adsabs/AstroCLIMB huggingface dataset:
Paper: Investigations of MWISP Clumps: 13CO Clump Source Catalog and Physical Properties
Authors: Yu Jiang, Qing-Zeng Yan, Ji Yang, Sheng Zheng, Xuepeng Chen, Yang Su, Zhibo Jiang, Zhiwei Chen, Xin Zhou, Yao Huang, Xiaoyu Luo, Haoran Feng, De-Jian Liu
Figure caption: Parameter loss example for the clump located in the upper right corner of Figure 1(d). The panels show how physical properties vary with normalized temperature gradient (TEdge/Tmax): (a) flux decreases by 6.5%, (b) σv decreases by 7.6%, and (c) Req decreases by 4.0%. Blue dots represent observational measurements sampled at TEdge intervals of ∼0.22 K, corresponding to the typical instrumental noise level. Red curves show cubic polynomial fits to the data, while green crosses indicate extrapolated values at the theoretical zero-intensity boundary.
Paper: Investigations of MWISP Clumps: 13CO Clump Source Catalog and Physical Properties
Authors: Yu Jiang, Qing-Zeng Yan, Ji Yang, Sheng Zheng, Xuepeng Chen, Yang Su, Zhibo Jiang, Zhiwei Chen, Xin Zhou, Yao Huang, Xiaoyu Luo, Haoran Feng, De-Jian Liu
Figure caption: Examples of MWISP clumps. Row 1: clump corresponding to the maximum intensity (position: [15﹩\mathop{.}\limits^{\unicode{x000b0}}﹩017, −0﹩\mathop{.}\limits^{\unicode{x000b0}}﹩667, 19.261 km s−1]). Row 2: clump with the maximum mass. Row 3: clump with the minimum mass. Row 4: the most massive maser-hosting clump. Row 5: the least massive maser-hosting clump. Columns from left to right: (a) velocity-integrated intensity maps, (b) optical depth maps, (c) excitation temperature maps, and (d) mass maps. Labels show the catalog ID, Galactic coordinates, total flux, mean optical depth, mean excitation temperature, and total mass.
Paper: Investigations of MWISP Clumps: 13CO Clump Source Catalog and Physical Properties
Authors: Yu Jiang, Qing-Zeng Yan, Ji Yang, Sheng Zheng, Xuepeng Chen, Yang Su, Zhibo Jiang, Zhiwei Chen, Xin Zhou, Yao Huang, Xiaoyu Luo, Haoran Feng, De-Jian Liu
Figure caption: Scaling relations between extrapolated physical parameters of MWISP. Panels show (a) M–Req, (b) n(H2)–Req, (c) αvir–Req, (d) σv–Req, (e) σv–M, (f) σv–ReqΣ, (g) N(13CO)–Req, (h) αvir–N(13CO), and (i) σv–N(13CO). The distributions are shown for four subsets: MWISP complete clumps (cyan contours), all extrapolated MWISP clumps (colored points with green contours), extrapolated CMD-C (blue contours), and extrapolated CMD-H (red contours). For each relation, the best-fit power-law index and corresponding P are indicated in the legend.
Paper: Investigations of MWISP Clumps: 13CO Clump Source Catalog and Physical Properties
Authors: Yu Jiang, Qing-Zeng Yan, Ji Yang, Sheng Zheng, Xuepeng Chen, Yang Su, Zhibo Jiang, Zhiwei Chen, Xin Zhou, Yao Huang, Xiaoyu Luo, Haoran Feng, De-Jian Liu
Figure caption: Probability distribution function histograms for six physical parameters. Panels show (a) M, (b) Req, (c) σv, (d) αvir, (e) Σ, and (f) n(H2). Each subplot compares data from MWISP, CHIMPS, and SEDIGISM, with their respective median values marked.
