adsabs/AstroCLIMB huggingface dataset:
Paper: Cassiopeia A’s Reverse Shock and Its Effects on the Expanding SN Ejecta 
Authors: Robert A. Fesen, Dan Milisavljevic, Daniel Patnaude, Roger A. Chevalier, John C. Raymond, McKinley Brumback, Kathryn E. Weil
Figure caption: P1: a coherent stream of ejecta located in the NE region of Cas A is shown here as it evolves in ground-based images taken between 1951 and 1999. Ejecta in this stream becomes sequentially visible through interaction with Cas A’s slower expanding reverse shock front whose location in 1951 is seen as the stream’s starting point or “base” indicated here by the red dotted line in these images, which is fixed in the sky frame. An arrow in each image points to a discrete ejecta knot in the stream, which is seen to travel steadily outward, i.e., toward the upper left of these frames. The position of the reverse shock, seen here as the start or base of this ejecta feature, also moves outward but far more slowly, measured by the increasing distance of the stream’s base away from its 1951 location (the red dotted line) in the observer’s rest frame. Note: After 1980, the stream’s base begins to shift downward as the ejecta stream loses its dominate radial orientation. North is up, east is to the left in all frames.
Paper: Cassiopeia A’s Reverse Shock and Its Effects on the Expanding SN Ejecta 
Authors: Robert A. Fesen, Dan Milisavljevic, Daniel Patnaude, Roger A. Chevalier, John C. Raymond, McKinley Brumback, Kathryn E. Weil
Figure caption: Top panel: a December 2004 HST image of the Cas A’s northern portion covering the remnant’s two large rings of optically bright ejecta. Bottom panel: a mosaic of 2000 January and 2004 December difference images made comparing the 2004 image (black) with the 2000 image (white). The progression of the reverse shock is seen to be highly fragmented in the central sections, but exhibiting a coherent front seen as long and continuous black filaments along the northeastern and northwestern sections. North is up, east is to the left.
Paper: Cassiopeia A’s Reverse Shock and Its Effects on the Expanding SN Ejecta 
Authors: Robert A. Fesen, Dan Milisavljevic, Daniel Patnaude, Roger A. Chevalier, John C. Raymond, McKinley Brumback, Kathryn E. Weil
Figure caption: Seventy years of evolution of Cas A’s red optical emission between 1951 and 2021. Images between 1951 and 1976 are digitally scanned broadband red Palomar 5 m plates, 1992 and 2021 are CCD MDM 2.4 m images, with the 2004 and 2011 images red and NIR HST images (see Table 2 for details). North is up, east is to the left.
Paper: Cassiopeia A’s Reverse Shock and Its Effects on the Expanding SN Ejecta 
Authors: Robert A. Fesen, Dan Milisavljevic, Daniel Patnaude, Roger A. Chevalier, John C. Raymond, McKinley Brumback, Kathryn E. Weil
Figure caption: Evolution of Cas A’s southern optical emission. Circles shown are 115″ in radius centered on the CoE of Cas A’s radio emission knots and shell (M. C. Anderson & L. Rudnick 1995). Note the southern’s limb spherical morphology that is present in 2021. North is up, east is to the left.
Paper: Cassiopeia A’s Reverse Shock and Its Effects on the Expanding SN Ejecta 
Authors: Robert A. Fesen, Dan Milisavljevic, Daniel Patnaude, Roger A. Chevalier, John C. Raymond, McKinley Brumback, Kathryn E. Weil
Figure caption: Comparison of 2000 and 2019 red HST images of exactly the same 80″ × 50″ northwest region illustrating large changes in Cas A’s optical morphology over a 19 yr period. North is up, east is to the left.
