adsabs/AstroCLIMB huggingface dataset:
Paper: The Dispersion Measure and Scattering of Fast Radio Bursts: Contributions from Multicomponents, and Clues for the Intrinsic Properties
Authors: Jian-feng Mo, Weishan Zhu, Long-Long Feng
Figure caption: The posterior distribution of the MCMC results for the parameters ﹩{f}_{\mathrm{PSFR}},\,\gamma ,\,\mathrm{and}\,{\mathrm{log}}_{10}({E}_{* })﹩ in the DM-only model, thinned by a factor of 20 for the sake of clarity. The vertical and horizontal red lines denote the median (solid), 16th (dashed), and 84th (dashed) percentiles of the distribution.
Paper: The Dispersion Measure and Scattering of Fast Radio Bursts: Contributions from Multicomponents, and Clues for the Intrinsic Properties
Authors: Jian-feng Mo, Weishan Zhu, Long-Long Feng
Figure caption: Similar to Figure 9, but for the parameters ﹩{f}_{{\rm{PSFR}}},\gamma ,{{\rm{log}}}_{10}({E}_{\ast }),{\rm{and}}\,{F}_{\max}﹩ in the DM and τ combined model.
Paper: Half a Million M Dwarf Stars Characterized Using Domain-adapted Spectral Analysis
Authors: Shuo Zhang, 硕 张, Hua-Wei Zhang, 华伟 张, Yuan-Sen Ting, 源森 丁, Rui Wang, 瑞 王, Teaghan O'Briain, Hugh R. A. Jones, Derek Homeier, A-Li Luo, 阿理 罗
Figure caption: Metallicity comparison between FGK primaries and M dwarf secondaries in wide binary systems identified from K. El-Badry et al. (2021). The FGK primary metallicities are from LASP, while M dwarf values are from this study. Colors indicate different S/N thresholds, with sample sizes decreasing from 868 pairs (S/N > 5) to 100 pairs (S/N > 50). The bias and scatter for all 868 pairs are shown. The red dashed line represents the 1:1 reference line.
Paper: Real-time Extrapolation of Nonlinear Force-free Fields from Photospheric Vector Magnetic Fields Using a Physics-informed Neural Operator
Authors: Mingyu Jeon, Hyun-Jin Jeong, Yong-Jae Moon, Jihye Kang, Kanya Kusano
Figure caption: Overview of our method. The white and black in the images indicate positive and negative polarities, respectively, with the color map range defined as ±(1000 G)/(z + 1). The neural operator, shown as an orange box, is a U-shaped neural operator with six Fourier layers. Here, Lmse is a mean-squared error loss, Lcc is a correlation coefficient loss, Lff is a force-free loss, Ldiv is a divergence-free loss, and Lbc is a bottom boundary condition loss.
Paper: FASHI: An Untargeted Survey of the 21 cm H I Absorption Galaxies with FAST
Authors: Chuan-Peng Zhang, Ming Zhu, Peng Jiang, Cheng Cheng, Jin-Long Xu, Nai-Ping Yu, Xiao-Lan Liu, Bo Zhang
Figure caption: Locations for 51 H I absorption galaxies detected by FASHI over an area of about 10,000 square degrees. The circles indicate their positions in the equatorial coordinate system. The background image is the all-sky 21 cm radio continuum of the Stockert 25 m (W. Reich 1982) and Villa Elisa 30 m (P. Reich & W. Reich 1986; P. Reich et al. 2001). The white dashed rectangles indicate roughly the area currently covered by FAST.
Paper: FASHI: An Untargeted Survey of the 21 cm H I Absorption Galaxies with FAST
Authors: Chuan-Peng Zhang, Ming Zhu, Peng Jiang, Cheng Cheng, Jin-Long Xu, Nai-Ping Yu, Xiao-Lan Liu, Bo Zhang
Figure caption: The rest-frame 1.4 GHz continuum luminosity (upper) of the background sources, the H I column density (middle), and the H I optical depth vs. redshift (lower) for the 21 cm H I absorbers, including data points from K. Geréb et al. (2015), F. M. Maccagni et al. (2017), S. J. Curran & S. W. Duchesne (2018), and FASHI. In the upper panel, the different lines indicate different 1.4 GHz continuum flux density values.
