adsabs/AstroCLIMB huggingface dataset:
Paper: Investigations of MWISP Filaments. I. Filament Identification and Analysis Algorithms, and Source Catalog
Authors: Yu Jiang, Xuepeng Chen, Sheng Zheng, Zhibo Jiang, Zhiwei Chen, Yao Huang, Yang Su, Li Sun, Jian-Cheng Feng, Haoran Feng, Ji Yang
Figure caption: The histogram statistics of Galactic distribution. Panels (a)–(c) display the distribution of filament positions, including Galactic longitude, Galactic latitude, and velocity. Dark blue denotes filaments identified by DPConCFil, while royal blue indicates those with a greater number of clumps. Lime green represents structures isolated by MST, and dark green highlights filaments with greater linearity. The dashed lines represent the median, and the mean and peak of the distribution for DPConCFil are also calculated.
Paper: Investigations of MWISP Filaments. I. Filament Identification and Analysis Algorithms, and Source Catalog
Authors: Yu Jiang, Xuepeng Chen, Sheng Zheng, Zhibo Jiang, Zhiwei Chen, Yao Huang, Yang Su, Li Sun, Jian-Cheng Feng, Haoran Feng, Ji Yang
Figure caption: Substructures of the filament. The numbered green and red circles connected by green lines represent the positions of clumps within the first subfilament, while the green contour represents the boundary of this substructure. Similarly, the numbered blue and red circles connected by blue lines represent the positions of clumps within the second subfilament, while the blue contour represents the boundary of this substructure. The red clump corresponds to a shared node between the two subfilaments, with its boundary outlined by the red contour.
Paper: Investigations of MWISP Filaments. I. Filament Identification and Analysis Algorithms, and Source Catalog
Authors: Yu Jiang, Xuepeng Chen, Sheng Zheng, Zhibo Jiang, Zhiwei Chen, Yao Huang, Yang Su, Li Sun, Jian-Cheng Feng, Haoran Feng, Ji Yang
Figure caption: (a) The fitted intensity skeleton and profiles of the first subfilament. The green contour outlines the region of this subfilament. (b) The fitted intensity skeleton and profiles of the second subfilament. The blue contour outlines the region of this subfilament. (c) The overall fitted intensity skeletons and profiles.
Paper: Investigations of MWISP Filaments. I. Filament Identification and Analysis Algorithms, and Source Catalog
Authors: Yu Jiang, Xuepeng Chen, Sheng Zheng, Zhibo Jiang, Zhiwei Chen, Yao Huang, Yang Su, Li Sun, Jian-Cheng Feng, Haoran Feng, Ji Yang
Figure caption: The angular length of filament, as certified by DPConCFil, in relation to the velocity separation between filaments and their nearest spiral arm. Points of different colors represent varying density estimates from the kernel density estimation, with the red line indicating the fitted relationship.
Paper: Investigations of MWISP Filaments. I. Filament Identification and Analysis Algorithms, and Source Catalog
Authors: Yu Jiang, Xuepeng Chen, Sheng Zheng, Zhibo Jiang, Zhiwei Chen, Yao Huang, Yang Su, Li Sun, Jian-Cheng Feng, Haoran Feng, Ji Yang
Figure caption: Giant structures isolated by DPConCFil and MST from the application data. DPConCFil-B, DPConCFil-C, and MST-B refer to the same filaments marked in Figure 10. The number of clumps within the filaments are 240, 255, and 2525, respectively. In DPConCFil-B and DPConCFil-C, lime curves represent the longest fitted intensity skeletons, while red asterisks and line segments denote the positions and orientations of the clumps. In MST-B, orange asterisk denotes the intensity-weighted central position of the structure, and green and blue contours correspond to the boundaries of filaments in DPConCFil-B and DPConCFil-C, respectively. In DPConCFil-B and MST-B, cyan rectangles outline the same areas and provide a zoomed-in view, with yellow contours marking the boundaries of the clumps missing in MST-B within the rectangle.
