adsabs/AstroCLIMB huggingface dataset:
Paper: Volatile Elements Characterized by MarSCoDe in Materials at Zhurong Landing Site
Authors: Yizhong Zhang, Xin Ren, Zhaopeng Chen, Yuxuan Luo, Wangli Chen, Jianjun Liu, Xiangfeng Liu, Zhenqiang Zhang, Weiming Xu, Rong Shu, Chunlai Li
Figure caption: S ∼564 nm peak in rock targets on the surface of Mars. (a) An example spectrum of a detected target (Sol69_SCI_20210723193507). (b) shows the spectral comparison between seven in situ rock targets and laboratory-collected reference samples (GBW07105 (blank control) and GBW07164 (14.86 SO3 wt%)) at the wavelength between between 560 and 570 nm. The black dashed lines and dotted lines represent the wavelength positions of S peaks. The spectral data were normalized to O peak area around 778 nm and offset for clarity.
Paper: Volatile Elements Characterized by MarSCoDe in Materials at Zhurong Landing Site
Authors: Yizhong Zhang, Xin Ren, Zhaopeng Chen, Yuxuan Luo, Wangli Chen, Jianjun Liu, Xiangfeng Liu, Zhenqiang Zhang, Weiming Xu, Rong Shu, Chunlai Li
Figure caption: SWIR spectra of different types of targets and their comparison with the CRISM library, (a), (b), and (c) are the images of typical Martian rocks, soil, and dune targets in the Zhurong landing site, and (d) are their corresponding SWIR spectra. (e), (f), and (g) are the standard spectra of different hydrated silica, sulfate, and iron oxide minerals, respectively. These spectra are from Viviano et al. (2014).
Paper: Volatile Elements Characterized by MarSCoDe in Materials at Zhurong Landing Site
Authors: Yizhong Zhang, Xin Ren, Zhaopeng Chen, Yuxuan Luo, Wangli Chen, Jianjun Liu, Xiangfeng Liu, Zhenqiang Zhang, Weiming Xu, Rong Shu, Chunlai Li
Figure caption: Cl 837.82 nm peak detected in the rock target observed on Sol 45. The dashed line in the figure is the LIBS spectrum of the GBW07449 target (Shanshan saline–alkali soil standard material, whose Cl abundance is 4%) and GBW07447 target (Hanggin Rear Banner saline–alkali soil standard material, whose Cl abundance is 0.78%) collected in ground laboratory. The spectral data were normalized to O peak area around 778 nm and offset for clarity.
Paper: Volatile Elements Characterized by MarSCoDe in Materials at Zhurong Landing Site
Authors: Yizhong Zhang, Xin Ren, Zhaopeng Chen, Yuxuan Luo, Wangli Chen, Jianjun Liu, Xiangfeng Liu, Zhenqiang Zhang, Weiming Xu, Rong Shu, Chunlai Li
Figure caption: The relationships between the normalized areas of characteristic peaks of major elements and corresponding element abundance of MCCT targets. The “Normed area” on the x-axis represents the normalized area of the emission peaks, and the “wt(%)” on the y-axis represents the element abundance. Black dashed lines are the linear fitting results of the normalized area and the element abundance.
Paper: Volatile Elements Characterized by MarSCoDe in Materials at Zhurong Landing Site
Authors: Yizhong Zhang, Xin Ren, Zhaopeng Chen, Yuxuan Luo, Wangli Chen, Jianjun Liu, Xiangfeng Liu, Zhenqiang Zhang, Weiming Xu, Rong Shu, Chunlai Li
Figure caption: The traverse of the Zhurong rover and the targets analyzed in this work. Red is rock targets, green represents soil targets, and blue is dune materials. For images of each target, the left taken by the Navigation and Terrain Cameras (NaTeCam) displays the target analyzed, and the center of the right image taken by the MarSCoDe microimaging camera shows the point of laser ablation.