Paper: Investigations of MWISP Clumps: 13CO Clump Source Catalog and Physical Properties
Authors: Yu Jiang, Qing-Zeng Yan, Ji Yang, Sheng Zheng, Xuepeng Chen, Yang Su, Zhibo Jiang, Zhiwei Chen, Xin Zhou, Yao Huang, Xiaoyu Luo, Haoran Feng, De-Jian Liu
Figure caption: Probability density distributions of parameter loss rates for all MWISP clumps. The panels display (a) the flux loss with a median value of −12.4%, (b) the σv loss with a median value of −5.7%, and (c) the Req loss with a median value of −6.1%. The dashed vertical lines indicate the median values.
Paper: Efficient Searches for Small Signals across Two-channel Noisy Data: A Challenge in Big-data Observations
Authors: Maryam Aghaei Abchouyeh, Maurice H. P. M. van Putten, Seyong Kim
Figure caption: Efficiency of GPU performance with respect to data array size, here shown for FFT pertinent to FFT-based signal processing. Efficiency critically depends on footprint in memory. Shown is a significant drop to memory bandwidth-limited performance when the array size exceeds local memory, causing calls to much slower global memory within the GPU. (Reprinted from M. H. P. M. van Putten et al. 2025.)
Paper: Efficient Searches for Small Signals across Two-channel Noisy Data: A Challenge in Big-data Observations
Authors: Maryam Aghaei Abchouyeh, Maurice H. P. M. van Putten, Seyong Kim
Figure caption: Spectrograms of simulated data used in the present benchmark study of two-channel observations by correlation, covering three types of background noise—Gaussian, Poisson, and uniform—and five types of signals—Gaussian, Poisson, uniform, chirp, and sine wave. Spectrograms are shown in pairs (one for each channel). Highlighted is the case of a relatively large signal amplitude clearly showing chirps and sine waves transient signals. Here we take λ = 10,000 for the Poisson background and signal strength α = 1 for illustrative purposes.
Paper: Asteroid Types, Albedos, and Diameters Catalog from Gaia DR3: Intelligent Inversion Results via Multisource Information Fusion
Authors: Jiayi Ge, Xiaoming Zhang, Juan Li, Huijuan Wang, Dawei Xu, Xiaojun Jiang
Figure caption: Impact of input information on model performance. Error bars represent the standard deviation of RMSE across the tenfold validation set. Initial refers to the combination of H, initial albedo, and initial diameter.
Paper: Asteroid Types, Albedos, and Diameters Catalog from Gaia DR3: Intelligent Inversion Results via Multisource Information Fusion
Authors: Jiayi Ge, Xiaoming Zhang, Juan Li, Huijuan Wang, Dawei Xu, Xiaojun Jiang
Figure caption: Overall accuracy of physical parameters in the AGAI catalog. Panel (a) shows the accuracy for types. Panels (b) and (c) display the errors for albedo and diameter, respectively. The solid red line represents the MAPE achieved by the proposed AadRF model, while the dashed red line refers to the traditional method, which uses the average albedo from type statistics and calculates the diameter using the Bowell relationship. The green line shows the MAPE in different bins of AadRF, and the black line shows the sample distribution. Reference values for error computation are primarily derived from NEOWISE.
Paper: Asteroid Types, Albedos, and Diameters Catalog from Gaia DR3: Intelligent Inversion Results via Multisource Information Fusion
Authors: Jiayi Ge, Xiaoming Zhang, Juan Li, Huijuan Wang, Dawei Xu, Xiaojun Jiang
Figure caption: Increment in sample counts of asteroid parameters. Known types are mainly derived from multicolor photometry and some from spectral classifications; albedo and diameter are primarily obtained through thermal model fitting and related calculations. “Others” include less common sources such as occultation, radar, and spacecraft missions. The green bars indicate the increment from this work.
Paper: Asteroid Types, Albedos, and Diameters Catalog from Gaia DR3: Intelligent Inversion Results via Multisource Information Fusion
Authors: Jiayi Ge, Xiaoming Zhang, Juan Li, Huijuan Wang, Dawei Xu, Xiaojun Jiang
Figure caption: Abundance of asteroid types and albedo distribution in AGAI catalog.
