adsabs/AstroCLIMB huggingface dataset:
Paper: Numerical Modeling of Energetic Charged-particle Transport with SPECTRUM Software: General Approach and Artificial Effects due to Field Discretization
Authors: J. G. Alonso Guzmán, V. Florinski, G. Tóth, S. Sharma, B. van der Holst, M. Opher
Figure caption: Running diffusion coefficient vs time. The black dashed line shows the theoretical value of the parallel diffusion coefficient for the conditions described in the text according to QLT. The red line corresponds to the run with an analytic background, while the markers are for the runs that used discretized backgrounds.
Paper: Numerical Modeling of Energetic Charged-particle Transport with SPECTRUM Software: General Approach and Artificial Effects due to Field Discretization
Authors: J. G. Alonso Guzmán, V. Florinski, G. Tóth, S. Sharma, B. van der Holst, M. Opher
Figure caption: Magnetic field components along curve (13). The solid lines represent the analytic dipole, while the circles are the discretized versions. The discrete values were sampled from a uniform grid with 10 blocks per dimension (4 × 4 × 4 cells per block) using trilinear interpolation. The right panel shows a zoomed-in view of the portions in the left panel demarcated in blue.
Paper: Numerical Modeling of Energetic Charged-particle Transport with SPECTRUM Software: General Approach and Artificial Effects due to Field Discretization
Authors: J. G. Alonso Guzmán, V. Florinski, G. Tóth, S. Sharma, B. van der Holst, M. Opher
Figure caption: Average time to integrate one trajectory for the weak-scaling tests described in the text. Error bars show 1 standard deviation. The tests on a single node are shown on the left, while tests using eight nodes simultaneously, with the number of processes divided equally among all the nodes, are on the right.
Paper: Numerical Modeling of Energetic Charged-particle Transport with SPECTRUM Software: General Approach and Artificial Effects due to Field Discretization
Authors: J. G. Alonso Guzmán, V. Florinski, G. Tóth, S. Sharma, B. van der Holst, M. Opher
Figure caption: Side view of a particle’s trajectory during one bounce period (red circles), and cross section of the grid along y = 0. The axis numbers are in units of R E.
Paper: Erratum: “Stellar Loci. VII. Photometric Metallicities of 5 Million FGK Stars Based on GALEX GR6+7 AIS and Gaia EDR3” (2024, ApJS, 271, 26)
Authors: Xue Lu, Haibo Yuan, Shuai Xu, Ruoyi Zhang, Kai Xiao, Yang Huang, Timothy C. Beers, Jihye Hong
Figure caption: From left to right, the columns of panels represent comparisons with the LAMOST DR8 value-added catalog of Wang et al. (2022), the SEGUE DR12 (Alam et al. 2015) catalog, and the VMP catalogs of Li et al. (2018) and Li et al. (2022), respectively. The left column of panels is color coded by the source number density. In the right column of panels, the gray and red dots are from Li et al. (2018) and Li et al. (2022), respectively. The dwarfs are plotted in the top row of panels and the giants in the bottom row of panels. The mean and standard deviation values of the residuals Δ[Fe/H] are labeled in the lower right of each panel.
Paper: A Blueprint for the Milky Way’s Stellar Populations. V. 3D Local Dust Extinction
Authors: Deokkeun An, Timothy C. Beers, Anirudh Chiti
Figure caption: Model deviations and uncertainties in XP MS sample. Top panel: mean model deviations of the XP MS sample as a function of wavelength. Weighted mean differences from all stars with E(B  −  V) < 0.1 are shown by a histogram, along with weighted standard deviations displayed by error bars. Bottom panel: weighted standard deviations (error bars in the top panel), overlaid on top of median fractional uncertainties in the XP spectra.
Paper: A Blueprint for the Milky Way’s Stellar Populations. V. 3D Local Dust Extinction
Authors: Deokkeun An, Timothy C. Beers, Anirudh Chiti
Figure caption: Model fits illustrating comparisons for various effective temperatures (T eff; left) and metallicities ([Fe/H]; right). Best-fitting estimates for T eff and [Fe/H] are shown, with high-resolution spectroscopic estimates from GALAH indicated in parentheses. The left panel depicts all cases at solar metallicity.
