adsabs/AstroCLIMB huggingface dataset:
Paper: The Dark Matter Content of Milky Way Dwarf Spheroidal Galaxies: Draco, Sextans, and Ursa Minor
Authors: Hao Yang, Wenting Wang, Ling Zhu, Ting S. Li, Sergey E. Koposov, Jiaxin Han, Songting Li, Rui Shi, Monica Valluri, Alexander H. Riley, Arjun Dey, Constance Rockosi, Carles G. Palau, Jessica Nicole Aguilar, Steven Ahlen, David Brooks, Todd Claybaugh, Andrew Cooper, Axel de la Macorra, Peter Doel, Simone Ferraro, Jaime E. Forero-Romero, Enrique Gaztañaga, Satya Gontcho A Gontcho, Alma Xochitl Gonzalez Morales, Gaston Gutierrez, Julien Guy, Klaus Honscheid, Mustapha Ishak, Dick Joyce, Robert Kehoe, Theodore Kisner, Namitha Kizhuprakkat, Anthony Kremin, Ofer Lahav, Martin Landriau, Laurent Le Guillou, Gustavo E. Medina, Aaron Meisner, Ramon Miquel, Nathalie Palanque-Delabrouille, Francisco Prada, Ignasi Pérez-Ràfols, Graziano Rossi, Eusebio Sanchez, David Schlegel, Michael Schubnell, Joseph Harry Silber, David Sprayberry, Gregory Tarlé, Benjamin Alan Weaver, Rongpu Zhou, Hu Zou
Figure caption: Distributions of LOSV errors for Draco member stars, observed by DESI MWS (blue) or by M. G. Walker et al. (2023; red). The black vertical dashed line is the intrinsic LOSV dispersion of Draco (see Table 1).
Paper: Simulations of Flare Chemistry in Brown Dwarf Companions to Active M Dwarfs
Authors: Aidan Gibbs, Michael P. Fitzgerald
Figure caption: Temperature-coupled photochemistry in response to a single 1034 erg flare. The flare begins at 5 minutes. The initial (quiescent) atmospheric mixing profiles of each chemical species is shown with solid lines, and includes the effects of vertical mixing and photochemistry. We also show mixing profiles calculated for the same temperature profile, but without photochemistry (dashed), and without vertical mixing or photochemistry (i.e., equilibrium chemistry, dotted), so that the effect of both photochemistry and vertical mixing on the quiescent profiles can be seen. Red shading indicates a decrease in abundance compared to the initial mixing profile, while blue shading indicates an increase in abundance. The temperature-coupled simulation is limited to 2 hr due to computational cost.
Paper: The Relation between the Optical Variability Timescale, Magnetic Field of Jets, and Black Hole Spin in Active Galactic Nuclei
Authors: Yongyun Chen, 永云 陈, Qiusheng Gu, 秋生 顾, Junhui Fan, 军辉 樊, Dingrong Xiong, 定荣 熊, Xiaoling Yu, 效龄 俞, Xiaotong Guo, 晓通 郭, Nan Ding, 楠 丁, Ting-Feng Yi, 庭丰 易
Figure caption: An example of fitting the zg-band light curve of B0215+015 with the DRW model using the fast Gaussian process solver celerite. The top panel shows the light curve of B0215+015, and the predicted light curve from the DRW model using the best-fitting, maximum likelihood parameters. The orange line is the best-fitting DRW model with 1σ uncertainty (orange shaded area). The lower-left panel shows the probability distributions for the fitted DRW parameters. The lower-right shows the normalized PSD and binned PSD with 1σ uncertainties. The orange shaded area is the model PSD with 1σ uncertainties. The gray line represents the Lomb–Scargle periodogram, while the black line denotes the binned Lomb–Scargle periodogram. The binned Lomb–Scargle periodogram was further fitted to a broken power law, as indicated by the red line. The red shaded regions indicate periods longer than 20% of the light curve duration (as shown in the lower-left and lower-right panels) and shorter than the mean cadence (as displayed in the lower-right panel). The discrepancies between the Lomb–Scargle periodogram and the model power spectral density (PSD) can be attributed to several factors: the inherent challenges in accurately estimating the PSD using Fourier-based methods on irregularly sampled light curves, the influence of flux measurement uncertainties on periodogram accuracy, and potential departures from the damped random walk (DRW) model (Z. Stone et al. 2022).