Paper: Asteroid Types, Albedos, and Diameters Catalog from Gaia DR3: Intelligent Inversion Results via Multisource Information Fusion
Authors: Jiayi Ge, Xiaoming Zhang, Juan Li, Huijuan Wang, Dawei Xu, Xiaojun Jiang
Figure caption: Correlation matrix of asteroid parameters.
Paper: Asteroid Types, Albedos, and Diameters Catalog from Gaia DR3: Intelligent Inversion Results via Multisource Information Fusion
Authors: Jiayi Ge, Xiaoming Zhang, Juan Li, Huijuan Wang, Dawei Xu, Xiaojun Jiang
Figure caption: Albedo and diameter errors of the AGAI catalog.
Paper: Asteroid Types, Albedos, and Diameters Catalog from Gaia DR3: Intelligent Inversion Results via Multisource Information Fusion
Authors: Jiayi Ge, Xiaoming Zhang, Juan Li, Huijuan Wang, Dawei Xu, Xiaojun Jiang
Figure caption: Model architecture of AadRF. Difference: adjacent-wavelength reflectance differences for spectral enhancement. Bottleneck: residual block with skip connections to improve network depth. AvgPool: 1D average pooling used for spectral feature compression.
Paper: Asteroid Types, Albedos, and Diameters Catalog from Gaia DR3: Intelligent Inversion Results via Multisource Information Fusion
Authors: Jiayi Ge, Xiaoming Zhang, Juan Li, Huijuan Wang, Dawei Xu, Xiaojun Jiang
Figure caption: Error distribution of albedo and diameter from NEOWISE.
Paper: Asteroid Types, Albedos, and Diameters Catalog from Gaia DR3: Intelligent Inversion Results via Multisource Information Fusion
Authors: Jiayi Ge, Xiaoming Zhang, Juan Li, Huijuan Wang, Dawei Xu, Xiaojun Jiang
Figure caption: Albedo and diameter distribution in samples.
Paper: Digitization of Astronomical Photographic Plates from China: Photometric Calibration of Single-exposure Plates and Release of Photometric Catalogs
Authors: Mingyang Ma, Haibo Yuan, Kai Xiao, Bowen Huang, Tao Wang, Yang Huang, Shiyin Shen, Zhengjun Shang, Yong Yu, Liangliang Wang, Meiting Yang, Jing Yang, Min Liu, Quanfeng Xu, Chenzhou Cui, Dongwei Fan, Zhenghong Tang, Jianhai Zhao
Figure caption: Calibration results of QD830883-20001. Panels (a)–(b) show instrumental magnitude vs. standard magnitude before and after large-scale flat-field correction, respectively. The distribution is much tighter after the correction. Panel (c) displays the large-scale flat field. Panels (d)–(f) plot the final magnitude, color, and flat-field terms, respectively. The blue curves in panels (d)–(e) are the fitted polynomials. The relatively small-scale structure is visible in panel (f). The overall flat-field structure closely resembles that of Figure 5. Panels (g)–(i) show the differences between the calibrated magnitudes and the standard magnitudes as a function of minst, BP − RP, and plate coordinates, respectively. The red dashed lines in panels (g)–(h) indicate the median differences; no further trends are found. The yellow dashed lines in panel (g) indicate the 3σ standard deviations. The overall standard deviation is also marked. The red dots are candidates of variable stars.
Paper: Digitization of Astronomical Photographic Plates from China: Photometric Calibration of Single-exposure Plates and Release of Photometric Catalogs
Authors: Mingyang Ma, Haibo Yuan, Kai Xiao, Bowen Huang, Tao Wang, Yang Huang, Shiyin Shen, Zhengjun Shang, Yong Yu, Liangliang Wang, Meiting Yang, Jing Yang, Min Liu, Quanfeng Xu, Chenzhou Cui, Dongwei Fan, Zhenghong Tang, Jianhai Zhao
Figure caption: An example (SH1301382001 from SHAO) to demonstrate the selection process of the closest JKC passband. The rows from top to bottom are for results of the U/B/V/R/I bands, respectively. For each row, the left panel shows the magnitude differences as a function of instrumental magnitude, where the red line indicates the polynomial fitting result. The middle panel shows the magnitude differences as a function of BP − RP. The right panel shows the fitting residuals as a function of BP − RP, where k represents the slope of the linear regression.