Paper: Cassiopeia A’s Reverse Shock and Its Effects on the Expanding SN Ejecta 
Authors: Robert A. Fesen, Dan Milisavljevic, Daniel Patnaude, Roger A. Chevalier, John C. Raymond, McKinley Brumback, Kathryn E. Weil
Figure caption: 2000 January and 2002 January WFC2 images, and a 2024 March ACS HST WFC2 image of ejecta in Cas A’s north regions showing ejecta brightness changes due to the reverse shock. Images are shown centered on the expanding ejecta. Circles in the top two panels are 4″ in radius and ﹩2\mathop{.}\limits^{^{\prime\prime} }4﹩ in the lower panels.
Paper: Cassiopeia A’s Reverse Shock and Its Effects on the Expanding SN Ejecta 
Authors: Robert A. Fesen, Dan Milisavljevic, Daniel Patnaude, Roger A. Chevalier, John C. Raymond, McKinley Brumback, Kathryn E. Weil
Figure caption: Examples of the appearance of new emission features along Cas A’s eastern limb, reflecting the motion of the reverse shock at Positions P2, P3, and P4. Images as shown are in the rest frame of the ejecta, which are moving to the left (eastward); the slower expanding reverse shock leads to the appearance of new emission to the right. North is up, east is to the left.
Paper: Cassiopeia A’s Reverse Shock and Its Effects on the Expanding SN Ejecta 
Authors: Robert A. Fesen, Dan Milisavljevic, Daniel Patnaude, Roger A. Chevalier, John C. Raymond, McKinley Brumback, Kathryn E. Weil
Figure caption: Combined 2004 March HST ACS F625W and F775W images of Cas A showing locations where reverse shock velocity measurements were made. The black cross marks the remnant’s optical CoE (J. R. Thorstensen et al. 2001).
Paper: Galaxy–Galaxy Strong Lensing with U-Net (GGSL-UNet). I. Extracting Two-dimensional Information from Multiband Images in Ground and Space Observations
Authors: Fucheng Zhong, Ruibiao Luo, Nicola R. Napolitano, Crescenzo Tortora, Rui Li, Xincheng Zhu, Valerio Busillo, L. V. E. Koopmans, Giuseppe Longo
Figure caption: Examples of training/mock images. The first three rows are KiDS mock images, and the last two rows are HST mock images. Each KiDS mock image has a size of 4 × 64 × 64 pixels and a resolution of 0﹩\mathop{.}\limits^{\unicode{x02033}}﹩2 pixel−1. The wavelength bands (i, r, g) are mapped to the colors (R, G, B). Each HST mock image has a size of 1 × 101 × 101 pixels and a resolution of 0﹩\mathop{.}\limits^{\unicode{x02033}}﹩05 pixel−1. The second column shows the mock foreground component, Ff; the third column shows the mock distorted background, Fb; and the final column shows the noise cutout from KiDS, Fn. By tuning the parameters α, β, γ, ϵ during training (for the HST mock image, we only tune its amplitudes because it is a single r-band image), the color changes, but the geometry remains the same. The first column, Fi = Ff + Fb + Fn, will be the input to the network, and the mock signal components Ff, Fb, as well as the survey cutout noise Fn, will be the outputs to be fitted.
Paper: Galaxy–Galaxy Strong Lensing with U-Net (GGSL-UNet). I. Extracting Two-dimensional Information from Multiband Images in Ground and Space Observations
Authors: Fucheng Zhong, Ruibiao Luo, Nicola R. Napolitano, Crescenzo Tortora, Rui Li, Xincheng Zhu, Valerio Busillo, L. V. E. Koopmans, Giuseppe Longo
Figure caption: The mock KiDS images and their reconstructed images using U-Net are shown side by side. Each row represents one object with its different components and the corresponding reconstructed images. The input Fi to U-Net is a four-band 64 × 64 pixel lens image, while the output of U-Net includes the foreground galaxy ﹩{\hat{F}}_{f}﹩, the background image ﹩{\hat{F}}_{b}﹩, and the residual ﹩{\hat{F}}_{n}={F}_{i}-{\hat{F}}_{f}-{\hat{F}}_{b}﹩. The mock foreground galaxy is Ff, and the mock background image is Fb. The second to last column shows the mock subtracted residual Fn = Fi − Ff − Fb.