Paper: A Blueprint for the Milky Way’s Stellar Populations. V. 3D Local Dust Extinction
Authors: Deokkeun An, Timothy C. Beers, Anirudh Chiti
Figure caption: Mean and statistical properties of R  V  estimates from stars within (m  −  M)0 ≤ 12. Only regions with significant reddening (E(B  −  V) ≥ 0.1 at (m  −  M)0 = 12) are included. (a) Mean R  V  estimates from Case A and Case B. (b) Differences in R  V  between Case A and Case B. (c) Half of the difference between the 15.9th and 84.1st percentiles of R  V  from Case A (σ(R  V )). (d) Significance of the deviation of R  V  from the fiducial case (R  V  = 3.1) in relation to the error in the mean R  V  (﹩\epsilon \equiv \sigma ({R}_{V})/\sqrt{N}﹩).
Paper: A Blueprint for the Milky Way’s Stellar Populations. V. 3D Local Dust Extinction
Authors: Deokkeun An, Timothy C. Beers, Anirudh Chiti
Figure caption: Mean metallicity estimates on the sky in the Galactic coordinate system assuming R  V  = 3.1, for (a) Case A and (b) Case B.
Paper: A Blueprint for the Milky Way’s Stellar Populations. V. 3D Local Dust Extinction
Authors: Deokkeun An, Timothy C. Beers, Anirudh Chiti
Figure caption: Comparison to the E(B  −  V) map of Schlegel et al. (1998). Top panel: differences from the averaged E(B  −  V) map at d = 1584 pc (panel (e) in Figure 11), in the sense of their E(B  −  V) minus our values. Bottom panel: the solid line represents the median difference in E(B  −  V), with error bars indicating the standard deviation.
Paper: A Blueprint for the Milky Way’s Stellar Populations. V. 3D Local Dust Extinction
Authors: Deokkeun An, Timothy C. Beers, Anirudh Chiti
Figure caption: Comparisons of metallicity estimates in this study with high-resolution spectroscopic measurements from GALAH (top panels) and APOGEE (bottom panels). In the right panels, the same suite of comparisons is shown, but when our parameter estimates are restricted to 390–993 nm, excluding UV portion of the spectra. The solid line represents a unity line.
Paper: A Blueprint for the Milky Way’s Stellar Populations. V. 3D Local Dust Extinction
Authors: Deokkeun An, Timothy C. Beers, Anirudh Chiti
Figure caption: Comparison to the E(B  −  V) map of Green et al. (2019). Top panels: comparisons are shown with respect to our averaged E(B  −  V) maps at selected distance bins (d = 251, 630, and 1584 pc), in the sense of their E(B  −  V) minus our values. Bottom panels: median deviations as a function of Galactic latitude in intervals of 2.°5. Error bars denote their standard deviations.
Paper: A Blueprint for the Milky Way’s Stellar Populations. V. 3D Local Dust Extinction
Authors: Deokkeun An, Timothy C. Beers, Anirudh Chiti
Figure caption: Comparison of E(B  −  V) and [Fe/H] estimates between Zhang et al. (2023b) and Case A for the identical XP sample from a region with a 3° radius, centered at (l, b) = (20°, 20°). An additional [Fe/H] comparison is presented in the bottom right panel along a line of sight with low extinction at (l, b) = (300°, 45°). Unity lines are represented by dashed lines, while zero differences are displayed in the bottom left panel.
Paper: A Blueprint for the Milky Way’s Stellar Populations. V. 3D Local Dust Extinction
Authors: Deokkeun An, Timothy C. Beers, Anirudh Chiti
Figure caption: Differences in A  V  derived from Case A when assuming a fixed value of R  V  = 3.1, compared to using a median R  V  (see text). The comparisons are illustrated at three representative distances.
Paper: A Blueprint for the Milky Way’s Stellar Populations. V. 3D Local Dust Extinction
Authors: Deokkeun An, Timothy C. Beers, Anirudh Chiti
Figure caption: Same as Figure 13, but displaying a comparison with Zhang et al. (2023b).