Paper: Digitization of Astronomical Photographic Plates from China: Photometric Calibration of Single-exposure Plates and Release of Photometric Catalogs
Authors: Mingyang Ma, Haibo Yuan, Kai Xiao, Bowen Huang, Tao Wang, Yang Huang, Shiyin Shen, Zhengjun Shang, Yong Yu, Liangliang Wang, Meiting Yang, Jing Yang, Min Liu, Quanfeng Xu, Chenzhou Cui, Dongwei Fan, Zhenghong Tang, Jianhai Zhao
Figure caption: The calibration statistics. Rows from top to bottom show the SHAO, NAOC, PMO, YNO, and QDO plates, respectively. The left and middle columns show the histogram distributions of photometric precision of different filters and plate grades, respectively. The number of plates and median precision are labeled. The right column plots precision as a function of observational time.
Paper: Asteroid Types, Albedos, and Diameters Catalog from Gaia DR3: Intelligent Inversion Results via Multisource Information Fusion
Authors: Jiayi Ge, Xiaoming Zhang, Juan Li, Huijuan Wang, Dawei Xu, Xiaojun Jiang
Figure caption: Statistical distributions of asteroid diameter, albedo, and type for different orbital groups. NEAs consist specifically of the Amor, Apollo, and Aten subgroups. Each panel includes three sections: the top subplot shows sample counts across diameter ranges; the middle panel displays albedo vs. diameter distributions; and the bottom subplot shows the fraction of each type.
Paper: Digitization of Astronomical Photographic Plates from China: Photometric Calibration of Single-exposure Plates and Release of Photometric Catalogs
Authors: Mingyang Ma, Haibo Yuan, Kai Xiao, Bowen Huang, Tao Wang, Yang Huang, Shiyin Shen, Zhengjun Shang, Yong Yu, Liangliang Wang, Meiting Yang, Jing Yang, Min Liu, Quanfeng Xu, Chenzhou Cui, Dongwei Fan, Zhenghong Tang, Jianhai Zhao
Figure caption: Color–magnitude diagram of the globular cluster M4. The MagB and MagV magnitudes are from the calibrated catalogs; the B and V magnitudes are from Gaia DR3. The red dots represent the member stars, and the gray dots are the other field stars.
Paper: Digitization of Astronomical Photographic Plates from China: Photometric Calibration of Single-exposure Plates and Release of Photometric Catalogs
Authors: Mingyang Ma, Haibo Yuan, Kai Xiao, Bowen Huang, Tao Wang, Yang Huang, Shiyin Shen, Zhengjun Shang, Yong Yu, Liangliang Wang, Meiting Yang, Jing Yang, Min Liu, Quanfeng Xu, Chenzhou Cui, Dongwei Fan, Zhenghong Tang, Jianhai Zhao
Figure caption: Examples of removing false stars. Panels (a)–(b) are for plates SH6001G60119001 and BJ7004DA757k001, respectively. The horizontal and vertical dashed lines indicate the cuts on std_mag_cut and inst_mag_cut, respectively.
Paper: Digitization of Astronomical Photographic Plates from China: Photometric Calibration of Single-exposure Plates and Release of Photometric Catalogs
Authors: Mingyang Ma, Haibo Yuan, Kai Xiao, Bowen Huang, Tao Wang, Yang Huang, Shiyin Shen, Zhengjun Shang, Yong Yu, Liangliang Wang, Meiting Yang, Jing Yang, Min Liu, Quanfeng Xu, Chenzhou Cui, Dongwei Fan, Zhenghong Tang, Jianhai Zhao
Figure caption: Digitized image of QD830883-20001.