Paper: Galaxy–Galaxy Strong Lensing with U-Net (GGSL-UNet). I. Extracting Two-dimensional Information from Multiband Images in Ground and Space Observations
Authors: Fucheng Zhong, Ruibiao Luo, Nicola R. Napolitano, Crescenzo Tortora, Rui Li, Xincheng Zhu, Valerio Busillo, L. V. E. Koopmans, Giuseppe Longo
Figure caption:  ﹩({\chi }_{1}^{2},{\chi }_{2}^{2})﹩ plane of mock data (left) and real data (right). The lines ﹩{\chi }_{2}^{2}=1﹩ and the criteria ﹩{\chi }_{1}^{2}-{\chi }_{2}^{2}=thr﹩ are plotted, as shown in Equation (18). Due to the weaker background signal in the real sources, the ﹩{\chi }_{1}^{2}﹩ values in the real data are smaller than those in the mock data. Therefore, we take thr = 1 for the mock data and thr = 0.1 for the real data as a demonstration.
Paper: Galaxy–Galaxy Strong Lensing with U-Net (GGSL-UNet). I. Extracting Two-dimensional Information from Multiband Images in Ground and Space Observations
Authors: Fucheng Zhong, Ruibiao Luo, Nicola R. Napolitano, Crescenzo Tortora, Rui Li, Xincheng Zhu, Valerio Busillo, L. V. E. Koopmans, Giuseppe Longo
Figure caption: The χ2 density distribution of 1000 mock KiDS and HST strong-lensing systems and the corresponding real data reconstructions. The χ2 values are binned with a width of 0.25. The proportion of cases where χ2 < 2, denoted as P(χ < 2), is shown in the legend.
Paper: Galaxy–Galaxy Strong Lensing with U-Net (GGSL-UNet). I. Extracting Two-dimensional Information from Multiband Images in Ground and Space Observations
Authors: Fucheng Zhong, Ruibiao Luo, Nicola R. Napolitano, Crescenzo Tortora, Rui Li, Xincheng Zhu, Valerio Busillo, L. V. E. Koopmans, Giuseppe Longo
Figure caption: The real KiDS/HST images and their reconstructed images using U-Net. Each row represents one object with its different components’ reconstructed images. The input Fi to U-Net is a four-band 64 × 64 pixel KiDS lens candidate image or an r-band 101 × 101 pixel HST lens image, while the output of U-Net includes the foreground galaxy ﹩{\hat{F}}_{f}﹩, the background image ﹩{\hat{F}}_{b}﹩, and the residual ﹩{\hat{F}}_{n}={F}_{i}-{\hat{F}}_{f}-{\hat{F}}_{b}﹩.
Paper: Galaxy–Galaxy Strong Lensing with U-Net (GGSL-UNet). I. Extracting Two-dimensional Information from Multiband Images in Ground and Space Observations
Authors: Fucheng Zhong, Ruibiao Luo, Nicola R. Napolitano, Crescenzo Tortora, Rui Li, Xincheng Zhu, Valerio Busillo, L. V. E. Koopmans, Giuseppe Longo
Figure caption: Masks generated by U-Net and the final output of different components, with a real KiDS lens image serving as the input. U-Net outputs three masks corresponding to three different components: a mask for the foreground, a mask for the background source, and a mask for noise. Masks can be considered as the probability of different components in each pixel. The notation ⨂ represents multiplication. The bottom three images show the final output of the three different components of the lens, which are the product of the input image and the respective mask.