Paper: Volatile Elements Characterized by MarSCoDe in Materials at Zhurong Landing Site
Authors: Yizhong Zhang, Xin Ren, Zhaopeng Chen, Yuxuan Luo, Wangli Chen, Jianjun Liu, Xiangfeng Liu, Zhenqiang Zhang, Weiming Xu, Rong Shu, Chunlai Li
Figure caption: Relationship of normalized peak areas on rock targets with sulfur signals, (a) is Ca and S, and (b) is H and S. Data points affected by the roughness effect in (b) are labeled separately.
Paper: Volatile Elements Characterized by MarSCoDe in Materials at Zhurong Landing Site
Authors: Yizhong Zhang, Xin Ren, Zhaopeng Chen, Yuxuan Luo, Wangli Chen, Jianjun Liu, Xiangfeng Liu, Zhenqiang Zhang, Weiming Xu, Rong Shu, Chunlai Li
Figure caption: Fitting results of S ∼564 nm peak in the seven Martian surface rock targets. After the spectral fitting is completed, the S peak fitting area is normalized to the O peak area around 778 nm.
Paper: KMT-2023-BLG-2669: Ninth Free-floating Planet Candidate with θ E Measurements
Authors: Youn Kil Jung, Kyu-Ha Hwang, Hongjing Yang, Andrew Gould, Jennifer C. Yee, Cheongho Han, Michael D. Albrow, Sun-Ju Chung, Yoon-Hyun Ryu, In-Gu Shin, Yossi Shvartzvald, Weicheng Zang, Sang-Mok Cha, Dong-Jin Kim, Seung-Lee Kim, Chung-Uk Lee, Dong-Joo Lee, Yongseok Lee, Byeong-Gon Park, Richard W. Pogge
Figure caption: Contrast ratio vs. host–source separation for a total of 25 late-time observations of a total of 12 2L1S microlensing events. The observatory and filter of each measurement are specified by the color, as indicated in the legend. There is generally an envelope of rising maximum contrast ratio as a function of separation, but with three exceptions. First, the high contrast ratio for MB08379 (HST V band) would not be considered as a reliable detection, because the measured lens flux is highly uncertain. Second, the anomalously high contrast ratio for the OB120950 (HST V-band) observation, when considered independently of the HST I-band and Keck K-band observations, has a factor of 2 range (at 1σ) in lens flux, so it is not clear that it would be regarded as a detection by itself. Third, the high-contrast star that was apparently detected for OB161195 is known not to be the lens, because the observers investigated the wrong source star.
Paper: KMT-2023-BLG-2669: Ninth Free-floating Planet Candidate with θ E Measurements
Authors: Youn Kil Jung, Kyu-Ha Hwang, Hongjing Yang, Andrew Gould, Jennifer C. Yee, Cheongho Han, Michael D. Albrow, Sun-Ju Chung, Yoon-Hyun Ryu, In-Gu Shin, Yossi Shvartzvald, Weicheng Zang, Sang-Mok Cha, Dong-Jin Kim, Seung-Lee Kim, Chung-Uk Lee, Dong-Joo Lee, Yongseok Lee, Byeong-Gon Park, Richard W. Pogge
Figure caption: Gaia DR3 proper motions of stars within 5′ of KMT-2023-BLG-2669. The blue and red dots correspond to red giant and main-sequence stars, respectively. In each population, the two solid contours include 68% and 95% of all stars. The black dot is the location of the baseline object (source). The dashed circle is the locus of the lens–source relative proper motions, μ rel = 4.82 mas yr−1.