Paper: Digitization of Astronomical Photographic Plates from China: Photometric Calibration of Single-exposure Plates and Release of Photometric Catalogs
Authors: Mingyang Ma, Haibo Yuan, Kai Xiao, Bowen Huang, Tao Wang, Yang Huang, Shiyin Shen, Zhengjun Shang, Yong Yu, Liangliang Wang, Meiting Yang, Jing Yang, Min Liu, Quanfeng Xu, Chenzhou Cui, Dongwei Fan, Zhenghong Tang, Jianhai Zhao
Figure caption: Flowchart to estimate the zero-point of each plate.
Paper: Hemispheric Asymmetry of Relative Sunspot Numbers during Solar Cycles 17–25
Authors: Wenhua Wang, Linhua Deng, Zuo Jiang, Jinlei Li, Xinhua Zhao, Tingting Xu, Miao Wan, Jie Cao, Nanbin Xiang, Xuewen Tan, Wei Zhou, Weihong Zhou
Figure caption: The daily sunspot relative number from 1939 March to 2024 October, with daily values represented on the left vertical axis (line plot), and monthly mean values on the right vertical axis (shaded area). Panel (a) illustrates the sunspot numbers over the full solar disk (blue-shaded region). Panel (b) presents the sunspot relative numbers for the northern hemisphere (orange-shaded region), while panel (c) depicts the sunspot relative numbers for the southern hemisphere (purple-shaded region). The data are based on monthly mean sunspot relative numbers provided by the National Astronomical Observatory of Japan (NAOJ/Mitaka).
Paper: Hemispheric Asymmetry of Relative Sunspot Numbers during Solar Cycles 17–25
Authors: Wenhua Wang, Linhua Deng, Zuo Jiang, Jinlei Li, Xinhua Zhao, Tingting Xu, Miao Wan, Jie Cao, Nanbin Xiang, Xuewen Tan, Wei Zhou, Weihong Zhou
Figure caption: Monthly mean sunspot numbers from 1939 to 2024, comparing values from the WDC-SILSO data set (solid lines) and the NAOJ/Mitaka observations (dashed lines). The top panel shows total sunspot numbers over the full solar disk, while the middle and bottom panels display the northern and southern hemispheres, respectively. The two data sets exhibit high consistency across all panels, validating the reliability of the NAOJ/Mitaka series over long timescales.
Paper: Hemispheric Asymmetry of Relative Sunspot Numbers during Solar Cycles 17–25
Authors: Wenhua Wang, Linhua Deng, Zuo Jiang, Jinlei Li, Xinhua Zhao, Tingting Xu, Miao Wan, Jie Cao, Nanbin Xiang, Xuewen Tan, Wei Zhou, Weihong Zhou
Figure caption: Monthly mean sunspot numbers in the northern and southern hemispheres from SC17 to SC25. The orange dashed line represents the monthly sunspot counts in the northern hemisphere, while the solid purple line shows those in the southern hemisphere.
Paper: Hemispheric Asymmetry of Relative Sunspot Numbers during Solar Cycles 17–25
Authors: Wenhua Wang, Linhua Deng, Zuo Jiang, Jinlei Li, Xinhua Zhao, Tingting Xu, Miao Wan, Jie Cao, Nanbin Xiang, Xuewen Tan, Wei Zhou, Weihong Zhou
Figure caption: The cumulative counts of monthly mean sunspot numbers in the northern and southern hemispheres during SC17–SC25. Each panel corresponds to one solar cycle. The orange dashed line represents the cumulative sunspot counts in the northern hemisphere, while the solid purple line indicates those in the southern hemisphere. The difference between the two lines reflects the hemispheric asymmetry in sunspot activity over each cycle.