Paper: Galaxy–Galaxy Strong Lensing with U-Net (GGSL-UNet). I. Extracting Two-dimensional Information from Multiband Images in Ground and Space Observations
Authors: Fucheng Zhong, Ruibiao Luo, Nicola R. Napolitano, Crescenzo Tortora, Rui Li, Xincheng Zhu, Valerio Busillo, L. V. E. Koopmans, Giuseppe Longo
Figure caption: The distribution of χ2 for the 17 HST r-band images is presented. The symbol ﹩{\hat{\chi }}^{2}﹩ represents the chi-square calculated using the BELLS GALLERY model, while χ2 represents the chi-square calculated using the U-Net output.
Paper: Galaxy–Galaxy Strong Lensing with U-Net (GGSL-UNet). I. Extracting Two-dimensional Information from Multiband Images in Ground and Space Observations
Authors: Fucheng Zhong, Ruibiao Luo, Nicola R. Napolitano, Crescenzo Tortora, Rui Li, Xincheng Zhu, Valerio Busillo, L. V. E. Koopmans, Giuseppe Longo
Figure caption: The loss of 50 training epochs. As the epochs increased, the loss of the validation samples fluctuated around a constant value. The checkpoints with minimal validation loss will be used as our model. The training and validation data are both mock augmented data (90% and 10% of the total). Due to the significant overfitting prevention by online augmentation, the training and validation losses appear close and overlap.
Paper: Galaxy–Galaxy Strong Lensing with U-Net (GGSL-UNet). I. Extracting Two-dimensional Information from Multiband Images in Ground and Space Observations
Authors: Fucheng Zhong, Ruibiao Luo, Nicola R. Napolitano, Crescenzo Tortora, Rui Li, Xincheng Zhu, Valerio Busillo, L. V. E. Koopmans, Giuseppe Longo
Figure caption: The real KiDS images and their reconstructed images using U-Net for unlensed cases are shown. These targets are randomly selected normal galaxies from the KiDS catalog. There are no signals in ﹩{\hat{F}}_{b}﹩. Labels are identical to those of Figure 6.
Paper: The Stellar Abundances and Galactic Evolution Survey (SAGES). II. Machine Learning–based Stellar Parameters for 21 Million Stars from the First Data Release
Authors: Hongrui Gu, Zhou Fan, Gang Zhao, Huang Yang, Timothy C. Beers, Wei Wang, Jie Zheng, Jingkun Zhao, Chun Li, Yuqin Chen, Haibo Yuan, Haining Li, Kefeng Tan, Yihan Song, Ali Luo, Nan Song, Yujuan Liu
Figure caption: A comparison of the performance of the H23 catalog and our catalog for four models with two parameters. The lower half of each panel shows the distribution of the differences between our model and the H23 model, based on the parameters provided by the H23 model, along with a histogram of the distribution of the differences. The mean and standard deviation were obtained through Gaussian fitting of the histogram, and the fitted values are displayed in the legend of each panel. The red-dashed line in the upper panels is the one-to-one line, and is the zero-residual line in the lower panels.
Paper: The Stellar Abundances and Galactic Evolution Survey (SAGES). II. Machine Learning–based Stellar Parameters for 21 Million Stars from the First Data Release
Authors: Hongrui Gu, Zhou Fan, Gang Zhao, Huang Yang, Timothy C. Beers, Wei Wang, Jie Zheng, Jingkun Zhao, Chun Li, Yuqin Chen, Haibo Yuan, Haining Li, Kefeng Tan, Yihan Song, Ali Luo, Nan Song, Yujuan Liu
Figure caption: Systematic errors and standard deviations for three stellar parameters ([Fe/H], Teff, log g), as a function of their values. Different colors represent different test sets and the different shapes of the points represent different types of stars (triangles for dwarfs, squares for giants, circles for giants and dwarfs).