Paper: Investigations of MWISP Filaments. I. Filament Identification and Analysis Algorithms, and Source Catalog
Authors: Yu Jiang, Xuepeng Chen, Sheng Zheng, Zhibo Jiang, Zhiwei Chen, Yao Huang, Yang Su, Li Sun, Jian-Cheng Feng, Haoran Feng, Ji Yang
Figure caption: The area of the largest molecular cloud and filaments identified by DPConCFil in the application data. The map is the 13CO emission of MWISP within 10° ≤ l ≤ 20°, −1﹩\mathop{.}\limits^{\circ }﹩6 ≤ b ≤ 1﹩\mathop{.}\limits^{\circ }﹩8, and −25 km s−1 ≤v ≤ 90 km s−1, and is preprocessed employing the signal region extraction method (Y. Jiang et al. 2023). GMF A is the largest giant filament. GMFs B and C are illustrated in Figure 21, while Filament D is a common filament present in both the example and application data, as previously shown in Figure 4. The central positions of these filaments are denoted by asterisks of different colors, and the boundaries are delineated by contours of different colors.
Paper: Investigations of MWISP Filaments. I. Filament Identification and Analysis Algorithms, and Source Catalog
Authors: Yu Jiang, Xuepeng Chen, Sheng Zheng, Zhibo Jiang, Zhiwei Chen, Yao Huang, Yang Su, Li Sun, Jian-Cheng Feng, Haoran Feng, Ji Yang
Figure caption: Velocity-integrated intensity images of filaments in Figure 9. The thicker red curves represent the fitted intensity skeletons, while the thinner red straight lines represent the profiles. The blue scatter points denote the peak intensity pixels on the profiles. The numbered circles of different colors indicate the positions of different filaments, and are consistent with the labels in Figure 9. Filaments 2, 3, 6, 8, and 9 are small scale.
Paper: Investigations of MWISP Filaments. I. Filament Identification and Analysis Algorithms, and Source Catalog
Authors: Yu Jiang, Xuepeng Chen, Sheng Zheng, Zhibo Jiang, Zhiwei Chen, Yao Huang, Yang Su, Li Sun, Jian-Cheng Feng, Haoran Feng, Ji Yang
Figure caption: The structures isolated by the MST algorithm. In the left panel, lines of various colors interconnect distinct coherent structures, while circles denote the spatial positions of clumps within these structures. The background is the velocity-integrated intensity map of all clumps. Panels (A), (B), and (C) respectively depict three coherent structures alongside their respective linearities. In panel (A), the linearity of the filament outlined in yellow is also computed.
Paper: Investigations of MWISP Filaments. I. Filament Identification and Analysis Algorithms, and Source Catalog
Authors: Yu Jiang, Xuepeng Chen, Sheng Zheng, Zhibo Jiang, Zhiwei Chen, Yao Huang, Yang Su, Li Sun, Jian-Cheng Feng, Haoran Feng, Ji Yang
Figure caption: The histogram statistics of properties. Panels (a)–(c) display the number of clumps within the filament, the angle, and the angular area for DPConCFil and MST. Panels (d)–(f) show the velocity gradient, SIOU, and angular FWHM from Gaussian fitting for DPConCFil.
Paper: Investigations of MWISP Filaments. I. Filament Identification and Analysis Algorithms, and Source Catalog
Authors: Yu Jiang, Xuepeng Chen, Sheng Zheng, Zhibo Jiang, Zhiwei Chen, Yao Huang, Yang Su, Li Sun, Jian-Cheng Feng, Haoran Feng, Ji Yang
Figure caption: The structures isolated by the FilFinder algorithm. The left panel shows the skeletons extracted from the mask obtained by FilFinder on the velocity-integrated map, with a global threshold of 0.8 K km s−1. The right panel shows the skeletons extracted from the mask of the integrated clumps. Different colors denote different skeletons, with circles indicating the longest skeleton and plus signs denoting branches. The minimum length threshold for both the skeletons and branches is set to 10 pixels.
Paper: Investigations of MWISP Filaments. I. Filament Identification and Analysis Algorithms, and Source Catalog
Authors: Yu Jiang, Xuepeng Chen, Sheng Zheng, Zhibo Jiang, Zhiwei Chen, Yao Huang, Yang Su, Li Sun, Jian-Cheng Feng, Haoran Feng, Ji Yang
Figure caption: Filaments identified by DPConCFil from the simulated molecular clouds. The background shows the integrated intensity of all clumps detected by FacetClumps. The red, blue, and green asterisks and line segments denote the position and direction of clumps within the filaments, clumps outside the filaments that are connected to them, and clumps outside the filaments that are not connected, respectively. The zoomed-in views showcase the two largest filaments, with the lime curve in the upper right corner representing the longest intensity skeletons, and the various red curves in the lower left corner representing the intensity skeletons of different substructures.