Paper: FASHI: An Untargeted Survey of the 21 cm H I Absorption Galaxies with FAST
Authors: Chuan-Peng Zhang, Ming Zhu, Peng Jiang, Cheng Cheng, Jin-Long Xu, Nai-Ping Yu, Xiao-Lan Liu, Bo Zhang
Figure caption: Two examples of FAST spectra superimposed on Arecibo spectra (I. F. Mirabel & D. B. Sanders 1988; C. M. Springob et al. 2005). The both show good agreement in velocity and flux.
Paper: The Impact of Host-galaxy Properties on Supernova Classification with Hierarchical Labels
Authors: V. Ashley Villar, Sebastian Gomez, Edo Berger, Alex Gagliano
Figure caption: Breakdown of SN subclasses in our new photometrically classified set of SNe without redshift information. Compared to the spectroscopic sample (green), our classifier (blue) predicts a smaller fraction of Type Ia and Type II SNe and a larger fraction of SLSNe and Type Ibc SNe. However, using our purity matrix (see text), we can correct our classification breakdowns accounting for expected misidentifications (orange). Note that error bars are shown in black and calculated using Poisson uncertainties. We see that, following this correction, our class breakdowns are largely consistent with the spectroscopic sample. This indicates that although our classifier is biased, it is biased in a way which can be understand via our training set and can likely be carefully corrected for population-level studies.
Paper: The Impact of Host-galaxy Properties on Supernova Classification with Hierarchical Labels
Authors: V. Ashley Villar, Sebastian Gomez, Edo Berger, Alex Gagliano
Figure caption: Comparison of SN classifications from V. A. Villar et al. (2020) and this work. On the abscissa, we plot the confidence level of the V. A. Villar et al. (2018) classifier, while the ordinate shows the confidence of the new classifier for the same class. Objects plotted as a point have the same classification with both methods; objects plotted as an “x” have different classifications with either method. The color of the central point (“x” or “o”) identifies the label from this paper. In the case of mismatches (the “x” objects), the colored circle represents the label from V. A. Villar et al. (2020).
Paper: The Impact of Host-galaxy Properties on Supernova Classification with Hierarchical Labels
Authors: V. Ashley Villar, Sebastian Gomez, Edo Berger, Alex Gagliano
Figure caption: Confusion matrices for the classifier using redshift information, trained using only light-curve features (left) and with both light-curve and galaxy features (right). Including host information provides similar overall classification accuracy.
Paper: The Impact of Host-galaxy Properties on Supernova Classification with Hierarchical Labels
Authors: V. Ashley Villar, Sebastian Gomez, Edo Berger, Alex Gagliano
Figure caption: Confusion matrices for the classifier using solely light-curve features (left) and a combination of galaxy and light-curve features (right), both excluding redshift information. Inclusion of galaxy features does not improve classification for any one class to a statistically significant degree, and the overall performance only moderately increases.
Paper: The Impact of Host-galaxy Properties on Supernova Classification with Hierarchical Labels
Authors: V. Ashley Villar, Sebastian Gomez, Edo Berger, Alex Gagliano
Figure caption: Confusion matrices for the classifier using only host galaxy with (left) and without (right) redshift information. Numbers are overall percent, while uncertainties are given in parentheses (e.g., the completeness of SLSNe in the five-way classifier is 0.48 ± 0.06). The classifier reaches state-of-the-art results for the Type Ia vs. CC classification, but fails to achieve high accuracy in the five-way class split.