Paper: A Blueprint for the Milky Way’s Stellar Populations. V. 3D Local Dust Extinction
Authors: Deokkeun An, Timothy C. Beers, Anirudh Chiti
Figure caption: Mean metallicity estimates from varying R  V  in the parameter search, for (a) Case A and (b) Case B.
Paper: A Blueprint for the Milky Way’s Stellar Populations. V. 3D Local Dust Extinction
Authors: Deokkeun An, Timothy C. Beers, Anirudh Chiti
Figure caption: Comparisons with E(B  −  V) estimates from the literature. (a) Open cluster samples with fundamental parameters from An et al. (2007, 2019). (b) A homogeneous set of fundamental parameters for open cluster samples from Dias et al. (2021). (c) Compilation of cluster E(B  −  V) for Galactic globular clusters as reported in Harris (1996). In panel (c), only the lower limit in our E(B  −  V) estimates is displayed, as the cluster distances exceed the maximum threshold of our E(B  −  V) cube. In all panels, the red solid line corresponds to the best-fitting regression to the data, with a zero-point and a slope displayed at the top, whereas dotted lines represent the unity and zero lines.
Paper: A Blueprint for the Milky Way’s Stellar Populations. V. 3D Local Dust Extinction
Authors: Deokkeun An, Timothy C. Beers, Anirudh Chiti
Figure caption: Reddening of stars against distance modulus in a single, multiresolution HEALPix cell located along l = 149.°8 and b = 4.°8. The four panels display different sets of E(B  −  V) measurements, Case A through Case D (see Table 1). Individual fits to the simulated data using a double logistic function in Equation (1) are illustrated by green lines, and the best-fitting dust model is depicted by a red solid line.
Paper: A Blueprint for the Milky Way’s Stellar Populations. V. 3D Local Dust Extinction
Authors: Deokkeun An, Timothy C. Beers, Anirudh Chiti
Figure caption: Multiresolution HEALPix scheme. (a) The number density of the XP MS sample in the Galactic coordinate system (Case A). The number of stars per 0.2 deg2 area is shown. (b) A multiresolution HEALPix map created using the data shown in panel (a), in the same coordinate system. The map is composed of four distinct sets of HEALPix cells, each with varying surface areas: 0.2 deg2 (28,152 cells), 0.8 deg2 (24,802), 3.4 deg2 (3872), and 13.4 deg2 (114). (c) Distribution of the number of stars per cell, derived from the multiresolution grid scheme shown in panel (b).
Paper: A Blueprint for the Milky Way’s Stellar Populations. V. 3D Local Dust Extinction
Authors: Deokkeun An, Timothy C. Beers, Anirudh Chiti
Figure caption: Example of the multiresolution HEALPix scheme. Left panel: number density distribution of the XP MS sample in the Galactic coordinate system in a patch of the sky. The number of stars per unit HEALPix cell with an area of 0.2 deg2 (N side = 128) is depicted. Right panel: mean reddening for the same region of the sky as in the left panel. We note that the region with high foreground extinction in the right panel (e.g., (l, b) ∼ (20°, 5°)) is underrepresented by the XP MS sample. Larger multiresolution HEALPix cells are adopted in this area to maintain a sufficient number of stars for modeling the foreground extinction distribution as a function of distance.
Paper: A Blueprint for the Milky Way’s Stellar Populations. V. 3D Local Dust Extinction
Authors: Deokkeun An, Timothy C. Beers, Anirudh Chiti
Figure caption: Average reddening of the XP MS sample shown in a Mollweide projection of the Galactic coordinate system, represented by the multiresolution HEALPix. Each panel corresponds to one of the four different solutions obtained in this study (Table 1).
Paper: A Blueprint for the Milky Way’s Stellar Populations. V. 3D Local Dust Extinction
Authors: Deokkeun An, Timothy C. Beers, Anirudh Chiti
Figure caption: Differential reddening of the XP MS sample based on Case A in selected distance bins. Reddening maps are displayed in a Mollweide projection of the Galactic coordinate system using the multiresolution HEALPix.
