adsabs/AstroCLIMB huggingface dataset:
Paper: A 13 Billion Year View of Galaxy Growth: Metallicity Gradient Evolution from the Local Universe to z = 9 with JWST and Archival Surveys
Authors: Zihao Li, Zheng Cai, Xin Wang, Zhaozhou Li, Avishai Dekel, Kartick C. Sarkar, Eduardo Bañados, Fuyan Bian, Aklant K. Bhowmick, Laura Blecha, Sarah E. I. Bosman, Jaclyn B. Champagne, Xiaohui Fan, Emmet Golden-Marx, Hyunsung D. Jun, Mingyu Li, Xiaojing Lin, Weizhe Liu, Fengwu Sun, Maxime Trebitsch, Fabian Walter, Feige Wang, Yunjing Wu, Jinyi Yang, Huanian Zhang, Shiwu Zhang, Mingyang Zhuang, Siwei Zou
Figure caption: (a) A violin plot showing the mass distribution of our full sample at each redshift bin. The white circles represent the median stellar mass and redshift of each bin. The dotted lines represent 1σ intervals of the stellar mass distributions. (b) The redshift evolution of metallicity gradients with normalization by stellar masses. The dark-red lines represent the best fitting of the observed metallicity gradients, the same as those in Figure 2. The circles represent metallicity gradients normalized to a fixed stellar mass, with colors indicating stellar masses normalized relative to the observed MZGR at each redshift.
Paper: A 13 Billion Year View of Galaxy Growth: Metallicity Gradient Evolution from the Local Universe to z = 9 with JWST and Archival Surveys
Authors: Zihao Li, Zheng Cai, Xin Wang, Zhaozhou Li, Avishai Dekel, Kartick C. Sarkar, Eduardo Bañados, Fuyan Bian, Aklant K. Bhowmick, Laura Blecha, Sarah E. I. Bosman, Jaclyn B. Champagne, Xiaohui Fan, Emmet Golden-Marx, Hyunsung D. Jun, Mingyu Li, Xiaojing Lin, Weizhe Liu, Fengwu Sun, Maxime Trebitsch, Fabian Walter, Feige Wang, Yunjing Wu, Jinyi Yang, Huanian Zhang, Shiwu Zhang, Mingyang Zhuang, Siwei Zou
Figure caption: The comparison between the observed best-fit redshift evolution of metallicity gradients and predictions from different suites of cosmological simulations. The simulations including FIRE (X. Ma et al. 2017), FIRE-2 (X. Sun et al. 2025), TNG50 (Z. S. Hemler et al. 2021), EAGLE (P. B. Tissera et al. 2022), MUGS/MAGICC (B. K. Gibson et al. 2013), FOGGIE (A. Acharyya et al. 2025), and Illustris (A. M. Garcia et al. 2025) are marked in different colors.
Paper: Parkes Transient Events. II. Pulsar Single-pulses Database Containing Raw Data Segments
Authors: Xuan Yang, Songbo Zhang, Le-Yu Tang, L. Toomey, Xuefeng Wu
Figure caption: Fluence of 17,449 single pulses of PSR J1453–6413 from four observation epochs. The x-axis represents the pulse-train number relative to the start of the observation, measured in units of the rotating period (P0). Each observation epoch is indicated by a blue background. The red solid lines represent the rms level variation scaling to mean fluence level.
Paper: Orbits and Masses for 156 Companions from Combined Astrometry and Radial Velocities, and a Validation of Gaia Non-single-star Solutions
Authors: Qier An, Timothy D. Brandt, G. Mirek Brandt, Alexander Venner
Figure caption: Agreement between measured Gaia DR3 astrometric accelerations and results expected based on this work. The agreement is quantified by χ2 between the two sets of values, predicted and measured, for each of 11 stars. Seven-parameter fit systems are shaded in gray, and nine-parameter fit systems are shaded in orange. The probability density function for the χ2 distribution with 2 degrees of freedom (as ﹩dp/d({\mathrm{ln}}\,{\chi }^{2})﹩) is plotted in red for reference. Seven of the 11 available comparisons are consistent with the red theoretical curve, while the remaining four are moderately discrepant.