Paper: KMT-2023-BLG-2669: Ninth Free-floating Planet Candidate with θ E Measurements
Authors: Youn Kil Jung, Kyu-Ha Hwang, Hongjing Yang, Andrew Gould, Jennifer C. Yee, Cheongho Han, Michael D. Albrow, Sun-Ju Chung, Yoon-Hyun Ryu, In-Gu Shin, Yossi Shvartzvald, Weicheng Zang, Sang-Mok Cha, Dong-Jin Kim, Seung-Lee Kim, Chung-Uk Lee, Dong-Joo Lee, Yongseok Lee, Byeong-Gon Park, Richard W. Pogge
Figure caption: Light curve of KMT-2023-BLG-2669. The upper panel shows the full data from the 2023 observing season and the lower panel shows the close-up of the event. The orange and black curves are the PSPL and FSPL (f B = 0) models, respectively.
Paper: KMT-2023-BLG-2669: Ninth Free-floating Planet Candidate with θ E Measurements
Authors: Youn Kil Jung, Kyu-Ha Hwang, Hongjing Yang, Andrew Gould, Jennifer C. Yee, Cheongho Han, Michael D. Albrow, Sun-Ju Chung, Yoon-Hyun Ryu, In-Gu Shin, Yossi Shvartzvald, Weicheng Zang, Sang-Mok Cha, Dong-Jin Kim, Seung-Lee Kim, Chung-Uk Lee, Dong-Joo Lee, Yongseok Lee, Byeong-Gon Park, Richard W. Pogge
Figure caption: Detection probability for the putative host star in the (s, q) plane.
Paper: KMT-2023-BLG-2669: Ninth Free-floating Planet Candidate with θ E Measurements
Authors: Youn Kil Jung, Kyu-Ha Hwang, Hongjing Yang, Andrew Gould, Jennifer C. Yee, Cheongho Han, Michael D. Albrow, Sun-Ju Chung, Yoon-Hyun Ryu, In-Gu Shin, Yossi Shvartzvald, Weicheng Zang, Sang-Mok Cha, Dong-Jin Kim, Seung-Lee Kim, Chung-Uk Lee, Dong-Joo Lee, Yongseok Lee, Byeong-Gon Park, Richard W. Pogge
Figure caption: VVV CMD for stars within 4′ of KMT-2023-BLG-2669. The notations are identical to those in Figure 2.
Paper: KMT-2023-BLG-2669: Ninth Free-floating Planet Candidate with θ E Measurements
Authors: Youn Kil Jung, Kyu-Ha Hwang, Hongjing Yang, Andrew Gould, Jennifer C. Yee, Cheongho Han, Michael D. Albrow, Sun-Ju Chung, Yoon-Hyun Ryu, In-Gu Shin, Yossi Shvartzvald, Weicheng Zang, Sang-Mok Cha, Dong-Jin Kim, Seung-Lee Kim, Chung-Uk Lee, Dong-Joo Lee, Yongseok Lee, Byeong-Gon Park, Richard W. Pogge
Figure caption: KMTS CMD for stars within 4′ of KMT-2023-BLG-2669. The blue and red dots are the locations of the baseline object (source) and the GC, respectively.
Paper: Utilizing Photometry from Multiple Sources to Mitigate Stellar Variability in Precise Radial Velocities: A Case Study of Kepler-21
Authors: Corey Beard, Paul Robertson, Mark R. Giovinazzi, Joseph M. Akana Murphy, Eric B. Ford, Samuel Halverson, Te Han, Rae Holcomb, Jack Lubin, Rafael Luque, Pranav Premnath, Chad F. Bender, Cullen H. Blake, Qian Gong, Howard Isaacson, Shubham Kanodia, Dan Li, Andrea S. J. Lin, Sarah E. Logsdon, Emily Lubar, Michael W. McElwain, Andrew Monson, Joe P. Ninan, Jayadev Rajagopal, Arpita Roy, Christian Schwab, Gudmundur Stefansson, Ryan C. Terrien, Jason T. Wright
Figure caption: Correlation between the mass and radius of known exoplanets with a measured mass and radius, taken from the NASA Exoplanet Archive on 2023 August 12. We only use planets with precisely measured masses (M  p /σ > 3). We add our new mass and radius measurements for Kepler-21 b in red. We additionally add theoretical planet compositions. Earth and iron compositions are taken from Zeng et al. (2019), and we extract irradiated water compositions from Aguichine et al. (2021). We use “Atm” to indicate the percentage of water in the atmosphere, and “Core” to indicate the percentage in the planet core. Kepler-21 b’s placement in the radius valley made it a candidate water world, though it seems such scenarios can likely be ruled out.