Paper: A Catalog of Hα Emission-line Stars and 785 Newly Identified Young Stellar Object Candidates from LAMOST Based on a Deep Learning Method
Authors: Lei Tan, 磊 谈, Ying Mei, 盈 梅, Jiale Qian, 家乐 钱, Xiaolong Wang, 小龙 王, Yue Cui, Aixin Huang, 爱新 黄, Feng Wang, 锋 王, Hui Deng, 辉 邓, Chao Liu, 超 刘, Huanbin Chi, 焕斌 迟
Figure caption: The distribution of YSO candidates in the Hertzsprung–Russell diagram. The red points represent the newly identified YSO candidates, the blue points represent the known samples of our YSO candidates, the green points represent the YSO candidates identified by J. Zhang et al. (2023), and the orange points represent the LPVs (identified using the SIMBAD label provided in Table 3). The black curve indicates the unreddened PARSEC isochrone for 100 Myr. The pink line represents the boundary between the LPVs and our YSO candidates. The cyan line indicates the ZAMS, corresponding to a stellar mass range of 0.75–12 M⊙.
Paper: A Catalog of Hα Emission-line Stars and 785 Newly Identified Young Stellar Object Candidates from LAMOST Based on a Deep Learning Method
Authors: Lei Tan, 磊 谈, Ying Mei, 盈 梅, Jiale Qian, 家乐 钱, Xiaolong Wang, 小龙 王, Yue Cui, Aixin Huang, 爱新 黄, Feng Wang, 锋 王, Hui Deng, 辉 邓, Chao Liu, 超 刘, Huanbin Chi, 焕斌 迟
Figure caption: The distribution of YSO candidates in equatorial coordinates. The top panel displays our YSO candidates, with red dots representing newly identified candidates and blue dots indicating previously known YSO candidates within our sample. The bottom panel provides a comparison between our candidates and those reported in previous studies, where the black points mark typical star-forming regions. The coordinates of all star-forming regions (Aquila S, CMa OB1, California, Cepheus Far/Near, Chamaeleon, Corona Australis, Gem OB1, Lupus, Mon OB1, Mon R2, Ophiuchus, Orion A/B/λ, Perseus, Rosette, Serpens/AqR, and Taurus) are adopted from Table 1 of C. Zucker et al. (2019), which provides the average positions and distances of local molecular clouds.
Paper: A Catalog of Hα Emission-line Stars and 785 Newly Identified Young Stellar Object Candidates from LAMOST Based on a Deep Learning Method
Authors: Lei Tan, 磊 谈, Ying Mei, 盈 梅, Jiale Qian, 家乐 钱, Xiaolong Wang, 小龙 王, Yue Cui, Aixin Huang, 爱新 黄, Feng Wang, 锋 王, Hui Deng, 辉 邓, Chao Liu, 超 刘, Huanbin Chi, 焕斌 迟
Figure caption: Examples of samples misclassified by the Hα emission-line identification model.
Paper: A Catalog of Hα Emission-line Stars and 785 Newly Identified Young Stellar Object Candidates from LAMOST Based on a Deep Learning Method
Authors: Lei Tan, 磊 谈, Ying Mei, 盈 梅, Jiale Qian, 家乐 钱, Xiaolong Wang, 小龙 王, Yue Cui, Aixin Huang, 爱新 黄, Feng Wang, 锋 王, Hui Deng, 辉 邓, Chao Liu, 超 刘, Huanbin Chi, 焕斌 迟
Figure caption: Examples of samples misclassified by the Li absorption line identification model.
Paper: Automatic 3D Reconstruction of Coronal Mass Ejections Based on Dual-viewpoint Observations and Machine Learning
Authors: Rongpei Lin, 荣沛 林, Yi Yang, 易 杨, Fang Shen, 芳 沈, Gilbert Pi, Yucong Li, 雨淙 李
Figure caption: Distribution of widths for the nonhalo CME events under investigation. The left and right panels show the widths that are retrieved from the CDAW catalog and the proposed algorithm, together with the average and median width. The bin size is 15°. The dotted line in the plot indicates the average width.