Paper: Investigations of MWISP Filaments. I. Filament Identification and Analysis Algorithms, and Source Catalog
Authors: Yu Jiang, Xuepeng Chen, Sheng Zheng, Zhibo Jiang, Zhiwei Chen, Yao Huang, Yang Su, Li Sun, Jian-Cheng Feng, Haoran Feng, Ji Yang
Figure caption: The structures isolated by the DisPerSE algorithm. Left panel: velocity-integrated intensity map. Curves in different colors denote different skeletons, each labeled with a corresponding number in the same color. Middle panel: latitude-integrated intensity map. Right panel: longitude-integrated intensity map. The minimum length threshold for skeletons is set to 10 pixels.
Paper: Investigations of MWISP Filaments. I. Filament Identification and Analysis Algorithms, and Source Catalog
Authors: Yu Jiang, Xuepeng Chen, Sheng Zheng, Zhibo Jiang, Zhiwei Chen, Yao Huang, Yang Su, Li Sun, Jian-Cheng Feng, Haoran Feng, Ji Yang
Figure caption: The clumps detected by FacetClumps in the velocity-integrated map. The intensity threshold is 1.6 K km s−1. The asterisks denote the positions of the clumps, the lines denote the direction of the principal axis of the clumps that have not touched the edge. Clumps 1, 2, and 3 are examples to illustrate the large shifts in direction and position.
Paper: Investigations of MWISP Filaments. I. Filament Identification and Analysis Algorithms, and Source Catalog
Authors: Yu Jiang, Xuepeng Chen, Sheng Zheng, Zhibo Jiang, Zhiwei Chen, Yao Huang, Yang Su, Li Sun, Jian-Cheng Feng, Haoran Feng, Ji Yang
Figure caption: The structures isolated by various algorithms in the simulated molecular clouds. Different colors indicate distinct structures. DPConCFil: the background shows the integrated intensity of all clumps, and the curves denote the longest skeletons of filaments. FilFinder: the curves denote the skeletons extracted from the mask generated by FilFinder on the velocity-integrated map, similar to the left panel of Figure 17. DisPerSE: the curves denote the longest skeletons of filaments, with the zoomed-in view showcasing the skeletons within a subregion. MST: the curves indicate the connections among clumps within the structures, which have not been filtered according to linearity checks, similar to the first panel of Figure 19.
Paper: Semiclassical Estimates of Pressure-induced Line Widths for Infrared Absorption in Hot (Exo)planetary Atmospheres
Authors: Jeanna Buldyreva, Kathleen Stehlin, Sergei N. Yurchenko, Elizabeth R. Guest, Jonathan Tennyson
Figure caption: Comparison of air-broadening coefficients γref obtained by the ML approach with HITRAN values (I. E. Gordon et al. 2022) and semiclassical (SC) estimates ﹩\widetilde{\gamma }﹩ of the present work, shown for CO (upper panel) and CH4 (lower panel).
Paper: Semiclassical Estimates of Pressure-induced Line Widths for Infrared Absorption in Hot (Exo)planetary Atmospheres
Authors: Jeanna Buldyreva, Kathleen Stehlin, Sergei N. Yurchenko, Elizabeth R. Guest, Jonathan Tennyson
Figure caption: Line-broadening coefficients γref obtained by the ML approach (E. R. Guest et al. 2024) and the semiclassical (SC) estimates ﹩\widetilde{\gamma }﹩ of the present work for MgF and SiO broadened by air.
Paper: Semiclassical Estimates of Pressure-induced Line Widths for Infrared Absorption in Hot (Exo)planetary Atmospheres
Authors: Jeanna Buldyreva, Kathleen Stehlin, Sergei N. Yurchenko, Elizabeth R. Guest, Jonathan Tennyson
Figure caption: The spread of the line-broadening coefficients ﹩\tilde{\gamma }﹩ (cm−1 atm−1) for the “exotic” molecules included in ExoMol and collision partners considered in this work. The sizes of the circles and the color heatmap represent the magnitude of ﹩\tilde{\gamma }﹩: the sizes are proportional to its value, while the heatmap is specified in the figure.
Paper: Semiclassical Estimates of Pressure-induced Line Widths for Infrared Absorption in Hot (Exo)planetary Atmospheres
Authors: Jeanna Buldyreva, Kathleen Stehlin, Sergei N. Yurchenko, Elizabeth R. Guest, Jonathan Tennyson
Figure caption: Left display: temperature dependence of the SiO line broadening for some perturbers considered in the present work. Right display: absorption spectrum of SiO computed for T = 3000 K and P = 1 atm.