Paper: Simulations of Flare Chemistry in Brown Dwarf Companions to Active M Dwarfs
Authors: Aidan Gibbs, Michael P. Fitzgerald
Figure caption: Contribution of reactions and transport to the net change in abundance of CH4 in response to a 1034 erg flare over 2 hr. Left: the color plot shows the net rate of change in CH4 number density at each time step. Blue shows a net increase in CH4 when considering both reactions and vertical transport (mixing), while red shows a net decrease. Both colors are plotted on the same absolute logarithmic scale. The initial CH4 number density profile is plotted as a line for reference, corresponding to the top axis. Note that identical rates of change have a larger effect on the CH4 mixing ratio at lower pressures due to reduced atmospheric density. Center: the summed chemical reaction rate affecting CH4, across all reactions. Regions with matching colors in the left and center panels indicate levels where chemical reactions are the dominant mechanism for change in CH4 abundance. Right: the rate of change of CH4 due to vertical transport, calculated as the net rate minus the chemical rate. Regions of matching color in the left and right plots are levels where the change in CH4 is primarily driven by mixing from other layers, rather than the chemical reaction rate.
Paper: Simulations of Flare Chemistry in Brown Dwarf Companions to Active M Dwarfs
Authors: Aidan Gibbs, Michael P. Fitzgerald
Figure caption: Change in temperature in response to flares of varying energy. Top left: The initial temperature–pressure profile of the simulated atmosphere. Top right: the change in temperature in response to a 1035 erg flare without considering any changes to atmospheric chemistry or opacity. Compared to simulations with temperature–chemistry coupling, the change in temperature is spread over a much broader pressure region of the atmosphere, resulting in a smaller temperature change. Bottom: change in temperature with temperature–chemistry coupling included for flares of varying energy. The largest increase in temperature occurs in a narrow pressure region where most of the photochemistry is occurring, indicating that the change is caused primarily by a change in opacity. Negligible cooling <1 K occurs anywhere in the atmosphere.
Paper: Simulations of Flare Chemistry in Brown Dwarf Companions to Active M Dwarfs
Authors: Aidan Gibbs, Michael P. Fitzgerald
Figure caption: Relative change in the high-resolution (R = 105) near-infrared emission spectrum of the brown dwarf in response to a single 1034 erg flare. Top: the relative change in the brown dwarf emission at four times spaced from the beginning of the simulated flare. All differences have been converted to positive values to allow plotting on a log scale, though some changes correspond to flux increases and others correspond to flux decreases. Most change occurs due to dissociation of H2O. At lower spectral resolution (R = 1000, not shown), changes are significantly smaller, peaking at ∼10 ppm, although the changes have a similar spectral and temporal pattern. Higher spectral resolution increases sensitivity to lower atmospheric pressures. Bottom: the initial brown dwarf emission spectrum, plotted with Earth’s near-infrared observing windows.
Paper: The Relation between the Optical Variability Timescale, Magnetic Field of Jets, and Black Hole Spin in Active Galactic Nuclei
Authors: Yongyun Chen, 永云 陈, Qiusheng Gu, 秋生 顾, Junhui Fan, 军辉 樊, Dingrong Xiong, 定荣 熊, Xiaoling Yu, 效龄 俞, Xiaotong Guo, 晓通 郭, Nan Ding, 楠 丁, Ting-Feng Yi, 庭丰 易
Figure caption: The relations between the damping timescale in the rest frame (τDRW) and other physical parameters. (a) Relation between damping timescale in the rest frame (τDRW) and the magnetic field of the jets. (b) Relation between damping timescale in the rest frame (τDRW) and black hole spin. (c) Relation between damping timescale in the rest frame (τDRW) and jet kinetic power. Shaded gray colored areas correspond to 1σ confidence bands. The black line is the best fit.
Paper: Simulations of Flare Chemistry in Brown Dwarf Companions to Active M Dwarfs
Authors: Aidan Gibbs, Michael P. Fitzgerald
Figure caption: Spectral and temporal evolution of Fiducial Flare synthetic flares. Left: a quiescent stellar spectrum (MUSCLES GJ 832; K. France et al. 2016) compared to a star plus flare spectrum at peak luminosity for flares of three different energies. Radiation longer than ∼240 nm is not capable of photodissociation and is effectively invisible to VULCAN, while radiation shorter than ∼240 nm is invisible to HELIOS due to limitations in opacities. Right: the bolometric luminosity light curve for flares of different energies relative to the quiescent stellar bolometric luminosity.