Paper: Orbits and Masses for 156 Companions from Combined Astrometry and Radial Velocities, and a Validation of Gaia Non-single-star Solutions
Authors: Qier An, Timothy D. Brandt, G. Mirek Brandt, Alexander Venner
Figure caption: Observed RVs of HIP 42030, plotted alongside the best-fit orbital model (black) and random draws (color coded by mass of HIP 42030 c) from the MCMC chain. The short-term deviations reveal the presence of planet b, whereas the limited long-term coverage drives the orbit of planet c.
Paper: Orbits and Masses for 156 Companions from Combined Astrometry and Radial Velocities, and a Validation of Gaia Non-single-star Solutions
Authors: Qier An, Timothy D. Brandt, G. Mirek Brandt, Alexander Venner
Figure caption: RV time series of HIP 101597.
Paper: Statistical Analyses of Solar Active Regions in SDO/HMI Magnetograms Detected by the Unsupervised Machine Learning Method DSARD
Authors: R. Chen, W. Lu, Q. Hao, Y. Meng, P. F. Chen, C. Shi
Figure caption: An observation taken on 2022 November 12 as an example to show the processing modules of the automated detection system. (a) The original observation obtained by SDO/HMI. (b) The magnetogram after threshold segmentation. (c) The detected result after the first (global) DBSCAN clustering, with each red box representing a cluster. (d) The detected result after the second (reformative) DBSCAN clustering. (e) The final detected AR results after filtering, merging, and labeling the clusters obtained from DSARD. Each red box with a number represents a bounding rectangle of the identified solar AR. (f) NOAA-identified solar active regions on the same day for comparison.
Paper: Statistical Analyses of Solar Active Regions in SDO/HMI Magnetograms Detected by the Unsupervised Machine Learning Method DSARD
Authors: R. Chen, W. Lu, Q. Hao, Y. Meng, P. F. Chen, C. Shi
Figure caption: An example to compare the ARs detected by the present method and the classical image-processing method. (a) The results detected by the present method are shown in the top panel, which are equivalent to those illustrated in Figure 1(e). (b) The results detected by the classical image-processing method based on the region-growing algorithm. The middle panels display enlarged sections of the blue box regions. The bottom panels are specific enlarged ARs detected by DSARD.
Paper: Statistical Analyses of Solar Active Regions in SDO/HMI Magnetograms Detected by the Unsupervised Machine Learning Method DSARD
Authors: R. Chen, W. Lu, Q. Hao, Y. Meng, P. F. Chen, C. Shi
Figure caption: Butterfly diagram and latitudinal migration of ARs during solar cycle 24 and the rising phase of solar cycle 25. (a) Butterfly diagram of active regions from 2010 to 2023. Each dot represents a single AR, with the size and color of the dot corresponding to the respective area of the active region. (b) Temporal evolution of the monthly average latitude of active regions in the northern (blue dots) and southern (orange dots) hemispheres, with the blue and orange lines representing the cubic polynomial fitted lines of the monthly average latitude of active regions. The dashed vertical line indicates the beginning of solar cycle 25. (c) Fitted variations in drift velocity in the northern (blue line) and southern (orange line) hemispheres.
Paper: Statistical Analyses of Solar Active Regions in SDO/HMI Magnetograms Detected by the Unsupervised Machine Learning Method DSARD
Authors: R. Chen, W. Lu, Q. Hao, Y. Meng, P. F. Chen, C. Shi
Figure caption: Distribution of the numbers of ARs detected by our method, the NOAA catalog, and the SHARP catalog from 2010 to 2023 within a longitudinal range limit of ±6° from the central meridian of the solar disk. (a) Distribution of the total AR number from 2010 to 2023. Each dot represents the sum of the AR numbers per month. Panels (b) and (c) are similar to panel (a) but for the number of ARs in the northern and southern hemispheres, respectively.
Paper: Statistical Analyses of Solar Active Regions in SDO/HMI Magnetograms Detected by the Unsupervised Machine Learning Method DSARD
Authors: R. Chen, W. Lu, Q. Hao, Y. Meng, P. F. Chen, C. Shi
Figure caption: (a) Distribution of AR numbers in different area ranges with respect to year from 2010 to 2023. (b) Distribution of AR numbers in different area ranges with respect to latitude during solar cycle 24. Panel (c) is similar to (b) but for that during the rising phase of solar cycle 25.
