daryl Haggard, Joseph L. Hora, Howard A. Smith, Zach Sumners, Gunther Witzel
Figure caption: 15 GHz VLA image. The gray box indicates the region used to model the Mini-spiral extinction, and the location of Sgr A* is indicated with a white star. The white circle in the bottom left indicates the beam size smoothed to JWST/MIRI 17.98 μm resolution.
Paper: Mid-infrared Extinction toward the Galactic Center
Authors: Sebastiano D. von Fellenberg, Joseph M. Michail, S. P. Willner, Braden Seefeldt-Gail, Tamojeet Roychowdhury, Macarena Garcia Marin, Giovanni G. Fazio, Nicole M. Ford, Daryl Haggard, Joseph L. Hora, Howard A. Smith, Zach Sumners, Gunther Witzel
Figure caption: Posterior distribution of the optical depth law τ(λ) defined in Equation (1). Different colors show the optical depths for different regions. The dashed line shows the optical depth profile by F. Kemper et al. (2004), which serves as a prior model and from which we allowed a multiplicative deviation.
Paper: Mid-infrared Extinction toward the Galactic Center
Authors: Sebastiano D. von Fellenberg, Joseph M. Michail, S. P. Willner, Braden Seefeldt-Gail, Tamojeet Roychowdhury, Macarena Garcia Marin, Giovanni G. Fazio, Nicole M. Ford, Daryl Haggard, Joseph L. Hora, Howard A. Smith, Zach Sumners, Gunther Witzel
Figure caption: Example of defringing using the factor-analysis approach for the λ = 19.057 μm recombination line. The left three plots in the top row show the FA component fields with contour lines showing the channel 4 mean flux density. The left three plots in the bottom row show the respective FA basis functions, the mean posterior GP fit (blue line), and the posterior samples (gray lines). The rightmost two plots show the observed spectrum with the derived continuum model (top panel, black and gray lines show continuum models) and the corrected spectrum (bottom panel).
Paper: Mid-infrared Extinction toward the Galactic Center
Authors: Sebastiano D. von Fellenberg, Joseph M. Michail, S. P. Willner, Braden Seefeldt-Gail, Tamojeet Roychowdhury, Macarena Garcia Marin, Giovanni G. Fazio, Nicole M. Ford, Daryl Haggard, Joseph L. Hora, Howard A. Smith, Zach Sumners, Gunther Witzel
Figure caption: Dust continuum models and derived extinction laws for different regions observed with JWST MIRI/MRS. The left panel shows the continuum fits to apertures centered on Sgr A*, the Mini-spiral, and the MIR-bright star IRS 29N. The right panel shows the corresponding extinction laws. The gray dashed line shows the MIR extinction law derived by T. K. Fritz et al. (2011).
Paper: Explainable Machine Learning Classification of Chandra X-Ray Sources: SHAP Analysis of Multiwavelength Features
Authors: Shivam Kumaran, Samir Mandal, Sudip Bhattacharyya
Figure caption: Scatterplot showing source clustering for positive and negative classes for the features (or their combination) picked out from the feature–feature interaction matrix. The contour lines show the PDF, starting with 0.1 at the innermost level, and the difference between successive levels is 0.1. The decision boundary is shown with the solid magenta line and the uncertainties in a blue shade. The top panel shows clustering corresponding to the highest FFI (g-sdss versus W1 for AGN, J versus Rp for star, and J − H versus m − csc for YSO in Figure 8. The bottom panel shows clustering for other combinations of features picked from the interaction matrix having high FFI values. See Section 4.3 for details.
Paper: Explainable Machine Learning Classification of Chandra X-Ray Sources: SHAP Analysis of Multiwavelength Features
Authors: Shivam Kumaran, Samir Mandal, Sudip Bhattacharyya
Figure caption: General workflow for local explanation of a black-box classifier model output using SHAP analysis. Starting with the source’s feature set Xs, the LightGBM model f generates a raw model output f(Xs), which is converted to CMP for the given class using the sigmoid (σ) function. This chain is indicated by black arrows. The blue arrows show the workflow of allocating the model output, f(Xs), to the feature contributions using SHAP analysis. SHAP value for each feature, ϕs(xi), is calculated from Equation (1). The green arrows outline equivalence between features’ SHAP values and the model raw output f(Xs) with additional model offset ϕ0. See Section 3 for details.