Paper: UPdec-Webb: A Data Set for Coaddition of JWST NIRCam Images
Authors: Lei Wang, Huanyuan Shan, Lin Nie, Cheng Cheng, Fang-Ting Yuan, Qifan Cui, Guoliang Li, Yushan Xie, Dezi Liu, Yao Liu, Min Fang, Nan Li, Peng Jia, Ran Li, Fengshan Liu, Yiping Shu, Chang Jiang, Cheng-Liang Wei, Han Qu, Wen-Wen Zheng, Li-Yan Zhu, Xi Kang
Figure caption: A corner of the SMACSJ0723 in RGB image. We mapped gray-scale images to monochromatic colors. Four color channels are used here (red: F444W; orange: F356W; green: F277W+F200W; blue: F150W+F090W). The RGB flux is combined by the following: blue = F150W + F090W; green = F200W + F277W + (165/255) × F356W; red = F356W + F444W. The left panel is a Drizzle combined image corresponding to the official NASA press release image. The UPDC's result is shown on the right panel with 10 iterations.
Paper: UPdec-Webb: A Data Set for Coaddition of JWST NIRCam Images
Authors: Lei Wang, Huanyuan Shan, Lin Nie, Cheng Cheng, Fang-Ting Yuan, Qifan Cui, Guoliang Li, Yushan Xie, Dezi Liu, Yao Liu, Min Fang, Nan Li, Peng Jia, Ran Li, Fengshan Liu, Yiping Shu, Chang Jiang, Cheng-Liang Wei, Han Qu, Wen-Wen Zheng, Li-Yan Zhu, Xi Kang
Figure caption: A flowchart shows how the UPDC works. The diagram above has two sections, yellow and blue, representing the telescope imaging process and mock imaging process, respectively. The dashed green line indicates that this step is only passed through once during initialization. The initial image f(0) (UPDC-iter0) is provided by the JWST pipeline with unshrunk pixels pixfrac = 1 and double sampling rate (PSR = 0.5). We convolve the f(0) by the HybPSF and downsample (or blot) the convolved image to mock exposures with the same sampling/dithers as the real exposures (input images). These mocked exposures are then compared one by one with the real exposures. If the comparison results meet the preset threshold, we output the results. If not, we repeat the mock imaging process and use the output to tune the input for the next round of iteration.
Paper: UPdec-Webb: A Data Set for Coaddition of JWST NIRCam Images
Authors: Lei Wang, Huanyuan Shan, Lin Nie, Cheng Cheng, Fang-Ting Yuan, Qifan Cui, Guoliang Li, Yushan Xie, Dezi Liu, Yao Liu, Min Fang, Nan Li, Peng Jia, Ran Li, Fengshan Liu, Yiping Shu, Chang Jiang, Cheng-Liang Wei, Han Qu, Wen-Wen Zheng, Li-Yan Zhu, Xi Kang
Figure caption: Coaddition comparison between the Starck–Pantin and the UPDC in the F200W band. All images except for the left column have been subjected to a nonstrict positivity constraint Equation (2). It is evident that both methods effectively suppress the diffraction spikes surrounding bright sources; however, the Starck–Pantin method results in increased noise levels. Tag-A, -B, and -C illustrate that the Starck–Pantin algorithm induces more pronounced ringing artifacts compared to UPDC, significantly impacting the surface brightness distribution of galaxies, as highlighted by Tag-A. In the case of point-source reconstruction, depicted in Tag-B and -C, the Starck–Pantin approach disrupts the PSF's original structure, substituting it with ringing and noise enhancements. Conversely, the UPDC algorithm preserves the PSF's self-similarity throughout equivalent iterations. As indicated by the yellow arrow, the self-similar PSF allows us to more easily distinguish between the PSF and faint sources blended with it.