Paper: Simulations of Flare Chemistry in Brown Dwarf Companions to Active M Dwarfs
Authors: Aidan Gibbs, Michael P. Fitzgerald
Figure caption: Photochemistry in response to single flares of varying energy. No temperature–chemistry coupling is included in this simulation to reduce the computation time. Initial chemical mixing profiles are shown as gray lines in the central column. More energetic flares have longer total durations, which drive differences in photochemistry behavior at early times for flares of different energies.
Paper: The Epoch of Reionization 21 cm Bispectrum at z = 8.2 from MWA Data. I. Foregrounds and Preliminary Upper Limits
Authors: Sukhdeep Singh Gill, Somnath Bharadwaj, Khandakar Md Asif Elahi, Shiv K. Sethi, Akash Kumar Patwa
Figure caption: The 3D cylindrical BS B(k1⊥, k2⊥, k3⊥, k1∥, k2∥) for the four triangle configurations (k1⊥, k2⊥, k3⊥) shown in Figure 1. These results are obtained via a 2D Fourier transform (Equation (3)) of the MABS shown in Figure 2. The top row shows heat maps of the 3D BS over the entire (k1∥, k2∥) plane, while the second row zooms into the central region −0.7 Mpc−1 ≤ (k1∥, k2∥) ≤ 0.7 Mpc−1. The third row shows 1D cuts along the diagonal k1∥ = k2∥ (marked by a dashed brown line in the second row), plotted on a symmetric logarithmic scale with a linear range of ±1021 mK3 Mpc6. The fourth row shows four distinct regions (A0, A1, A2, and A3) into which the (k1∥, k2∥) plane has been divided based on the number of triangle sides that are outside the foreground wedge, that is, ﹩({k}_{i\parallel }\gt [r/({r}^{{\prime} }{\rm{\Delta }}{\nu }_{c})]{k}_{{i}_{\perp }})﹩. The bottom row provides a zoomed-in view of the fourth row.
Paper: The Epoch of Reionization 21 cm Bispectrum at z = 8.2 from MWA Data. I. Foregrounds and Preliminary Upper Limits
Authors: Sukhdeep Singh Gill, Somnath Bharadwaj, Khandakar Md Asif Elahi, Shiv K. Sethi, Akash Kumar Patwa
Figure caption: The top row shows ∣B(k1⊥, k1∥)∣, which is the magnitude of the 3D cylindrical BS ∣B(k1⊥, k2⊥, k3⊥, k1∥, k2∥)∣ for squeezed triangles (k1⊥ ≈ k2⊥, k3⊥ → 0) with the constraints k1∥ = k2∥ and k1∥ = −k2∥ for the left and center panels, respectively. The top-right panel shows ∣P(k1⊥, k1∥)∣ the cylindrical PS for the same data from K. M. A. Elahi et al. (2025). In each panel, the dashed line shows the predicted foreground wedge boundary ﹩{[{k}_{1\parallel }]}_{{\rm{H}}}=[r/({r}^{{\prime} }{\rm{\Delta }}{\nu }_{c})]{k}_{1\perp }﹩, whereas the dotted line in the left panel shows ﹩{[{k}_{3\parallel }]}_{{\rm{H}}}﹩ corresponding to the minimum value of k3⊥ (= 0.005 Mpc−1). The panels in the bottom row show 1D sections through the respective panels of the upper row, at k1⊥ ≈ 0.023 Mpc−1 for the BS and k1⊥ ≈ 0.021 Mpc−1 for the PS.
Paper: The Epoch of Reionization 21 cm Bispectrum at z = 8.2 from MWA Data. I. Foregrounds and Preliminary Upper Limits
Authors: Sukhdeep Singh Gill, Somnath Bharadwaj, Khandakar Md Asif Elahi, Shiv K. Sethi, Akash Kumar Patwa
Figure caption: Mean-cube brightness temperature fluctuations, Δ3(k1), for equilateral triangles (k1 ≈ k2 ≈ k3) in the left panel and squeezed triangles (k1 ≈ k2, k3 → 0) in the right panel. The solid black lines show results with no foreground avoidance (A0+A1+A2+A3). The dotted colored lines show results for various foreground avoidance scenarios, as indicated in the figure legend. The solid red line shows ∣Δ2(k1)∣3/2, where Δ2(k1) is the mean-square brightness temperature fluctuation from K. M. A. Elahi et al. (2025), who have analyzed the same data.