Paper: Explainable Machine Learning Classification of Chandra X-Ray Sources: SHAP Analysis of Multiwavelength Features
Authors: Shivam Kumaran, Samir Mandal, Sudip Bhattacharyya
Figure caption: Class-wise GFI indicating the relative feature importance for AGN, stars, and YSOs. The GFI is the expected SHAP values normalized relative to the highest expectation value within each class. See the text for details.
Paper: Explainable Machine Learning Classification of Chandra X-Ray Sources: SHAP Analysis of Multiwavelength Features
Authors: Shivam Kumaran, Samir Mandal, Sudip Bhattacharyya
Figure caption: Relative FFI between the top five GFI (Figure 6) is shown for AGNs (left), stars (center), and YSO (right). Each FFI strength is normalized and represented by a color code.
Paper: Explainable Machine Learning Classification of Chandra X-Ray Sources: SHAP Analysis of Multiwavelength Features
Authors: Shivam Kumaran, Samir Mandal, Sudip Bhattacharyya
Figure caption: Variation of normalized SHAP values for a few selected features (xi). The blue scatterplot corresponds to individual sources. The scatter points are grouped in 15 equal bins on the X-axis. The black square points are the average value along the Y-axis in each bin and are placed at the center of the bins on the X-axis. The solid blue vertical line shows the threshold value where the trend line (black curve) crosses the zero SHAP value (shown with a red line) on the Y-axis. The error in the threshold is shown with vertical blue dashed lines. See the text for details.
Paper: Erratum: “Ab-initio General-relativistic Neutrino-radiation Hydrodynamics Simulations of Long-lived Neutron Star Merger Remnants to Neutrino Cooling Timescales” (2023, ApJ, 959, 46)
Authors: David Radice, Sebastiano Bernuzzi
Figure caption: Profile of the convective instability criterion χ for the ℓmix = 0 and ℓmix = ℓmix(ρ) as a function of the cylindrical radius ϱ (averaged over ϕ in the z = 0 plane), or along z (ℓmix = 0 model only).
Paper: Explainable Machine Learning Classification of Chandra X-Ray Sources: SHAP Analysis of Multiwavelength Features
Authors: Shivam Kumaran, Samir Mandal, Sudip Bhattacharyya
Figure caption: Local explanation for the source 2CXO J01422.8−005331. The raw output of the LightGBM model for this source is f(Xs) = 4.83. The individual features SHAP values ϕs(xi) are given on the X-axis for the top 10 features xi on the Y-axis. The sum of contributions from all remaining features is indicated with the “ARF” label in the last row.
Paper: Explainable Machine Learning Classification of Chandra X-Ray Sources: SHAP Analysis of Multiwavelength Features
Authors: Shivam Kumaran, Samir Mandal, Sudip Bhattacharyya
Figure caption: Comparison of the distribution of sources in the training dataset to the sources in the newly identified dataset on the optical (Gaia) and IR (WISE and 2MASS) color–magnitude diagram.
Paper: Modeling the Energy Release in Solar Eruptive Events
Authors: Bart van der Holst, Spiro K. Antiochos, Nishtha Sachdeva, Gabor Toth, Joel T. Dahlin, Tamas I. Gombosi
Figure caption: The CME configuration after 46 minutes of stitching. The signed radial magnetic field strength at the inner boundary is shown in saturated red–blue contours. The color contours in the y = 0 plane are for the electron temperature (top left), proton temperature (top right), radial velocity (bottom left), and the ratio of current to magnetic field strength (bottom right). The field lines are colored to visualize the various flux systems: the overarching helmet streamer in black, flux rope formed by the flare reconnection in purple with a sheared core in gray, and the neighboring high-latitude arcades in red and green.