Paper: A Blueprint for the Milky Way’s Stellar Populations. V. 3D Local Dust Extinction
Authors: Deokkeun An, Timothy C. Beers, Anirudh Chiti
Figure caption: Difference in modeled E(B  −  V) between different cases of parameter estimates (Table 1) in selected distance bins.
Paper: A Blueprint for the Milky Way’s Stellar Populations. V. 3D Local Dust Extinction
Authors: Deokkeun An, Timothy C. Beers, Anirudh Chiti
Figure caption: Average E(B  −  V) from Case A and Case B (Table 1) in the Galactic coordinate system as a function of heliocentric distance.
Paper: A Blueprint for the Milky Way’s Stellar Populations. V. 3D Local Dust Extinction
Authors: Deokkeun An, Timothy C. Beers, Anirudh Chiti
Figure caption: Same as Figure 5, but displaying Case A measurements for selected lines of sight. Sight lines directed toward the Galactic plane are displayed on the left, while additional sight lines situated at various Galactic latitudes within the same longitude range are displayed on the right. Note that distinct coverages are employed, with each one representing a single multiresolution HEALPix cell.
Paper: A Blueprint for the Milky Way’s Stellar Populations. V. 3D Local Dust Extinction
Authors: Deokkeun An, Timothy C. Beers, Anirudh Chiti
Figure caption: Range of minimum (top panel) and maximum (bottom panel) distance modulus determined by the number of stars accessible in Case A.
Paper: USmorph: An Updated Framework of Automatic Classification of Galaxy Morphologies and Its Application to Galaxies in the COSMOS Field
Authors: Jie Song, GuanWen Fang, Shuo Ba, Zesen Lin, Yizhou Gu, Chichun Zhou, Tao Wang, Cai-Na Hao, Guilin Liu, Hongxin Zhang, Yao Yao, Xu Kong
Figure caption: Some examples of image preprocessing. The left column displays original images of four randomly selected galaxies, the middle column shows the corresponding denoised images, and the right column displays images that have undergone a polar coordinate transformation. The redshift information of these chosen galaxies is shown in the first column.
Paper: USmorph: An Updated Framework of Automatic Classification of Galaxy Morphologies and Its Application to Galaxies in the COSMOS Field
Authors: Jie Song, GuanWen Fang, Shuo Ba, Zesen Lin, Yizhou Gu, Chichun Zhou, Tao Wang, Cai-Na Hao, Guilin Liu, Hongxin Zhang, Yao Yao, Xu Kong
Figure caption: Illustration of the post-hoc visual inspection for label alignment. 100 galaxies are randomly selected from each group (only 64 galaxies are selected for Group 9 because the total number of galaxies in this group is fewer than 100) for visual inspection. Since galaxies within each group share similar features, we are able to quickly categorize each group into five types (SPH, ETD, LTD, IRR, and UNC) by simultaneously assessing the overall morphological features of these selected galaxies.
Paper: USmorph: An Updated Framework of Automatic Classification of Galaxy Morphologies and Its Application to Galaxies in the COSMOS Field
Authors: Jie Song, GuanWen Fang, Shuo Ba, Zesen Lin, Yizhou Gu, Chichun Zhou, Tao Wang, Cai-Na Hao, Guilin Liu, Hongxin Zhang, Yao Yao, Xu Kong
Figure caption: The left and middle panels represent the precision and recall of the GoogLeNet model, with both the overall precision and recall exceeding 94%, which indicate that the GoogLeNet model can effectively distinguish between different types of galaxies. The right panel represents the general confusion matrix.
Paper: USmorph: An Updated Framework of Automatic Classification of Galaxy Morphologies and Its Application to Galaxies in the COSMOS Field
Authors: Jie Song, GuanWen Fang, Shuo Ba, Zesen Lin, Yizhou Gu, Chichun Zhou, Tao Wang, Cai-Na Hao, Guilin Liu, Hongxin Zhang, Yao Yao, Xu Kong
Figure caption: The distribution of I-band magnitudes in the COSMOS field. A magnitude limit of I mag < 25 is imposed.