Paper: The Epoch of Reionization 21 cm Bispectrum at z = 8.2 from MWA Data. I. Foregrounds and Preliminary Upper Limits
Authors: Sukhdeep Singh Gill, Somnath Bharadwaj, Khandakar Md Asif Elahi, Shiv K. Sethi, Akash Kumar Patwa
Figure caption: MABS BA(ℓ1, ℓ2, ℓ3, Δν1, Δν2) plotted as a function of (Δν1, Δν2) for the four representative triangle configurations—equilateral (top left), squeezed (top right), stretched (bottom left), and right-angle (bottom right)—illustrated in Figure 1. The Δν1 − Δν2 plane is restricted to ∣ν1∣, ∣ν2∣ ≤ Bbw/2, thereby excluding frequency separations that are not sampled. Only the upper half-plane, i.e., -Bbw/2 ≤ Δν1 ≤ Bbw/2 and 0 ≤ Δν2 ≤ Bbw/2, is displayed, owing to the symmetry BA(ℓ1, ℓ2, ℓ3, −Δν1, −Δν2) = BA(ℓ1, ℓ2, ℓ3, Δν1, Δν2).
Paper: The Epoch of Reionization 21 cm Bispectrum at z = 8.2 from MWA Data. I. Foregrounds and Preliminary Upper Limits
Authors: Sukhdeep Singh Gill, Somnath Bharadwaj, Khandakar Md Asif Elahi, Shiv K. Sethi, Akash Kumar Patwa
Figure caption: Four triangle configurations—equilateral, squeezed, stretched, and right-angle—for which we explicitly present the MABS and the 3D cylindrical BS results. For each case, the numerical values of the triangle sides (ℓ1, ℓ2, ℓ3) together with the corresponding perpendicular wavenumbers k1⊥ = ℓ1/r, k2⊥ = ℓ2/r, and k3⊥ = ℓ3/r are listed in the bottom row. These four cases are a small subset of the total of 669 distinct triangle configurations formed by all the (ℓ1, ℓ2, ℓ3) analyzed in this study.
Paper: Evolution of the Physical Properties of the Most Massive Galaxies in Clusters and Their Protohalos
Authors: Qingyang Li, Xiaohu Yang, Antonios Katsianis, Paola Popesso, Ilaria Marini, Y. Sophia Dai, Chengze Liu, Yipeng Jing, Jia-Sheng Huang, Marcin Sawicki
Figure caption: Comparison of stellar mass growth from SED fitting and SFR. The left and right panels show the trends for the cluster and protohalo MMGs, respectively. The top and bottom panels show the comparisons for the first and second MMGs. The black line represents the median stellar mass of the brightest galaxies, while the red arrows indicate the expected stellar mass assuming in situ growth only, calculated from the SFR and time intervals between redshifts following in Equation (8). The shaded region with red, orange, and blue colors indicates three stages of stellar mass growth: in situ dominated (z > 2.5), transitionary (2.5 ≲ z ≲ 1), and ex situ dominated (z < 1).
Paper: Evolution of the Physical Properties of the Most Massive Galaxies in Clusters and Their Protohalos
Authors: Qingyang Li, Xiaohu Yang, Antonios Katsianis, Paola Popesso, Ilaria Marini, Y. Sophia Dai, Chengze Liu, Yipeng Jing, Jia-Sheng Huang, Marcin Sawicki
Figure caption: Cumulative stellar mass functions at different redshifts, coded with different color lines. The solid and hollow triangles show the evolution trajectory of cluster first and second galaxies based on the median stellar mass shown in the top left panel of Figure 6. The solid and hollow gray points indicate the evolution trajectory of the cluster first and second MMGs from the evolving cumulative number density method (P. S. Behroozi et al. 2013) based on the number density of MMGs at 0 < z < 0.4. The gray dashed lines mark the level of constant cumulative number density.
Paper: The Epoch of Reionization 21 cm Bispectrum at z = 8.2 from MWA Data. I. Foregrounds and Preliminary Upper Limits
Authors: Sukhdeep Singh Gill, Somnath Bharadwaj, Khandakar Md Asif Elahi, Shiv K. Sethi, Akash Kumar Patwa
Figure caption: One-dimensional slices of the MABS plotted as a function of Δν1 at fixed Δν2 = 0, corresponding to each of the 2D MABS panels presented in Figure 2.