Paper: Statistical Analyses of Solar Active Regions in SDO/HMI Magnetograms Detected by the Unsupervised Machine Learning Method DSARD
Authors: R. Chen, W. Lu, Q. Hao, Y. Meng, P. F. Chen, C. Shi
Figure caption: Histograms of active regions showing their distribution with latitude. (a) Total events; (b) active regions in solar cycle 24; (c) active regions in the rising phase of solar cycle 25.
Paper: Statistical Analyses of Solar Active Regions in SDO/HMI Magnetograms Detected by the Unsupervised Machine Learning Method DSARD
Authors: R. Chen, W. Lu, Q. Hao, Y. Meng, P. F. Chen, C. Shi
Figure caption: An observation taken on 2014 August 2 as an example to show the results detected by DSARD, as well as those from the SHARP and NOAA catalogs. The middle panel shows the ARs detected by DSARD, represented by red boxes within a blue box. This is an enlarged subimage from the left panel. The right panel shows the SHARP regions, represented by a green box, with annotations from the NOAA catalog.
Paper: Statistical Analyses of Solar Active Regions in SDO/HMI Magnetograms Detected by the Unsupervised Machine Learning Method DSARD
Authors: R. Chen, W. Lu, Q. Hao, Y. Meng, P. F. Chen, C. Shi
Figure caption: Distribution of cumulative area and magnetic flux with respect to latitudes and years.
Paper: Statistical Analyses of Solar Active Regions in SDO/HMI Magnetograms Detected by the Unsupervised Machine Learning Method DSARD
Authors: R. Chen, W. Lu, Q. Hao, Y. Meng, P. F. Chen, C. Shi
Figure caption: Similar to Figure 8 but for the magnetic flux.
Paper: Statistical Analyses of Solar Active Regions in SDO/HMI Magnetograms Detected by the Unsupervised Machine Learning Method DSARD
Authors: R. Chen, W. Lu, Q. Hao, Y. Meng, P. F. Chen, C. Shi
Figure caption: Yearly asymmetries of the number and cumulative area (upper panel), and total flux, cumulative positive flux, and negative flux (lower panel) of all ARs.
Paper: Statistical Analyses of Solar Active Regions in SDO/HMI Magnetograms Detected by the Unsupervised Machine Learning Method DSARD
Authors: R. Chen, W. Lu, Q. Hao, Y. Meng, P. F. Chen, C. Shi
Figure caption: Variation of true positive rate RTP (a) and false positive rate RFP (b) based on the NOAA catalog and SHARP catalog from 2010 to 2023.
Paper: Statistical Analyses of Solar Active Regions in SDO/HMI Magnetograms Detected by the Unsupervised Machine Learning Method DSARD
Authors: R. Chen, W. Lu, Q. Hao, Y. Meng, P. F. Chen, C. Shi
Figure caption: Distribution of average relative latitude of magnetic bipolar ARs with respect to years. The butterfly diagram is represented by light blue dots. The average latitudes of positive and negative polarities are indicated by red and black dots, respectively. The lines connecting the bipoles illustrate the tilt angle at a specific latitude and time. To present the difference in tilt angles more clearly, they are multiplied by a factor of 8 to enlarge the angle differences.
Paper: Statistical Analyses of Solar Active Regions in SDO/HMI Magnetograms Detected by the Unsupervised Machine Learning Method DSARD
Authors: R. Chen, W. Lu, Q. Hao, Y. Meng, P. F. Chen, C. Shi
Figure caption: Latitudinal distribution of average AR tilt angles in every 5° interval during solar cycle 24. Panels (a)–(d) are the latitudinal distribution of average ARs tilt angles in every 5° interval within the area ranges <50 millionth, 50–250 millionth , 250–500 millionth, and >500 millionth, respectively. The error bars represent the 95% confidence interval, while the circles and squares symbolize the signs of average tilt angles. Red and blue are used to indicate tilt angles in the northern and southern hemispheres, respectively. The blue vertical lines represent the cumulative magnetic flux in every 5° interval.