Paper: Modeling the Energy Release in Solar Eruptive Events
Authors: Bart van der Holst, Spiro K. Antiochos, Nishtha Sachdeva, Gabor Toth, Joel T. Dahlin, Tamas I. Gombosi
Figure caption: The CME configuration after 14 minutes of stitching. The signed radial magnetic field strength at the inner boundary is shown in saturated red–blue contours. The color contours in the y = 0 plane are for the electron temperature (top left), proton temperature (top right), radial velocity (bottom left), and the ratio of current to magnetic field strength (bottom right). The field lines are colored to visualize the various flux systems: the overarching helmet streamer in black, breakout arcade in gray, and the neighboring high-latitude arcades in red and green.
Paper: Modeling the Energy Release in Solar Eruptive Events
Authors: Bart van der Holst, Spiro K. Antiochos, Nishtha Sachdeva, Gabor Toth, Joel T. Dahlin, Tamas I. Gombosi
Figure caption: (Left) Initial bipole configuration embedded in a dipolar solar wind. The signed radial magnetic field strength is shown in saturated red–blue contours. Selected field lines show the arcade overlying the PIL. (Right) Sheared arcade after 2 minutes of stitching.
Paper: Modeling the Energy Release in Solar Eruptive Events
Authors: Bart van der Holst, Spiro K. Antiochos, Nishtha Sachdeva, Gabor Toth, Joel T. Dahlin, Tamas I. Gombosi
Figure caption: (Left) The steady-state solar wind solution showing the radial velocity in color contour in the y = 0 plane. The radial magnetic field component is projected on the solar surface, and streamlines represent magnetic field lines by ignoring the out-of-plane component. (Right) Zoom-in to show the quadrupolar structure of the active region.
Paper: Modeling the Energy Release in Solar Eruptive Events
Authors: Bart van der Holst, Spiro K. Antiochos, Nishtha Sachdeva, Gabor Toth, Joel T. Dahlin, Tamas I. Gombosi
Figure caption: The CME at times t = 1 (left) and t = 3 hr (right). The signed radial magnetic field strength at the inner boundary is shown in saturated red–blue contours. The color contours in the y = 0 plane are for the radial velocity (top) and proton temperature (bottom). The translucent gray-colored surface identifies the shock as (∇ · u)Δr ≤ −60 km s−1. For the left panels we have an additional constraint that the shock velocity is ≥200 km s−1, while for the right panels it is ≥400 km s−1.
Paper: Modeling the Energy Release in Solar Eruptive Events
Authors: Bart van der Holst, Spiro K. Antiochos, Nishtha Sachdeva, Gabor Toth, Joel T. Dahlin, Tamas I. Gombosi
Figure caption: The radial velocity component normalized to the Alfvén and magnetoacoustic speed along the x-axis from x = −1.05 to x = −1.35 R⊙.
Paper: Modeling the Energy Release in Solar Eruptive Events
Authors: Bart van der Holst, Spiro K. Antiochos, Nishtha Sachdeva, Gabor Toth, Joel T. Dahlin, Tamas I. Gombosi
Figure caption: Zoom-in of Figure 4 to show the flare reconnection.
Paper: Eclipsing Stellar Flare on the Demon Star Algol Binary System Observed during the MAXI–NICER Follow-up Campaign in 2018
Authors: Kazuya Nakayama, Wataru Buz Iwakiri, Teruaki Enoto, Shun Inoue, Yuta Notsu, Keith Gendreau, Zaven Arzoumanian, Kenji Hamaguchi, Tatehiro Mihara
Figure caption: The observed configurations around and during the second eclipse shown in the line of sight of Algol and two possible examples of the flare. The upper panels (a1)–(a3) show the flare occurring in the midlatitude region of the southern hemisphere of Algol B (Example A), whereas the lower panels (b1)–(b3) show the flare in the low-latitude region of the northern hemisphere (Example B). The green arrows indicate the moving orbital direction of Algol B. As the orbital motion progresses, the flare loop moves to the near side due to the tidally locked rotation of Algol B. Panels (a1) and (b1) correspond to the eclipse start (ϕorb = 0.414), when the flare loop begins to be obscured by Algol A. Panels (a2) and (b2) are at the center of the eclipse (ϕorb = 0.468), when 80% of the flare loop is obscured. Panels (a3) and (b3) are the end of the eclipse (ϕorb = 0.522), when the flare loop completely moves out of the region blocked by Algol A.