Paper: Utilizing Photometry from Multiple Sources to Mitigate Stellar Variability in Precise Radial Velocities: A Case Study of Kepler-21
Authors: Corey Beard, Paul Robertson, Mark R. Giovinazzi, Joseph M. Akana Murphy, Eric B. Ford, Samuel Halverson, Te Han, Rae Holcomb, Jack Lubin, Rafael Luque, Pranav Premnath, Chad F. Bender, Cullen H. Blake, Qian Gong, Howard Isaacson, Shubham Kanodia, Dan Li, Andrea S. J. Lin, Sarah E. Logsdon, Emily Lubar, Michael W. McElwain, Andrew Monson, Joe P. Ninan, Jayadev Rajagopal, Arpita Roy, Christian Schwab, Gudmundur Stefansson, Ryan C. Terrien, Jason T. Wright
Figure caption: Injection-recovery results for fits with an injected “transiting” planet. The amplitude and period of the known planet are denoted by a black dashed line. Top left: injection-recovery tests run with no GP training. Top right: differential preference for recovering the injected planets between Kepler and untrained fits. Bottom left: differential preference for recovering the injected planets between TESS and untrained fits. Bottom right: differential BF improvements between the training methods. Longer orbital periods are consistently recovered more robustly when training on Kepler.
Paper: Utilizing Photometry from Multiple Sources to Mitigate Stellar Variability in Precise Radial Velocities: A Case Study of Kepler-21
Authors: Corey Beard, Paul Robertson, Mark R. Giovinazzi, Joseph M. Akana Murphy, Eric B. Ford, Samuel Halverson, Te Han, Rae Holcomb, Jack Lubin, Rafael Luque, Pranav Premnath, Chad F. Bender, Cullen H. Blake, Qian Gong, Howard Isaacson, Shubham Kanodia, Dan Li, Andrea S. J. Lin, Sarah E. Logsdon, Emily Lubar, Michael W. McElwain, Andrew Monson, Joe P. Ninan, Jayadev Rajagopal, Arpita Roy, Christian Schwab, Gudmundur Stefansson, Ryan C. Terrien, Jason T. Wright
Figure caption: Injection-recovery results for fits with an injected “RV-detected” planet. The amplitude and period of the known planet are denoted by a black dashed line. Top left: injection-recovery tests run with no GP training. Top right: differential preference for recovering the injected planets between Kepler and untrained fits. Bottom left: differential preference for recovering the injected planets between TESS and untrained fits. Bottom right: differential BF improvements between the training methods. The vast majority of injected planets were recovered more strongly when training on Kepler.
Paper: Utilizing Photometry from Multiple Sources to Mitigate Stellar Variability in Precise Radial Velocities: A Case Study of Kepler-21
Authors: Corey Beard, Paul Robertson, Mark R. Giovinazzi, Joseph M. Akana Murphy, Eric B. Ford, Samuel Halverson, Te Han, Rae Holcomb, Jack Lubin, Rafael Luque, Pranav Premnath, Chad F. Bender, Cullen H. Blake, Qian Gong, Howard Isaacson, Shubham Kanodia, Dan Li, Andrea S. J. Lin, Sarah E. Logsdon, Emily Lubar, Michael W. McElwain, Andrew Monson, Joe P. Ninan, Jayadev Rajagopal, Arpita Roy, Christian Schwab, Gudmundur Stefansson, Ryan C. Terrien, Jason T. Wright
Figure caption: Top: rejection sampling for a variety of masses and orbital periods of the long-period companion, where inclination is fixed at 90°. Bottom: same as above, but with inclination allowed to vary. Due to the lack of sizable astrometric signatures in Gaia data, we can rule out many long-period and high-mass objects.