Paper: Supra-arcade Downflows in an Extensive Fan Associated with a Giant Quiescent Solar Filament Eruption
Authors: Xiaoyan Xie, Katharine K. Reeves, Chengcai Shen, Nishu Karna, Yan Xu, Christopher S. Moore, Crisel Suarez, Ritesh Patel, Daniel B. Seaton
Figure caption: Evolution of SADs A and B, where the dot and cross indicate the head of SADs observed in XRT/Be-thin (a)–(k). White and black solid lines indicate the corresponding SAD widths shown in Figure 4. The dashed line indicates the distance that is 6 pixels away from the head of SAD A. The green line in panel (d) indicates twice the width of the white line at the moment. We plot positions of SAD heads at different times in panel (l). Note that the time difference between panels (b) and (c) is 509 s, and the rest is about 180 s.
Paper: Supra-arcade Downflows in an Extensive Fan Associated with a Giant Quiescent Solar Filament Eruption
Authors: Xiaoyan Xie, Katharine K. Reeves, Chengcai Shen, Nishu Karna, Yan Xu, Christopher S. Moore, Crisel Suarez, Ritesh Patel, Daniel B. Seaton
Figure caption: Observations of the supra-arcade fan in AIA channels and XRT filters at 2023 December 24 15:20 UT, where the arrow in each panel indicates the color change for intensity increase. The locations of SADs A and B’s heads identified from Figure 3(i) at 15:20 UT are indicated in each panel. White dashed lines indicate the height measurements for SADs before performing deprojection of plane-of-sky effect.
Paper: Supra-arcade Downflows in an Extensive Fan Associated with a Giant Quiescent Solar Filament Eruption
Authors: Xiaoyan Xie, Katharine K. Reeves, Chengcai Shen, Nishu Karna, Yan Xu, Christopher S. Moore, Crisel Suarez, Ritesh Patel, Daniel B. Seaton
Figure caption: Height, velocity, and width as a function of time for SADs A and B, where we set the moment when we start tracking SAD A (i.e., 14:54:02 UT, as shown in Figure 3(b)) as time 0.
Paper: Supra-arcade Downflows in an Extensive Fan Associated with a Giant Quiescent Solar Filament Eruption
Authors: Xiaoyan Xie, Katharine K. Reeves, Chengcai Shen, Nishu Karna, Yan Xu, Christopher S. Moore, Crisel Suarez, Ritesh Patel, Daniel B. Seaton
Figure caption: Temperature (a) and EM (d) distributions at 15:20 UT derived form XRT/Be-thin and Al-poly, where the dots and cross indicate the heads of SADs A and B, respectively. (b), (c), (e), (f) Temperature and EM variations as a function of distance along the corresponding colored paths indicated in panels (a) and (d), where the red dashed line indicates the locations of the head of SAD B. The temperature dips of SADs A and B are marked by “A” and “B” in panel (b).
Paper: Supra-arcade Downflows in an Extensive Fan Associated with a Giant Quiescent Solar Filament Eruption
Authors: Xiaoyan Xie, Katharine K. Reeves, Chengcai Shen, Nishu Karna, Yan Xu, Christopher S. Moore, Crisel Suarez, Ritesh Patel, Daniel B. Seaton
Figure caption: (a) Temperature responses of AIA/94 Å, AIA/193 Å, and AIA/94 Å due to Fe XVIII line (94 Å/Fe XVIII) and AIA/193 Å due to Fe XII lines (193 Å/Fe XII). (b) Intensity distribution of 94 Å/Fe XVIII. (c) Intensity distribution of 193 Å/Fe XII.
Paper: Supra-arcade Downflows in an Extensive Fan Associated with a Giant Quiescent Solar Filament Eruption
Authors: Xiaoyan Xie, Katharine K. Reeves, Chengcai Shen, Nishu Karna, Yan Xu, Christopher S. Moore, Crisel Suarez, Ritesh Patel, Daniel B. Seaton
Figure caption: Illustration of projection effects where solar-X and solar-Y indicate the solar image coordinate (adopted from https://math.etsu.edu/multicalc/prealpha/Chap3/Chap3-5/part2.htm).