Paper: UPdec-Webb: A Data Set for Coaddition of JWST NIRCam Images
Authors: Lei Wang, Huanyuan Shan, Lin Nie, Cheng Cheng, Fang-Ting Yuan, Qifan Cui, Guoliang Li, Yushan Xie, Dezi Liu, Yao Liu, Min Fang, Nan Li, Peng Jia, Ran Li, Fengshan Liu, Yiping Shu, Chang Jiang, Cheng-Liang Wei, Han Qu, Wen-Wen Zheng, Li-Yan Zhu, Xi Kang
Figure caption: JWST sampling for the six bands. The Nyquist sampling has an FWHM of 2 CCD pixels, namely a radius of 1 CCD pixel. Below this value is undersampling. The solid lines come from the HybPSF, the dashed from a drizzled star at R.A. = 110﹩\mathop{.}\limits^{\circ }﹩865243, decl. = −73﹩\mathop{.}\limits^{\circ }﹩454731. The left panel represents the SW band (0﹩\mathop{.}\limits^{{\rm{^{\prime} }}{\rm{^{\prime} }}}﹩031 pixel−1), while the right one for the LW (0﹩\mathop{.}\limits^{{\rm{^{\prime} }}{\rm{^{\prime} }}}﹩063 pixel−1). All images are sampled doubly compared to their detectors.
Paper: UPdec-Webb: A Data Set for Coaddition of JWST NIRCam Images
Authors: Lei Wang, Huanyuan Shan, Lin Nie, Cheng Cheng, Fang-Ting Yuan, Qifan Cui, Guoliang Li, Yushan Xie, Dezi Liu, Yao Liu, Min Fang, Nan Li, Peng Jia, Ran Li, Fengshan Liu, Yiping Shu, Chang Jiang, Cheng-Liang Wei, Han Qu, Wen-Wen Zheng, Li-Yan Zhu, Xi Kang
Figure caption: A zoom-in RGB image for some details in the SMACSJ0723 field. The JWST diffraction spikes on the elliptical and face-on spiral indicated by Tag-A have been significantly reduced by UPDC; the two sets of binary star systems marked by Tag-B have been clearly distinguished; the background galaxy distorted by strong gravitational lensing, as indicated by Tag-C, has become clearer; as shown by Tag-D, since the UPDC algorithm is based on a forward modeling Bayesian estimation, the spikes of the central saturated and truncated flux stars cannot be effectively suppressed by PSF deconvolution; finally, the distinguishable point sources marked by the yellow arrow in the right panel are obscured by bright spikes in the left.
Paper: UPdec-Webb: A Data Set for Coaddition of JWST NIRCam Images
Authors: Lei Wang, Huanyuan Shan, Lin Nie, Cheng Cheng, Fang-Ting Yuan, Qifan Cui, Guoliang Li, Yushan Xie, Dezi Liu, Yao Liu, Min Fang, Nan Li, Peng Jia, Ran Li, Fengshan Liu, Yiping Shu, Chang Jiang, Cheng-Liang Wei, Han Qu, Wen-Wen Zheng, Li-Yan Zhu, Xi Kang
Figure caption: Comparison of the UPDC-iter0 image with the mosaic released on MAST jw02736-o001_t001_nircam_clear-f200w_i2d.fits. For comparison purposes, the right panel is output with the same sampling rate (PSR = 1.0) as the left one. The image on the right panel displays a better background subtraction. It also shows a more continuous distribution of ICL in comparison to the image on the left. The 1/f effect is visually apparent on the left panel.
Paper: UPdec-Webb: A Data Set for Coaddition of JWST NIRCam Images
Authors: Lei Wang, Huanyuan Shan, Lin Nie, Cheng Cheng, Fang-Ting Yuan, Qifan Cui, Guoliang Li, Yushan Xie, Dezi Liu, Yao Liu, Min Fang, Nan Li, Peng Jia, Ran Li, Fengshan Liu, Yiping Shu, Chang Jiang, Cheng-Liang Wei, Han Qu, Wen-Wen Zheng, Li-Yan Zhu, Xi Kang
Figure caption: UPDC enhances the signal of faint sources. The detected sources are indicated by white ellipticals, i.e., the Kron apertures (R. G. Kron 1980). In the top row of stamps, eight faint sources marked by colored arrows are undetected in other bands (Drizzle images, i.e., UPDC-iter0 images) but are identified after UPDC processing (UPDC-iter5 images). This reflects the improved performance of UPDC in detecting faint sources. The panels in the middle row exhibit about 25% more new detections (16 sources) than those in the upper row. Half of the 16 new detections have been crossmatched in multiple bands, while the remaining half marked with green crosses have not been crossmatched, but exhibit 6σbkg over the background. In the bottom row of panels, there are minimal new detections in the UPDC-iter10 coadditions compared to the UPDC-iter5 images, with only four additional cases in total. The coordinate axis is measured in pixels, with each pixel corresponding to 0﹩\mathop{.}\limits^{{\rm{^{\prime} }}{\rm{^{\prime} }}}﹩031. The center of the stamp is located at R.​​​​​​A. = 110﹩\mathop{.}\limits^{\circ }﹩694059, decl. = −73﹩\mathop{.}\limits^{\circ }﹩475037.