Paper: Statistical Analyses of Solar Active Regions in SDO/HMI Magnetograms Detected by the Unsupervised Machine Learning Method DSARD
Authors: R. Chen, W. Lu, Q. Hao, Y. Meng, P. F. Chen, C. Shi
Figure caption: Latitudinal distribution of ARs categorized by whether they violate Hale’s law. (a) Latitudinal distribution of regular and anti-Hale ARs during solar cycle 24, with red and blue dots representing regular and anti-Hale ARs, respectively. The histogram on the right side of the figure presents the distribution of AR numbers for regular and anti-Hale ARs in different latitude bands. Panel (b) is similar to (a) but for those during the rising phase of solar cycle 25.
Paper: Statistical Analyses of Solar Active Regions in SDO/HMI Magnetograms Detected by the Unsupervised Machine Learning Method DSARD
Authors: R. Chen, W. Lu, Q. Hao, Y. Meng, P. F. Chen, C. Shi
Figure caption: Similar to Figure 13 but for the rising phase of solar cycle 25.
Paper: Statistical Analyses of Solar Active Regions in SDO/HMI Magnetograms Detected by the Unsupervised Machine Learning Method DSARD
Authors: R. Chen, W. Lu, Q. Hao, Y. Meng, P. F. Chen, C. Shi
Figure caption: Influence of ﹩{P}_{{{\rm{\min }}}_{1}}﹩ on clustering results, using an observation from 2022 November 12. Columns show results for ﹩{P}_{{{\rm{\min }}}_{1}}=100﹩, 200, and 400. Top: first-stage DBSCAN results. Bottom: final output.
Paper: Statistical Analyses of Solar Active Regions in SDO/HMI Magnetograms Detected by the Unsupervised Machine Learning Method DSARD
Authors: R. Chen, W. Lu, Q. Hao, Y. Meng, P. F. Chen, C. Shi
Figure caption: Influence of ﹩{P}_{{{\rm{\min }}}_{2}}﹩ on clustering results, using an observation from 2022 November 12. Columns show results for ﹩{P}_{{{\rm{\min }}}_{2}}=300﹩, 500, and 1000. Top: second-stage DBSCAN results. Bottom: final output.
Paper: Statistical Analyses of Solar Active Regions in SDO/HMI Magnetograms Detected by the Unsupervised Machine Learning Method DSARD
Authors: R. Chen, W. Lu, Q. Hao, Y. Meng, P. F. Chen, C. Shi
Figure caption: Effect of maxSize on DSARD results for 2022 November 12. Columns show results for maxSize = 0, 3000, and 10,000. Top: second-stage DBSCAN results. Bottom: final output.
Paper: Statistical Properties of Solar Wind and Interplanetary Magnetic Field Upstream of Planets at 1 au and Beyond: A Comprehensive Analysis
Authors: Tao Tang, Ruilong Guo, Quanqi Shi, Jong-Sun Park, Xiao Ma, Jinyan Zhao, Xuzhi Zhou, Hui Zhang, Limei Yan, Anmin Tian, Shichen Bai, Yijia Zhou, Alexander William Degeling, Yuchen Xiao, Qiugang Zong
Figure caption: Radial dependence of solar wind magnetic field components across heliocentric distance: (a) magnitude of magnetic field (B), (b) radial component (|BR|), (c) tangential component (|BT|), and (d) normal component (|BN|). The blue, red, yellow, and brown markers represent the mean values of parameter statistics at Earth, Mars, Jupiter, and Saturn, respectively. Filled yellow triangles and stars represent Juno and Galileo data, with their heliocentric distances shifted by ±0.2 au to avoid overlap. The gray-dashed lines indicate the fitted results, excluding data from Galileo and Juno. The fitting coefficients and their errors are provided in each panel, and the green-dashed line represents the empirical formula proposed by L. F. Burlaga et al. (1984). Error bars indicate the standard error of the mean.