Paper: The Stellar Abundances and Galactic Evolution Survey (SAGES). II. Machine Learning–based Stellar Parameters for 21 Million Stars from the First Data Release
Authors: Hongrui Gu, Zhou Fan, Gang Zhao, Huang Yang, Timothy C. Beers, Wei Wang, Jie Zheng, Jingkun Zhao, Chun Li, Yuqin Chen, Haibo Yuan, Haining Li, Kefeng Tan, Yihan Song, Ali Luo, Nan Song, Yujuan Liu
Figure caption: This figure presents the metallicity histograms from this work. The top two panels show the open clusters NGC 2420 and NGC 2682, and the bottom two panels display the globular clusters NGC 6934 and NGC 7089. The red-dashed lines represent the best-fit Gaussian distributions to the histograms, with the mean and standard deviation displayed in the panels. The black dashed lines indicate the cluster metallicities from literature, with their values shown in legends.
Paper: The Stellar Abundances and Galactic Evolution Survey (SAGES). II. Machine Learning–based Stellar Parameters for 21 Million Stars from the First Data Release
Authors: Hongrui Gu, Zhou Fan, Gang Zhao, Huang Yang, Timothy C. Beers, Wei Wang, Jie Zheng, Jingkun Zhao, Chun Li, Yuqin Chen, Haibo Yuan, Haining Li, Kefeng Tan, Yihan Song, Ali Luo, Nan Song, Yujuan Liu
Figure caption: Left panel: The photometric-metallicity distributions of dwarf (blue) and giant (yellow) stars in Data Set 1. The number of dwarf and giant stars in each bin of metallicity are also given. Right panel: similar to the left panel, but using data from Data Set 2.
Paper: The Stellar Abundances and Galactic Evolution Survey (SAGES). II. Machine Learning–based Stellar Parameters for 21 Million Stars from the First Data Release
Authors: Hongrui Gu, Zhou Fan, Gang Zhao, Huang Yang, Timothy C. Beers, Wei Wang, Jie Zheng, Jingkun Zhao, Chun Li, Yuqin Chen, Haibo Yuan, Haining Li, Kefeng Tan, Yihan Song, Ali Luo, Nan Song, Yujuan Liu
Figure caption: Similar to Figure 9, but for a comparison with the A23 catalog.
Paper: Spectuner: A Framework for Automated Line Identification of Interstellar Molecules
Authors: Yisheng Qiu, Tianwei Zhang, Thomas Möller, Xue-Jian Jiang, Zihao Song, Huaxi Chen, Donghui Quan
Figure caption: Schematics of some definitions in our peak-finding algorithm as introduced in Section 2.4. In the upper panel, black dashed lines represent examples of prominence. Colored lines depict the peak widths estimated by the peak_widths function in SCIPY using various input parameters R, defined in Equation (7). The lower panel illustrates the interval intersection algorithm, assuming that the blue dashed line is an observed spectrum and the green dashed line is a model spectrum. The definitions of dobs, dpred, d∩, and dFP can also be found in the lower panel.
Paper: Spectuner: A Framework for Automated Line Identification of Interstellar Molecules
Authors: Yisheng Qiu, Tianwei Zhang, Thomas Möller, Xue-Jian Jiang, Zihao Song, Huaxi Chen, Donghui Quan
Figure caption: Comparison of the best-fitting spectra using different loss functions. The black solid line illustrates the observed spectrum of SgrB2M-IRAM (see Section 3.4), and blue dashed lines represent the spectral lines of C2H3CN identified by A. Belloche et al. (2013). The blue and red lines demonstrate the best-fitting results achieved with the χ2 and peak-matching loss functions, respectively. The peak-matching loss function is defined in Section 2.4. We compute and display both the χ2 and peak-matching loss values corresponding to each best-fitting spectrum. These values imply that using the χ2 loss is inappropriate for spectral fitting of a single molecule.