Paper: USmorph: An Updated Framework of Automatic Classification of Galaxy Morphologies and Its Application to Galaxies in the COSMOS Field
Authors: Jie Song, GuanWen Fang, Shuo Ba, Zesen Lin, Yizhou Gu, Chichun Zhou, Tao Wang, Cai-Na Hao, Guilin Liu, Hongxin Zhang, Yao Yao, Xu Kong
Figure caption: The distribution of galaxy morphological types in the training and validation sets.
Paper: USmorph: An Updated Framework of Automatic Classification of Galaxy Morphologies and Its Application to Galaxies in the COSMOS Field
Authors: Jie Song, GuanWen Fang, Shuo Ba, Zesen Lin, Yizhou Gu, Chichun Zhou, Tao Wang, Cai-Na Hao, Guilin Liu, Hongxin Zhang, Yao Yao, Xu Kong
Figure caption: Some examples of the final classification results. From left to right, they are SPHs, ETDs, LTDs, IRRs, and UNCs.
Paper: USmorph: An Updated Framework of Automatic Classification of Galaxy Morphologies and Its Application to Galaxies in the COSMOS Field
Authors: Jie Song, GuanWen Fang, Shuo Ba, Zesen Lin, Yizhou Gu, Chichun Zhou, Tao Wang, Cai-Na Hao, Guilin Liu, Hongxin Zhang, Yao Yao, Xu Kong
Figure caption: Framework of the morphological classification model employed in this work.
Paper: USmorph: An Updated Framework of Automatic Classification of Galaxy Morphologies and Its Application to Galaxies in the COSMOS Field
Authors: Jie Song, GuanWen Fang, Shuo Ba, Zesen Lin, Yizhou Gu, Chichun Zhou, Tao Wang, Cai-Na Hao, Guilin Liu, Hongxin Zhang, Yao Yao, Xu Kong
Figure caption: A t-SNE diagram of randomly selected 5000 galaxies from the final classification results, where red, green, blue, cyan, and gray represent SPHs, ETDs, LTDs, IRRs, and UNCs, respectively. Additionally, unless otherwise stated, the same color scheme is adopted in the following analyses. The solid lines of different colors in the figure represent the corresponding 1σ contours. Different types of galaxies exhibit distinct boundaries on the t-SNE diagram, indicating that our classification algorithm can effectively distinguish between different types of galaxies.
Paper: USmorph: An Updated Framework of Automatic Classification of Galaxy Morphologies and Its Application to Galaxies in the COSMOS Field
Authors: Jie Song, GuanWen Fang, Shuo Ba, Zesen Lin, Yizhou Gu, Chichun Zhou, Tao Wang, Cai-Na Hao, Guilin Liu, Hongxin Zhang, Yao Yao, Xu Kong
Figure caption: The distribution of effective radius (left panel) and Sérsic index (right panel) for different types of galaxies. The bars at the top represent the median values of ﹩\mathrm{log}({r}_{e})﹩ and n for different galaxy types. It is evident that from SPHs to IRRs, the effective radius of galaxies gradually increases, while the Sérsic index gradually decreases.
Paper: USmorph: An Updated Framework of Automatic Classification of Galaxy Morphologies and Its Application to Galaxies in the COSMOS Field
Authors: Jie Song, GuanWen Fang, Shuo Ba, Zesen Lin, Yizhou Gu, Chichun Zhou, Tao Wang, Cai-Na Hao, Guilin Liu, Hongxin Zhang, Yao Yao, Xu Kong
Figure caption: The distribution of four subclasses in the Gini–M 20 (left) and C–A (right) spaces. The contour represents 50% of the specified galaxies. The diamonds with different colors correspond to the median values of the parameters and the error bars represent the corresponding standard deviations.
Paper: USmorph: An Updated Framework of Automatic Classification of Galaxy Morphologies and Its Application to Galaxies in the COSMOS Field
Authors: Jie Song, GuanWen Fang, Shuo Ba, Zesen Lin, Yizhou Gu, Chichun Zhou, Tao Wang, Cai-Na Hao, Guilin Liu, Hongxin Zhang, Yao Yao, Xu Kong
Figure caption: The distributions of G 2 (left panel) and Ψ (right panel) for different types of massive galaxies. The bars at the top represent the median values of the corresponding parameters.