Paper: Statistical Properties of Solar Wind and Interplanetary Magnetic Field Upstream of Planets at 1 au and Beyond: A Comprehensive Analysis
Authors: Tao Tang, Ruilong Guo, Quanqi Shi, Jong-Sun Park, Xiao Ma, Jinyan Zhao, Xuzhi Zhou, Hui Zhang, Limei Yan, Anmin Tian, Shichen Bai, Yijia Zhou, Alexander William Degeling, Yuchen Xiao, Qiugang Zong
Figure caption: Example of solar wind interval selection and plasma moment fitting for Cassini. (a) Magnetic field, (b) ion differential energy spectrum, (c) electron differential energy spectrum, and (d) plasma moment fitting for the CAPS. Red-shaded areas at the top denote the selected solar wind times, green-shaded areas indicate solar wind periods detected by CAPS, and black-shaded areas represent intervals inside Saturn’s bow shock. The vertical black dashed lines in panels (a)–(c) mark the time selected for plasma moment fitting in panel (d). In panel (d), black dots show ion phase space densities, and the red curve represents the fit from Equation (4). Derived plasma parameters (Np,fitted: proton density, Tp,fitted: proton temperature, and Em: mean kinetic energy) and uncertainties are annotated in blue text. The coefficient of determination (R2) quantifies the goodness of fit.
Paper: Statistical Properties of Solar Wind and Interplanetary Magnetic Field Upstream of Planets at 1 au and Beyond: A Comprehensive Analysis
Authors: Tao Tang, Ruilong Guo, Quanqi Shi, Jong-Sun Park, Xiao Ma, Jinyan Zhao, Xuzhi Zhou, Hui Zhang, Limei Yan, Anmin Tian, Shichen Bai, Yijia Zhou, Alexander William Degeling, Yuchen Xiao, Qiugang Zong
Figure caption: (a)–(c) The statistical distributions of BR, BT, and IMF θa at Earth; (d)–(f) at Mars; (g)–(i) at Jupiter; and (j)–(l) at Saturn distances. The statistical mean (red solid line), standard deviation (red-dashed line), and median (blue-dashed line) are given in the panels for the parameters BR and BT, and the fitted peak position is given in the panels for the parameter IMF θa. At Jupiter, the Juno (yellow bar) and Galileo (green bar) spacecraft statistics are included. However, the Juno and Galileo data were not used to calculate the mean, standard deviation, median, and peak fitting.
Paper: Statistical Properties of Solar Wind and Interplanetary Magnetic Field Upstream of Planets at 1 au and Beyond: A Comprehensive Analysis
Authors: Tao Tang, Ruilong Guo, Quanqi Shi, Jong-Sun Park, Xiao Ma, Jinyan Zhao, Xuzhi Zhou, Hui Zhang, Limei Yan, Anmin Tian, Shichen Bai, Yijia Zhou, Alexander William Degeling, Yuchen Xiao, Qiugang Zong
Figure caption: The variations of Np, Pdyn, E, β, V, and VA with heliocentric distance are shown in panels (a)–(f), respectively. The blue, red, yellow, and brown dots (crosses) represent the mean (median) values of parameter statistics at Earth, Mars, Jupiter, and Saturn, respectively. Error bars indicate the standard error of the mean. Red asterisks denote parameters that deviate significantly from actual values, caused by either low-density results from Cassini or high-temperature data from MAVEN. The statistical results from E. Echer (2019) for the upstream of Saturn were adopted as reference values (represented by purple dots for means and purple crosses for medians), with the heliocentric distance fixed at 9 au to avoid symbol overlap.
Paper: Statistical Properties of Solar Wind and Interplanetary Magnetic Field Upstream of Planets at 1 au and Beyond: A Comprehensive Analysis
Authors: Tao Tang, Ruilong Guo, Quanqi Shi, Jong-Sun Park, Xiao Ma, Jinyan Zhao, Xuzhi Zhou, Hui Zhang, Limei Yan, Anmin Tian, Shichen Bai, Yijia Zhou, Alexander William Degeling, Yuchen Xiao, Qiugang Zong
Figure caption: (a) Sunspot number variation over time, with the blue line representing the monthly averaged sunspot number and the black line representing the smoothed sunspot number. (b) The blue, red, yellow, gray, green, and brown horizontal bars indicate the data collection periods of the ACE (Earth), MAVEN (Mars), Ulysses (Jupiter), Juno (Jupiter), Galileo (Jupiter), and Cassini (Saturn) spacecraft, respectively. Note that Cassini near Saturn acquired only magnetic field data without plasma measurements from 2012 June to 2016 July. The red, green, blue, and purple background color blocks represent the solar activity phases: solar maximum, descending, minimum, and ascending phases, respectively.