Paper: Utilizing Photometry from Multiple Sources to Mitigate Stellar Variability in Precise Radial Velocities: A Case Study of Kepler-21
Authors: Corey Beard, Paul Robertson, Mark R. Giovinazzi, Joseph M. Akana Murphy, Eric B. Ford, Samuel Halverson, Te Han, Rae Holcomb, Jack Lubin, Rafael Luque, Pranav Premnath, Chad F. Bender, Cullen H. Blake, Qian Gong, Howard Isaacson, Shubham Kanodia, Dan Li, Andrea S. J. Lin, Sarah E. Logsdon, Emily Lubar, Michael W. McElwain, Andrew Monson, Joe P. Ninan, Jayadev Rajagopal, Arpita Roy, Christian Schwab, Gudmundur Stefansson, Ryan C. Terrien, Jason T. Wright
Figure caption: Left: phase-folded Kepler transit of planet b, and the fit residuals below. Right: phase-folded TESS transit of planet b, with residuals below. We recover the previously reported transits in Kepler, but we also include, for the first time, a fit using TESS data. The transit of a planet with a radius of 1.618 R ⊕ orbiting a star with (R * = 1.902 R ⊙), is quite small, and difficult to discern from an individual transit. Nonetheless, folding multiple TESS transits and binning the data robustly reveals a transit-like structure.
Paper: Utilizing Photometry from Multiple Sources to Mitigate Stellar Variability in Precise Radial Velocities: A Case Study of Kepler-21
Authors: Corey Beard, Paul Robertson, Mark R. Giovinazzi, Joseph M. Akana Murphy, Eric B. Ford, Samuel Halverson, Te Han, Rae Holcomb, Jack Lubin, Rafael Luque, Pranav Premnath, Chad F. Bender, Cullen H. Blake, Qian Gong, Howard Isaacson, Shubham Kanodia, Dan Li, Andrea S. J. Lin, Sarah E. Logsdon, Emily Lubar, Michael W. McElwain, Andrew Monson, Joe P. Ninan, Jayadev Rajagopal, Arpita Roy, Christian Schwab, Gudmundur Stefansson, Ryan C. Terrien, Jason T. Wright
Figure caption: Top: RV time series of Kepler-21 spanning more than a decade. Light colors reflect the GP model used for each instrument. Middle: residuals of a one-planet, trend, and GP fit to the data. Bottom: phase-folded RVs to planet b.
Paper: Utilizing Photometry from Multiple Sources to Mitigate Stellar Variability in Precise Radial Velocities: A Case Study of Kepler-21
Authors: Corey Beard, Paul Robertson, Mark R. Giovinazzi, Joseph M. Akana Murphy, Eric B. Ford, Samuel Halverson, Te Han, Rae Holcomb, Jack Lubin, Rafael Luque, Pranav Premnath, Chad F. Bender, Cullen H. Blake, Qian Gong, Howard Isaacson, Shubham Kanodia, Dan Li, Andrea S. J. Lin, Sarah E. Logsdon, Emily Lubar, Michael W. McElwain, Andrew Monson, Joe P. Ninan, Jayadev Rajagopal, Arpita Roy, Christian Schwab, Gudmundur Stefansson, Ryan C. Terrien, Jason T. Wright
Figure caption: A plot of our NEID RV coverage as a function of time. TESS simultaneous viewing is highlighted with a light blue streak. All of our NEID RVs were obtained near in time or simultaneously with TESS observations.