Paper: The Local Ultraviolet to Infrared Treasury. I. Survey Overview of the Broadband Imaging
Authors: Karoline M. Gilbert, Yumi Choi, Martha L. Boyer, Benjamin F. Williams, Daniel R. Weisz, Eric F. Bell, Julianne J. Dalcanton, Kristen B. W. McQuinn, Evan D. Skillman, Guglielmo Costa, Andrew E. Dolphin, Morgan Fouesneau, Léo Girardi, Steven R. Goldman, Karl D. Gordon, Puragra Guhathakurta, Maude Gull, Lea Hagen, Ky Huynh, Christina W. Lindberg, Paola Marigo, Claire E. Murray, Giada Pastorelli, Petia Yanchulova Merica-Jones
Figure caption: The specific SFR of star-forming galaxies in the local Universe as a function of their stellar mass, drawn from the 11 Mpc sample of J. C. Lee et al. (2009). The larger points represent the LEGUS (diamonds), LUVIT (circles), and select Local Group (M31, M33, LMC, and SMC; stars) galaxies and are color coded by distance, with the divergent point of the color map set at 3.5 Mpc, which is the approximate upper and lower limits of the LUVIT and LEGUS surveys, respectively. The LUVIT survey is complementary to the LEGUS survey, with the LUVIT galaxies chosen to represent the lowest stellar mass, lowest metallicity star-forming galaxies in the local Universe (Section 2.1), with estimated stellar masses M * ≲ 107.5 M ⊙. The resulting sample has gas-phase oxygen abundances of ﹩12+\mathrm{log}({\rm{O}}/{\rm{H}})\lt 8﹩ (Table 1).
Paper: DRAFTS: A Deep-learning-based Radio Fast Transient Search Pipeline
Authors: Yong-Kun Zhang, Di Li, Yi Feng, Chao-Wei Tsai, Pei Wang, Chen-Hui Niu, Hua-Xi Chen, Yu-Hao Zhu
Figure caption: Waiting-time distribution of FRB 20190520B. The red solid line represents the exponential distribution fit, the red dashed line represents the Weibull distribution fit, and the blue bars represent the waiting-time distribution of FRB 20190520B.
Paper: DRAFTS: A Deep-learning-based Radio Fast Transient Search Pipeline
Authors: Yong-Kun Zhang, Di Li, Yi Feng, Chao-Wei Tsai, Pei Wang, Chen-Hui Niu, Hua-Xi Chen, Yu-Hao Zhu
Figure caption: Two examples of omitted signals. The first and third columns show the time–frequency plots of two bursts; the second and fourth columns display the time–DM plots. The expected bursts’ locations in the time–DM plots are marked by red lines.
Paper: DRAFTS: A Deep-learning-based Radio Fast Transient Search Pipeline
Authors: Yong-Kun Zhang, Di Li, Yi Feng, Chao-Wei Tsai, Pei Wang, Chen-Hui Niu, Hua-Xi Chen, Yu-Hao Zhu
Figure caption: 183 newly detected bursts from FRB 20190520B.
Paper: Twinkle: A GPU-based Binary-lens Microlensing Code with the Contour Integration Method
Authors: Suwei Wang, Lile Wang, Subo Dong
Figure caption: Calculation performance of Twinkle compared with VBBL. All the origin points are moved to the position of planetary caustic (or the resonant caustic for s = 1). The left column takes s = 0.5, q = 10−4, ρ = 5 × 10−5, Δθx = (θx + 1.5), Δθy = (θy − 0.035). The middle column takes s = 1, q = 10−4, ρ = 1 × 10−3, Δθx = θx, Δθy = θy. The right column takes s = 3, q = 10−4, ρ = 1 × 10−4, Δθx = (θx − 2.666), Δθy = θy. The red solid line is the caustics. The performance for specific extended sources is shown by the color at the source center location. The origin point is moved to the caustics, meaning Δθx and Δθy. Each row except the fourth row takes the same color map. Additionally, the calculation times for Twinkle and VBBL in the second and third rows share the same logarithmic color mapping to demonstrate the calculation features.
Paper: Twinkle: A GPU-based Binary-lens Microlensing Code with the Contour Integration Method
Authors: Suwei Wang, Lile Wang, Subo Dong
Figure caption: An example demonstrating the enhanced accuracy introduced by the improvements in generating the coefficients of the lens equation (Equation (4) in Section 2.1). The top panel shows the overall images (green) on the image plane (θx–θy). The bottom left and right panels are the zoom-ins of the region marked by the square in the top panel, showing the results using conventional (bottom left panel; Equation (4)) and our improved (bottom right panel; Equation (6)) schemes of generating the coefficients. In the bottom panels, the origin is shifted to the central position of the zoom-in region, with Δθx = (θx − 0.5000595) and Δθy = (θy − 0.000535), where the real images and ghost images (gray diamonds) mapped from the source boundary cross on the critical curve (black solid line). The real images on the boundary with positive and negative parities are marked with magenta dots and blue crosses, respectively. The pink lines connecting real images form the boundary of the extended image for the contour integration method. As shown in the bottom panels, the improved accuracy of Twinkle's new method yields a more accurate image contour and hence more reliable magnification than conventional coefficient method.