Paper: Statistical Properties of Solar Wind and Interplanetary Magnetic Field Upstream of Planets at 1 au and Beyond: A Comprehensive Analysis
Authors: Tao Tang, Ruilong Guo, Quanqi Shi, Jong-Sun Park, Xiao Ma, Jinyan Zhao, Xuzhi Zhou, Hui Zhang, Limei Yan, Anmin Tian, Shichen Bai, Yijia Zhou, Alexander William Degeling, Yuchen Xiao, Qiugang Zong
Figure caption: An example of solar wind interval selection for MAVEN. (a) Magnetic field, (b) proton density, (c) velocity, (d) temperature, and (e) ion differential energy spectrum. Red-shaded areas at the top denote selected intervals outside the Martian bow shock, black-shaded areas correspond to intervals inside the Martian bow shock, and the green-shaded areas represent the selected solar wind times.
Paper: Statistical Properties of Solar Wind and Interplanetary Magnetic Field Upstream of Planets at 1 au and Beyond: A Comprehensive Analysis
Authors: Tao Tang, Ruilong Guo, Quanqi Shi, Jong-Sun Park, Xiao Ma, Jinyan Zhao, Xuzhi Zhou, Hui Zhang, Limei Yan, Anmin Tian, Shichen Bai, Yijia Zhou, Alexander William Degeling, Yuchen Xiao, Qiugang Zong
Figure caption: Schematic definition of (a) IMF clock angle θc and (b) IMF azimuth angle θa in the RTN coordinate system.
Paper: Statistical Properties of Solar Wind and Interplanetary Magnetic Field Upstream of Planets at 1 au and Beyond: A Comprehensive Analysis
Authors: Tao Tang, Ruilong Guo, Quanqi Shi, Jong-Sun Park, Xiao Ma, Jinyan Zhao, Xuzhi Zhou, Hui Zhang, Limei Yan, Anmin Tian, Shichen Bai, Yijia Zhou, Alexander William Degeling, Yuchen Xiao, Qiugang Zong
Figure caption: Comparison of solar wind measurements between MMS4 spacecraft and OMNI database from 2017 November 9 15:00 to 2017 November 10 15:00 UTC, along with derived parameters from plasma moment fitting for different FOVs. (a) Magnetic field in GSE coordinates, (b) ion (proton) density, (c) ion (proton) bulk velocity, (d) ion (proton) temperature, and (e) ion differential energy spectrum measured by the MMS4 FPI Instrument. In panel (a), solid red, green, and blue lines represent Bx, By, and Bz from MMS4 FGM measurements, while dashed lines with corresponding colors show OMNI database values. In panels (b)–(d), black solid lines indicate MMS4 FPI measurements and green solid lines denote OMNI proton data, while red, blue, and purple dashed lines display proton parameters derived from plasma moment fitting. The different color dashed lines in panels (b)–(d) correspond to distinct FOV configurations: red represents the omnidirectional FOV, whereas blue and purple denote manually constrained FOV1 and FOV2, respectively. The data in panels (a)–(d) are all plotted with a time resolution of 1 minute.
Paper: Statistical Properties of Solar Wind and Interplanetary Magnetic Field Upstream of Planets at 1 au and Beyond: A Comprehensive Analysis
Authors: Tao Tang, Ruilong Guo, Quanqi Shi, Jong-Sun Park, Xiao Ma, Jinyan Zhao, Xuzhi Zhou, Hui Zhang, Limei Yan, Anmin Tian, Shichen Bai, Yijia Zhou, Alexander William Degeling, Yuchen Xiao, Qiugang Zong
Figure caption: Statistical analysis of solar wind parameters from the Ulysses spacecraft at different locations. (a)–(i) The spatial distribution of the average B, |BR|, |BT|, NP, V, Tp, E, Mms, and PSA bias, respectively. In panel (a), the black arrows represent the projection of the IMF in the ρZ plane, with BR set to a positive value when calculating the projection. In panel (i), the angle between the black (red) arrows and the +ρ-axis reflects the IMF SA (PSA). Red dots mark the Sun’s position, and the gray-dashed lines are concentric circles spaced at 1 au intervals. The color bar represents the average parameter magnitudes.