Paper: Spectuner: A Framework for Automated Line Identification of Interstellar Molecules
Authors: Yisheng Qiu, Tianwei Zhang, Thomas Möller, Xue-Jian Jiang, Zihao Song, Huaxi Chen, Donghui Quan
Figure caption: Visualization of ﹩{S}_{\,\rm{TP}\,}^{i}﹩ and ﹩{S}_{\,\rm{FP}\,}^{i}﹩ defined in Equations (21)–(25). The black solid lines illustrate the observed spectrum of W51-Mopra (see Section 3.1). The red lines show the best-fitting spectra of 13CH3OH and C2H5CN obtained with the peak-matching loss in the combined phase. The complete identification results for W51-Mopra are presented in Section 4. Each black (blue) vertical line represents a true (false) positive peak identified using our peak-finding algorithm as described in Section 2.4.
Paper: Spectuner: A Framework for Automated Line Identification of Interstellar Molecules
Authors: Yisheng Qiu, Tianwei Zhang, Thomas Möller, Xue-Jian Jiang, Zihao Song, Huaxi Chen, Donghui Quan
Figure caption: Best-fitting results for W51-Mopra. Black lines represent the observed spectrum. Left and right panels show the results using the peak-matching and χ2 loss functions, respectively. The peak-matching loss function is described in Section 2.4.
Paper: Spectuner: A Framework for Automated Line Identification of Interstellar Molecules
Authors: Yisheng Qiu, Tianwei Zhang, Thomas Möller, Xue-Jian Jiang, Zihao Song, Huaxi Chen, Donghui Quan
Figure caption: Recall and precision of species identified in W51-Mopra. The red and blue bars represent the results using the peak-matching and χ2 loss functions, respectively. Definitions of recall and precision are provided in Section 4.1.
Paper: Spectuner: A Framework for Automated Line Identification of Interstellar Molecules
Authors: Yisheng Qiu, Tianwei Zhang, Thomas Möller, Xue-Jian Jiang, Zihao Song, Huaxi Chen, Donghui Quan
Figure caption: Flowchart of the proposed automated line identification framework. An overview of the algorithm is given in Section 2.1.
Paper: The FAST H I 21 cm Absorption Blind Survey. II. Statistical Exploration for Associated and Intervening Systems
Authors: Wenkai Hu, Yougang Wang, Yichao Li, Wenxiu Yang, Yidong Xu, Fengquan Wu, Ue-Li Pen, Jie Wang, Yingjie Jing, Chen Xu, Qingze Chen, Zheng Zheng, Di Li, Ming Zhu, Xin Zhang, Xuelei Chen
Figure caption: Left panel: same as in Figure 2, except for 4C +31.04. The black dotted–dashed vertical line marks the redshift as given in the NED. Middle-left panel: radio map from VLASS centered at 4C +31.04. Middle-right panel: W3 band infrared map of WISEA J011935.00+321050.2 from WISE. Right panel: optical map of 4C +31.04 from SDSS.
Paper: The FAST H I 21 cm Absorption Blind Survey. II. Statistical Exploration for Associated and Intervening Systems
Authors: Wenkai Hu, Yougang Wang, Yichao Li, Wenxiu Yang, Yidong Xu, Fengquan Wu, Ue-Li Pen, Jie Wang, Yingjie Jing, Chen Xu, Qingze Chen, Zheng Zheng, Di Li, Ming Zhu, Xin Zhang, Xuelei Chen
Figure caption: Left panel: H I absorption feature of 4C +56.02. The blue solid line shows the absorption spectrum, and the red solid line shows the fit with a six-component Gaussian model. The fitting residual is shown as a black solid line at the bottom. The optical depth value for H I absorption is shown on the right scale. Middle panel: the radio map from VLASS centered at 4C +56.02. Right panel: the W3 band infrared map centered at 4C +56.02.