Paper: Twinkle: A GPU-based Binary-lens Microlensing Code with the Contour Integration Method
Authors: Suwei Wang, Lile Wang, Subo Dong
Figure caption: Schematic examples of ghost image pair misjudgment near the critical curve. The magenta dots and the blue crosses are real images with positive and negative parity, while the gray diamonds are ghost images. The black line is the critical curve, on which a pair of real images could transfer into a pair of ghost images. Image pairs marked with the same text come from the same point sources. In the left panel, pair 1 are ghost images misjudged as real images, forming a wrong boundary of the extended image. The correct boundary near the critical curve is the connection of pair 0 images, as shown by the pink solid line. In the right panel, pair a and b are misjudged as real images, forming a fake piece of the image, and may cause spikes in the light curves.
Paper: Twinkle: A GPU-based Binary-lens Microlensing Code with the Contour Integration Method
Authors: Suwei Wang, Lile Wang, Subo Dong
Figure caption: An example of Twinkle robustness. The upper left panel shows the magnification calculated by Twinkle and VBBL, and the lower left panel shows the relative difference, with the horizontal pink lines representing tolerance and the horizontal axis representing the coordinate of source centers. The right panel is the relative position of the source and the planetary caustic, in which the red line is a planetary caustic, and the circles are extended source positions corresponding to data points in the left panels. The origin point is moved to the position of the planetary caustic, where Δθx = θ + 1.5000, Δθy = θy + 0.0035. The spikes in the left panel correspond to the black circles in the right panel, whose boundaries are near the cusp of the planetary caustic. The upper and lower black circles correspond to the right and left spikes, respectively.
Paper: Twinkle: A GPU-based Binary-lens Microlensing Code with the Contour Integration Method
Authors: Suwei Wang, Lile Wang, Subo Dong
Figure caption: Visualization of an extended source and the images. The left and right panels show the source and image planes, respectively. The caustic is shown in red, and the critical curve is displayed in black. The two black plus signs mark the positions of two lens objects. The source boundary in the left panel crosses the caustic twice, creating three complete image boundaries (1, 2, and 3 in the right panel) and two broken tracks (4 and 5). The points with the viridis color map in the right panel are real images belonging to the point sources with the same colors. The colors represent the source position angle θ. The real images inside the critical curve have negative parities and are marked by crosses, while the images outside (dots) have positive parities. The gray diamonds represent ghost images generated by points on the source boundary located outside the caustics.
Paper: Twinkle: A GPU-based Binary-lens Microlensing Code with the Contour Integration Method
Authors: Suwei Wang, Lile Wang, Subo Dong
Figure caption: The inverse transform method generates eight new samples. θ is the position angle of the sampling point source. The green line is the cumulative distribution function induced by the area error. The cyan quantiles distribute uniformly on the vertical axis, mapping to θ positions by finding the points on the cumulative distribution curve. Because the cumulative error rises sharply at the locations with greater errors, more sampling points are attracted there.
Paper: Twinkle: A GPU-based Binary-lens Microlensing Code with the Contour Integration Method
Authors: Suwei Wang, Lile Wang, Subo Dong
Figure caption: Calculation performance in parameter space. The upper row shares the same logarithmic color mapping, in which the blank region marks where VBBL takes an abnormally long calculation time. The bottom left panel is acceleration defined as the time ratio of Twinkle and single-thread VBBL. The bottom right panel is the error rate as the proportion of VBBL wrong results that exceed the tolerance compared to the results from Twinkle. The white region in the bottom right panel means no differences between Twinkle and VBBL magnification results. The green squares and pink dots are the published microlensing events and the simulated Roman detection.