Paper: Utilizing Photometry from Multiple Sources to Mitigate Stellar Variability in Precise Radial Velocities: A Case Study of Kepler-21
Authors: Corey Beard, Paul Robertson, Mark R. Giovinazzi, Joseph M. Akana Murphy, Eric B. Ford, Samuel Halverson, Te Han, Rae Holcomb, Jack Lubin, Rafael Luque, Pranav Premnath, Chad F. Bender, Cullen H. Blake, Qian Gong, Howard Isaacson, Shubham Kanodia, Dan Li, Andrea S. J. Lin, Sarah E. Logsdon, Emily Lubar, Michael W. McElwain, Andrew Monson, Joe P. Ninan, Jayadev Rajagopal, Arpita Roy, Christian Schwab, Gudmundur Stefansson, Ryan C. Terrien, Jason T. Wright
Figure caption: Top: Kepler Quarters 6 and 7 PDCSAP flux, binned to 0.1 day. Bottom: TESS Sectors 40 and 41 PDCSAP flux, binned to 0.1 day. Both data sets exhibit clear, quasi-periodic variability caused by stellar magnetic activity. Simultaneous RVs are marked with red triangles.
Paper: Modeling Multiple Radius Valley Emergence Mechanisms with Multitransiting Systems
Authors: Madison VanWyngarden, Ryan Cloutier
Figure caption: The architectures and model-predicted minimum masses for half of the 75 planet pairs in our sample of systems for which the enveloped planet mass is known. The left panel displays the systems’ orbital architectures and planet sizes. Mutual inclinations are not reflected. Planets are classified as being either rocky (black markers) or gas enveloped (gray), based on their observed masses and radii. In a given row, the system’s planets that do not belong to the rocky-enveloped pair being considered are translucent. The right panel compares the model-predicted minimum masses of the enveloped planets in each pair for three radius valley emergence models: XUV-driven PE (blue-filled circles), CPML (red-filled circles), and PRV (green-filled circles). The model-predicted minimum masses are compared to the enveloped planet’s measured mass (black-filled triangles). All point estimates include their respective 1σ error bars.
Paper: Modeling Multiple Radius Valley Emergence Mechanisms with Multitransiting Systems
Authors: Madison VanWyngarden, Ryan Cloutier
Figure caption: Distributions of the probability of planetary system consistency with a given mechanism for our full sample of 36 multitransiting systems. The three physical mechanisms are abbreviated by PE, CPML, and PRV. Each distribution is smoothed by a kernel density estimation and the horizontal markers highlight the 16th, 50th, and 84th percentiles, respectively. Translucent violins depict the results of testing additional timescales than those described in Section 2.2. The fiducial timescale for PE, labeled f(M ⋆), is a function of stellar mass that ranges from 100 to 1000 Myr.
Paper: Modeling Multiple Radius Valley Emergence Mechanisms with Multitransiting Systems
Authors: Madison VanWyngarden, Ryan Cloutier
Figure caption: The planetary pairs with measured masses used in this study binned by stellar effective temperature. Dashed lines connect rocky-enveloped pairs within the same planetary system. The location of the radius valley is plotted as a black line at 1.6R ⊕ for T eff < 4700 K and at 1.8R ⊕ for T eff > 4700 K.
Paper: Modeling Multiple Radius Valley Emergence Mechanisms with Multitransiting Systems
Authors: Madison VanWyngarden, Ryan Cloutier
Figure caption:  PEPPER's code structure for radius valley emergence models of XUV-driven PE, CPML (top panel), and a PRV (bottom panel). The code, available on GitHub (VanWyngarden 2024b), is broken into four modules, which are color coded in the key in the top-left of the graphic. The flowchart illustrates the processes performed on both the rocky and enveloped planets within a multitransiting system.