Paper: Supra-arcade Downflows in an Extensive Fan Associated with a Giant Quiescent Solar Filament Eruption
Authors: Xiaoyan Xie, Katharine K. Reeves, Chengcai Shen, Nishu Karna, Yan Xu, Christopher S. Moore, Crisel Suarez, Ritesh Patel, Daniel B. Seaton
Figure caption: Intensity versus distance along the extended cuts indicated in Figures 3(b)–(i) for SAD A. The dashed lines indicate the SAD A widths that correspond to white lines in Figures 3(b)–(i).
Paper: Supra-arcade Downflows in an Extensive Fan Associated with a Giant Quiescent Solar Filament Eruption
Authors: Xiaoyan Xie, Katharine K. Reeves, Chengcai Shen, Nishu Karna, Yan Xu, Christopher S. Moore, Crisel Suarez, Ritesh Patel, Daniel B. Seaton
Figure caption: Synthetic images from XRT-derived EMs.
Paper: Assessing the Geoeffectiveness of Stream Interaction Regions through Physically Interpretable Machine Learning
Authors: Yudong Ye, Jiajia Liu, Yongqiang Hao, Jun Cui, Xueshang Feng
Figure caption: Normalized Fisher score rankings of the top 60 features selected from the original feature set. The left panel shows the top 30 features, while the right panel displays features ranked 31–60. SW_Speed and SW_Temp refer to the solar wind velocity and temperature, respectively. Prefixes such as PreMean and PostMean represent average values of a parameter before and after each SIR event. AbsDiff and RelDiff indicate the absolute and relative differences between pre- and post-event values, respectively. Std denotes the standard deviation, and Deviation refers to variability within the SIR duration.
Paper: Assessing the Geoeffectiveness of Stream Interaction Regions through Physically Interpretable Machine Learning
Authors: Yudong Ye, Jiajia Liu, Yongqiang Hao, Jun Cui, Xueshang Feng
Figure caption: UMAP projection of SIR events using the top eight SHAP-ranked features derived from the SVM geoeffectiveness model. Each point represents a single SIR event, and colors indicate cluster assignments obtained via KMeans clustering (k = 2). The features were selected based on their contribution to SVM predictions, as measured by mean absolute SHAP values. UMAP was applied to the standardized feature set using 15 nearest neighbors and a minimum distance of 0.1. Two distinct clusters are clearly visible, with minimal overlap and a relatively sharp boundary separating them, suggesting that the selected features capture key structural differences among SIRs related to their geoeffectiveness. This representation supports the presence of physically meaningful patterns in the data, as discovered through an unsupervised manifold learning approach.
Paper: Assessing the Geoeffectiveness of Stream Interaction Regions through Physically Interpretable Machine Learning
Authors: Yudong Ye, Jiajia Liu, Yongqiang Hao, Jun Cui, Xueshang Feng
Figure caption: Lollipop plot of SHAP feature importances, grouped by physical category. The left panel shows magnetic field (teal) and electric field (pink) features, while the right panel includes velocity (blue) and pressure/density (orange) features. The horizontal axis represents the mean absolute SHAP value, indicating each feature’s average contribution to the geoeffectiveness prediction. Features outlined in black correspond to the top 11 most influential contributors with mean absolute SHAP values larger than 0.02.
Paper: Assessing the Geoeffectiveness of Stream Interaction Regions through Physically Interpretable Machine Learning
Authors: Yudong Ye, Jiajia Liu, Yongqiang Hao, Jun Cui, Xueshang Feng
Figure caption: Illustration of the soft-margin Support Vector Machine (SVM) framework, adapted from our previous article (Y. Ye et al. 2024). The diagram shows the optimal separating hyperplane (solid blue line), margin boundaries (dashed green lines), support vectors (highlighted with dashed arrows), and slack variables ﹩\xi ﹩ representing margin violations. Triangles and squares represent samples from two different classes.
Paper: Assessing the Geoeffectiveness of Stream Interaction Regions through Physically Interpretable Machine Learning
Authors: Yudong Ye, Jiajia Liu, Yongqiang Hao, Jun Cui, Xueshang Feng
Figure caption: SHAP summary plot illustrating the contribution of each feature to the SVM model’s prediction of SIR geoeffectiveness. Features are sorted by overall importance (mean absolute SHAP value), and each point represents a single SIR event. Point color indicates the actual feature value, with red corresponding to high values and blue to low values. Positive SHAP values indicate a contribution toward classifying the event as geoeffective (C1), while negative values contribute to a nongeoeffective (C2) prediction.