Paper: Automatic 3D Reconstruction of Coronal Mass Ejections Based on Dual-viewpoint Observations and Machine Learning
Authors: Rongpei Lin, 荣沛 林, Yi Yang, 易 杨, Fang Shen, 芳 沈, Gilbert Pi, Yucong Li, 雨淙 李
Figure caption: Distribution of widths that are derived from the proposed algorithm for the halo CME events under investigation, together with the average and median width. The bin size is 15°. The dotted line in the plot indicates the average width.
Paper: Automatic 3D Reconstruction of Coronal Mass Ejections Based on Dual-viewpoint Observations and Machine Learning
Authors: Rongpei Lin, 荣沛 林, Yi Yang, 易 杨, Fang Shen, 芳 沈, Gilbert Pi, Yucong Li, 雨淙 李
Figure caption: The reconstruction of the CME event on 2011 October 1.
Paper: Automatic 3D Reconstruction of Coronal Mass Ejections Based on Dual-viewpoint Observations and Machine Learning
Authors: Rongpei Lin, 荣沛 林, Yi Yang, 易 杨, Fang Shen, 芳 沈, Gilbert Pi, Yucong Li, 雨淙 李
Figure caption: Distribution of velocities for the halo CME events under investigation. The left and right panels show the distribution of velocities from the CDAW catalog and the proposed algorithm, together with the average and median velocities. The bin size is 250 km s−1. The dotted line in the plot indicates the average velocity.
Paper: Automatic 3D Reconstruction of Coronal Mass Ejections Based on Dual-viewpoint Observations and Machine Learning
Authors: Rongpei Lin, 荣沛 林, Yi Yang, 易 杨, Fang Shen, 芳 沈, Gilbert Pi, Yucong Li, 雨淙 李
Figure caption: Distribution of velocities for the nonhalo CME events under investigation. The left and right panels show the velocities retrieved from the CDAW CME catalog and the proposed method, together with the average and median velocities. The bin size is 200 km s−1. The dotted line in the plot indicates the average velocity.
Paper: Automatic 3D Reconstruction of Coronal Mass Ejections Based on Dual-viewpoint Observations and Machine Learning
Authors: Rongpei Lin, 荣沛 林, Yi Yang, 易 杨, Fang Shen, 芳 沈, Gilbert Pi, Yucong Li, 雨淙 李
Figure caption: Scattering plots of velocities and widths from the CDAW catalog (left) and the proposed algorithm (right).
Paper: AllBRICQS: The Discovery of Luminous Quasars in the Northern Hemisphere
Authors: Yunyi Choi, Yuming Fu, Myungshin Im, Xue-Bing Wu, Christopher A. Onken, Christian Wolf, Seo-Won Chang, Hyeonho Choi, Mankeun Jeong, Yongjung Kim, Gu Lim, Yuxuan Pang, Taewan Kim, Jubee Sohn, Dohyeong Kim, Ji Hoon Kim, Eunhee Ko, Gregory S. H. Paek, Sungho Jung
Figure caption: Spectra of the stars, presented in order of increasing R.A. The y-axis shows the scaled flux, aligned with contemporaneous broadband photometry. Pink dotted vertical lines indicate the positions of Balmer absorption lines. Green dotted vertical lines at 6867.2 and 7593.7 Å mark regions affected by telluric absorption, which may impact spectral interpretation.
Paper: AllBRICQS: The Discovery of Luminous Quasars in the Northern Hemisphere
Authors: Yunyi Choi, Yuming Fu, Myungshin Im, Xue-Bing Wu, Christopher A. Onken, Christian Wolf, Seo-Won Chang, Hyeonho Choi, Mankeun Jeong, Yongjung Kim, Gu Lim, Yuxuan Pang, Taewan Kim, Jubee Sohn, Dohyeong Kim, Ji Hoon Kim, Eunhee Ko, Gregory S. H. Paek, Sungho Jung
Figure caption: Spectra of the unclassified sources, presented in order of increasing R.A. The y-axis shows the scaled flux, aligned with contemporaneous broadband photometry. Green dotted vertical lines at 6867.2 and 7593.7 Å mark regions affected by telluric absorption, which may impact spectral interpretation.