Paper: Modeling Multiple Radius Valley Emergence Mechanisms with Multitransiting Systems
Authors: Madison VanWyngarden, Ryan Cloutier
Figure caption: Model-predicted minimum core masses of Kepler-36 c in order for the Kepler-36 system to be consistent with radius valley emergence mechanisms of XUV-driven PE (blue), core-powered mass loss (red), and a PRV (green). The minimum core mass distributions are shown alongside the planet’s mass posterior of 7.13 ± 0.18 M ⊕ from Vissapragada et al. (2020).
Paper: Modeling Multiple Radius Valley Emergence Mechanisms with Multitransiting Systems
Authors: Madison VanWyngarden, Ryan Cloutier
Figure caption: Same Figure 4 for the second half of our planet sample.
Paper: Modeling Multiple Radius Valley Emergence Mechanisms with Multitransiting Systems
Authors: Madison VanWyngarden, Ryan Cloutier
Figure caption: Same as Figure 6 after binning our planet sample into four stellar mass bins. The number of systems N per bin is annotated in each panel.
Paper: Modeling Multiple Radius Valley Emergence Mechanisms with Multitransiting Systems
Authors: Madison VanWyngarden, Ryan Cloutier
Figure caption: Same as Figure 6 after binning our planet sample into three stellar metallicity bins. The number of systems N per bin is annotated in each panel.
Paper: Analysis of Ring Galaxies Detected Using Deep Learning with Real and Simulated Data
Authors: Harish Krishnakumar, J. Bryce Kalmbach
Figure caption: Workflow starting from the initial data to the final CNN. Obtaining the initial data is described in Section 2. The simulation of 100,000 galaxies is described in Section 3.1. The CNN trained on the simulated data is described in Section 3.2. Finally, the process of transfer learning with the CNN is described in Section 3.3.
Paper: Analysis of Ring Galaxies Detected Using Deep Learning with Real and Simulated Data
Authors: Harish Krishnakumar, J. Bryce Kalmbach
Figure caption: Sky coverage of the application data. Left (a): the sky coverage before the subtraction of the sky covered by the Galaxy Zoo 2 project. Right (b): the blue represents the sky coverage of the Galaxy Zoo 2 project while the magenta represents the sky coverage of the modified catalog after removal.
Paper: Analysis of Ring Galaxies Detected Using Deep Learning with Real and Simulated Data
Authors: Harish Krishnakumar, J. Bryce Kalmbach
Figure caption:  R-band magnitude distribution for the Galaxy Zoo 2 rings.
Paper: Analysis of Ring Galaxies Detected Using Deep Learning with Real and Simulated Data
Authors: Harish Krishnakumar, J. Bryce Kalmbach
Figure caption: A simulated ring galaxy and modifications to make it further resemble real data. Left (a): the simulated light profile initially created by GALFIT. Middle (b): the simulated light profile after convolution with a PSF. Right (c): the simulated light profile after convolution with a PSF and the addition of randomized noise.
Paper: Analysis of Ring Galaxies Detected Using Deep Learning with Real and Simulated Data
Authors: Harish Krishnakumar, J. Bryce Kalmbach
Figure caption: Redshift distribution for the Galaxy Zoo 2 rings.
Paper: 3D Morphology and Motions of the Canis Major Region from Gaia DR3
Authors: Yiwei Dong, Ye Xu, Chaojie Hao, Yingjie Li, Dejian Liu, Yan Sun, Zehao Lin
Figure caption: Distributions of YSOs satisfying all the selection criteria. (a) The l–b distribution of YSOs overlaid on the 12CO (blue), 13CO (green), and C18O (red) intensity maps of the three MCs. The yellow circles, magenta crosses, and gray crosses indicate YSOs in Class II or earlier classes, Class III, and ambiguous evolutionary stages, respectively. The numbers of sources are also annotated. The red star represents the center of the CMa shell proposed by B. Fernandes et al. (2019). (b)–(d) The ϖ–﹩{\mu }_{{\alpha }^{* }}﹩, ϖ–μ  δ , and ﹩{\mu }_{{\alpha }^{* }}﹩–μ  δ  distributions of YSOs.