Paper: UPdec-Webb: A Data Set for Coaddition of JWST NIRCam Images
Authors: Lei Wang, Huanyuan Shan, Lin Nie, Cheng Cheng, Fang-Ting Yuan, Qifan Cui, Guoliang Li, Yushan Xie, Dezi Liu, Yao Liu, Min Fang, Nan Li, Peng Jia, Ran Li, Fengshan Liu, Yiping Shu, Chang Jiang, Cheng-Liang Wei, Han Qu, Wen-Wen Zheng, Li-Yan Zhu, Xi Kang
Figure caption: Coaddition for a point source from SMACSJ0723 (a star at R.​​​​​​A. = 110﹩\mathop{.}\limits^{\circ }﹩865243, decl. = −73﹩\mathop{.}\limits^{\circ }﹩454731) using different methods in the F200W band. Five circles are displayed on the top left panel, representing radii of 50 mas, 80 mas (radius of first minimum), 150 mas, 1″, and 1﹩\mathop{.}\limits^{{\rm{^{\prime} }}{\rm{^{\prime} }}}﹩8, respectively. We primarily compare our pipeline with the Stark–Pantin algorithm at the fifth and 10th iterations under the same positivity constraint (Equation (2)). If the constraint is removed, Stark–Pantin coaddition produces a significant ringing effect around bright point sources as shown on the bottom left panel. Tag-A denotes another point source that is severely affected by the ringing effect during the Stark–Pantin coaddition. The UPDC algorithm controls noise well and reduces the ringing effect significantly under the same number of iterations.
Paper: UPdec-Webb: A Data Set for Coaddition of JWST NIRCam Images
Authors: Lei Wang, Huanyuan Shan, Lin Nie, Cheng Cheng, Fang-Ting Yuan, Qifan Cui, Guoliang Li, Yushan Xie, Dezi Liu, Yao Liu, Min Fang, Nan Li, Peng Jia, Ran Li, Fengshan Liu, Yiping Shu, Chang Jiang, Cheng-Liang Wei, Han Qu, Wen-Wen Zheng, Li-Yan Zhu, Xi Kang
Figure caption: Enhancement for objects in the parallel field of SMACSJ0723. Three pairs of objects have been designated as Tag-A and display differing levels of overlap in their line of sight. However, thanks to the implementation of the UPDC algorithm, each pair of objects is now more distinct, thus enabling an improved photometric analysis. Moreover, the UPDC algorithm has successfully identified a substructure within the galaxy located at Tag-B. This substructure may either be a foreground or background galaxy or part of the galaxy itself. Originally, the galaxy featured a luminous bulge and surrounding disk; however, following our pipeline processing, it now exhibits a clear two-arm spiral structure, evidenced at Tag-C.
Paper: UPdec-Webb: A Data Set for Coaddition of JWST NIRCam Images
Authors: Lei Wang, Huanyuan Shan, Lin Nie, Cheng Cheng, Fang-Ting Yuan, Qifan Cui, Guoliang Li, Yushan Xie, Dezi Liu, Yao Liu, Min Fang, Nan Li, Peng Jia, Ran Li, Fengshan Liu, Yiping Shu, Chang Jiang, Cheng-Liang Wei, Han Qu, Wen-Wen Zheng, Li-Yan Zhu, Xi Kang
Figure caption: Deblending for overlapped objects. The red galaxy labeled by Tag-A exhibits clearer point sources following UPDC processing, which are generally believed to be globular clusters, such as the famous Sparkler Galaxy in Figure 8. There is a possibility that the white object situated at the lower right of the bulge is a foreground/background galaxy. Tag-B, the spiral galaxy, is effectively freed from blurring as a result of UPDC processing, allowing it to be distinguished from both the foreground stars and the galaxy to its right. The UPDC algorithm not only suppresses the central spikes of the elliptical galaxy (Tag-C) but also separates a galaxy from its upper left. Tag-D’s star in the UPDC-iter10 has an obvious green color, due to the central flux missing in F277W and F200W bands. This causes the green component of the PSF to remain uncorrected by UPDC.