Paper: The FAST H I 21 cm Absorption Blind Survey. II. Statistical Exploration for Associated and Intervening Systems
Authors: Wenkai Hu, Yougang Wang, Yichao Li, Wenxiu Yang, Yidong Xu, Fengquan Wu, Ue-Li Pen, Jie Wang, Yingjie Jing, Chen Xu, Qingze Chen, Zheng Zheng, Di Li, Ming Zhu, Xin Zhang, Xuelei Chen
Figure caption: Left panel: the same as Figure 3, but for NVSS J112832+583346. Middle-left panel: radio map from VLASS centered at NVSS J112832+583346. Middle-right panel: W2 band infrared map of WISEA J112833.59+583346.5 (WISE counterpart to NVSS J112832+583346 ) from WISE. Right panel: SDSS optical map of the optical counterpart of WISEA J112833.59+583346.5.
Paper: The FAST H I 21 cm Absorption Blind Survey. II. Statistical Exploration for Associated and Intervening Systems
Authors: Wenkai Hu, Yougang Wang, Yichao Li, Wenxiu Yang, Yidong Xu, Fengquan Wu, Ue-Li Pen, Jie Wang, Yingjie Jing, Chen Xu, Qingze Chen, Zheng Zheng, Di Li, Ming Zhu, Xin Zhang, Xuelei Chen
Figure caption: Left and middle-left panels: the same as Figure 2, but for 3C 84 HVS and 3C 84, respectively. Middle panel: the radio map from VLASS centered at 3C 84. Middle-right panel: W2 band infrared map of WISEA J031948.16 +413042.3 from WISE. Right panel: SDSS optical map of the optical counterpart of WISEA J031948.16+413042.3.
Paper: The FAST H I 21 cm Absorption Blind Survey. II. Statistical Exploration for Associated and Intervening Systems
Authors: Wenkai Hu, Yougang Wang, Yichao Li, Wenxiu Yang, Yidong Xu, Fengquan Wu, Ue-Li Pen, Jie Wang, Yingjie Jing, Chen Xu, Qingze Chen, Zheng Zheng, Di Li, Ming Zhu, Xin Zhang, Xuelei Chen
Figure caption: Left panel: the same as Figure 2, but for NVSS J085521+575143. Middle-left panel: radio map from VLASS centered at NVSS J085521+575143. Middle-right panel: W1 band infrared map of WISEA J085519.02+575140.7 (shown as a purple cross) and WISEA J085519.81+575141.1 (WISE counterpart to background NVSS J085521 +575143, shown as an orange cross) from WISE. Right panel: SDSS optical map of the optical counterpart of WISEA J085519.02+575140.7.
Paper: The FAST H I 21 cm Absorption Blind Survey. II. Statistical Exploration for Associated and Intervening Systems
Authors: Wenkai Hu, Yougang Wang, Yichao Li, Wenxiu Yang, Yidong Xu, Fengquan Wu, Ue-Li Pen, Jie Wang, Yingjie Jing, Chen Xu, Qingze Chen, Zheng Zheng, Di Li, Ming Zhu, Xin Zhang, Xuelei Chen
Figure caption: Left panel: the same as Figure 3, but for 4C +57.23. Middle-left panel: radio map from VLASS centered at 4C +57.23. Middle-right panel: W1 band infrared map of WISEA J135400.67+565000.5 (shown as a purple cross) and 4C +57.23 (shown as an orange cross). Right panel: SDSS optical map centered at the optical counterpart of 4C +57.23, the bright galaxy below is the optical counterpart of WISEA J135400.67+565000.5.
Paper: The FAST H I 21 cm Absorption Blind Survey. II. Statistical Exploration for Associated and Intervening Systems
Authors: Wenkai Hu, Yougang Wang, Yichao Li, Wenxiu Yang, Yidong Xu, Fengquan Wu, Ue-Li Pen, Jie Wang, Yingjie Jing, Chen Xu, Qingze Chen, Zheng Zheng, Di Li, Ming Zhu, Xin Zhang, Xuelei Chen
Figure caption: Left panel: the same as Figure 2, but for 4C −06.18. Middle panel: the radio map from VLASS centered at 4C −06.18. Right panel: the W3 band infrared map from WISE centered at 4C −06.18.