Paper: Twinkle: A GPU-based Binary-lens Microlensing Code with the Contour Integration Method
Authors: Suwei Wang, Lile Wang, Subo Dong
Figure caption: CPU version performance in parameter space. The left panel shows the computational time used by the CPU version of Twinkle, with the same color mapping as the upper row of Figure 7. The right panel is the acceleration defined as the computation time ratio of the single-thread VBBL and single-thread CPU version of Twinkle. The green squares and pink dots are the published microlensing events and the simulated Roman detection.
Paper: Twinkle: A GPU-based Binary-lens Microlensing Code with the Contour Integration Method
Authors: Suwei Wang, Lile Wang, Subo Dong
Figure caption: Scaling relationship of computations performed by Twinkle. The horizontal axis is the number of sources in tasks, and the vertical axis is the computational time normalized by the linear fitting coefficient. Each source is dispatched to one block. The green data points are the calculation time used for different task scales. The blue solid line is the linear fitting of the task scale and time consumed. The pink vertical lines are multiples of the number of SMs. For the NVIDIA 4090 used in this paper, NSM = 128.
Paper: ALMA Spectral Survey of an Eruptive Young Star, V883 Ori (ASSAY). II. Freshly Sublimated Complex Organic Molecules in the Keplerian Disk
Authors: Jae-Hong Jeong, Jeong-Eun Lee, Seonjae Lee, Giseon Baek, Ji-Hyun Kang, Seokho Lee, Chul-Hwan Kim, Hyeong-Sik Yun, Yuri Aikawa, Gregory J. Herczeg, Doug Johnstone, Lucas Cieza
Figure caption: Figures to depict the line identification method. Left and middle panels: Four examples for XCLASS model spectra, overlaid on the observed spectra. The colored solid lines indicate acetone (CH3COCH3) and glycolaldehyde (CH2OHCHO) model spectra at two different column densities (N = 5.0 × 1018 cm−2, 5.0 × 1016 cm−2), respectively. The gray solid lines are the observed spectra, and gray dashed/dotted horizontal lines represent the 1σ/3σ levels of the observed spectrum. Right panel: As examples for fN, X (Equation (3)), we show the fN, X profiles for 10 molecules. The profiles are shown as solid lines for the six molecules whose ratios reached 100% (considered as detected) at some column density steps, and as dashed lines for the remaining four molecules.
Paper: ALMA Spectral Survey of an Eruptive Young Star, V883 Ori (ASSAY). II. Freshly Sublimated Complex Organic Molecules in the Keplerian Disk
Authors: Jae-Hong Jeong, Jeong-Eun Lee, Seonjae Lee, Giseon Baek, Ji-Hyun Kang, Seokho Lee, Chul-Hwan Kim, Hyeong-Sik Yun, Yuri Aikawa, Gregory J. Herczeg, Doug Johnstone, Lucas Cieza
Figure caption: Integrated intensity (left panel) and intensity-weighted velocity (right panel) maps of the CH3OH 2(1,1)–1(0,1) line, as a representative emission distribution for COMs in the V883 Ori disk. The structure in the left panel shows a ringlike shape, and the inner emission depression (r < ∼ 0﹩\mathop{.}\limits^{{\rm{^{\prime} }}{\rm{^{\prime} }}}﹩1) is due to the optically thick dust blocking the molecular emission. The integral of the velocity ranges from −3.5 to 3.5 km s−1. The images are clipped above the 4σ (1σ = 2.0 mJy beam−1) level. Black contours represent continuum emission at 5σ, 10σ, 25σ, 50σ, 100σ, 200σ, 400σ, 800σ, and 1600σ (1σ = 0.023 mJy beam−1). The three weakest black contours are shown as dotted lines, while the others are in solid lines. The beam is shown on the lower left corner of each panel. Please refer to J.-E. Lee et al. (2024a; Paper I) for the analysis of the emission structure of various simple molecules as well as COMs. This figure is reproduced using the data presented in Paper I.
Paper: ALMA Spectral Survey of an Eruptive Young Star, V883 Ori (ASSAY). II. Freshly Sublimated Complex Organic Molecules in the Keplerian Disk
Authors: Jae-Hong Jeong, Jeong-Eun Lee, Seonjae Lee, Giseon Baek, Ji-Hyun Kang, Seokho Lee, Chul-Hwan Kim, Hyeong-Sik Yun, Yuri Aikawa, Gregory J. Herczeg, Doug Johnstone, Lucas Cieza
Figure caption: The disk-averaged spectrum of V883 Ori. This is the observed spectrum extracted from the PC1 filtering, but not the reconstructed one through the dust attenuation and beam-filling factor correction. The upper panel shows the spectrum of the full frequency range covered in our observation of V883 Ori, after subtraction of the continuum level. The lower panel shows a randomly selected, zoomed-in spectrum of the blue-shaded region in the upper panel. The vertical color bars represent identified lines of COMs from our study. The red dashed/dotted horizontal lines represent the 1σ/3σ levels of the observed spectrum.
Paper: ALMA Spectral Survey of an Eruptive Young Star, V883 Ori (ASSAY). II. Freshly Sublimated Complex Organic Molecules in the Keplerian Disk
Authors: Jae-Hong Jeong, Jeong-Eun Lee, Seonjae Lee, Giseon Baek, Ji-Hyun Kang, Seokho Lee, Chul-Hwan Kim, Hyeong-Sik Yun, Yuri Aikawa, Gregory J. Herczeg, Doug Johnstone, Lucas Cieza
Figure caption: The continuum intensities as a function of spectral window weighted by the moment 0 map of the PCA Eigen cube 1. The red crosses indicate the corrected intensity of each spectral window. The thick blue line is the best-fit result of ﹩{T}_{\mathrm{cont}}\equiv \eta \times {T}_{\mathrm{rot}}\times (1-{e}^{-{\tau }_{\nu ,\mathrm{dust}}})﹩. The thin blue lines represent ±2% range.
Paper: ALMA Spectral Survey of an Eruptive Young Star, V883 Ori (ASSAY). II. Freshly Sublimated Complex Organic Molecules in the Keplerian Disk
Authors: Jae-Hong Jeong, Jeong-Eun Lee, Seonjae Lee, Giseon Baek, Ji-Hyun Kang, Seokho Lee, Chul-Hwan Kim, Hyeong-Sik Yun, Yuri Aikawa, Gregory J. Herczeg, Doug Johnstone, Lucas Cieza
Figure caption: Column densities of COMs relative to methanol for various hot corinos/cores studies. There are three types of markers: stars for three V883 Ori studies, diamonds for five studies of a single source, and boxplots for five survey studies. The boxes of the boxplots extend across the first (Q1) to the third (Q3) quartile of the data and have a line at the median. The whiskers extend from the box to the farthest data point that is within 1.5 times the Q3−Q1 range from the box. The outliers of the distribution are shown as open circles. In legends, we separate the V883 Ori, hot corinos, and hot cores studies into three groups. For CH2OHCHO, the upper limit of V883 Ori is marked.
Paper: ALMA Spectral Survey of an Eruptive Young Star, V883 Ori (ASSAY). II. Freshly Sublimated Complex Organic Molecules in the Keplerian Disk
Authors: Jae-Hong Jeong, Jeong-Eun Lee, Seonjae Lee, Giseon Baek, Ji-Hyun Kang, Seokho Lee, Chul-Hwan Kim, Hyeong-Sik Yun, Yuri Aikawa, Gregory J. Herczeg, Doug Johnstone, Lucas Cieza
Figure caption: Comparison of the column densities of molecules obtained by iterative LTE line fitting using only isolated, optically thin lines (τν,line < 0.7, corresponds to the column density result of the seventh iteration of Figure 5) and using isolated lines of all optical depths (corresponds to the result of the zeroth iteration of Figure 5). Each data point represents the derived column densities of a single species. Labeled molecules are the ones that show differences of larger than 0.2 dex. The line representing 1:1 is indicated by a gray dashed line. The lines representing 3 times and 10 times differences are shown as gray solid lines with dark and light gray shaded areas, respectively.