Browsing by Author "Ghosh, Aritra"

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    Morphological Parameters and Associated Uncertainties for 8 Million Galaxies in the Hyper Suprime-Cam Wide Survey
    (Wiley, 2023) Ghosh, Aritra; Urry, C. Megan; Mishra, Aayush; Perreault-Levasseur, Laurence; Natarajan, Priyamvada; Sanders, David B.; Nagai, Daisuke; Tian, Chuan; Cappelluti, Nico; Kartaltepe, Jeyhan S.; Powell, Meredith C.; Rau, Amrit; Treister, Ezequiel
    We use the Galaxy Morphology Posterior Estimation Network (GaMPEN) to estimate morphological parameters and associated uncertainties for & SIM;8 million galaxies in the Hyper Suprime-Cam Wide survey with z & LE; 0.75 and m & LE; 23. GaMPEN is a machine-learning framework that estimates Bayesian posteriors for a galaxy's bulge-to-total light ratio (L ( B )/L ( T )), effective radius (R ( e )), and flux (F). By first training on simulations of galaxies and then applying transfer learning using real data, we trained GaMPEN with <1% of our data set. This two-step process will be critical for applying machine-learning algorithms to future large imaging surveys, such as the Rubin-Legacy Survey of Space and Time, the Nancy Grace Roman Space Telescope, and Euclid. By comparing our results to those obtained using light profile fitting, we demonstrate that GaMPEN's predicted posterior distributions are well calibrated (& LSIM;5% deviation) and accurate. This represents a significant improvement over light profile fitting algorithms, which underestimate uncertainties by as much as & SIM;60%. For an overlapping subsample, we also compare the derived morphological parameters with values in two external catalogs and find that the results agree within the limits of uncertainties predicted by GaMPEN. This step also permits us to define an empirical relationship between the Sersic index and L ( B )/L ( T ) that can be used to convert between these two parameters. The catalog presented here represents a significant improvement in size (& SIM;10x), depth (& SIM;4 mag), and uncertainty quantification over previous state-of-the-art bulge+disk decomposition catalogs. With this work, we also release GaMPEN's source code and trained models, which can be adapted to other data sets.
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    Stripe 82-XL: The ∼54.8 deg2 and ∼18.8 Ms Chandra and XMM-Newton Point-source Catalog and Number of Counts
    (2024) Peca, Alessandro; Cappelluti, Nico; Lamassa, Stephanie; Urry, C. Megan; Moscetti, Massimo; Marchesi, Stefano; Sanders, David; Auge, Connor; Ghosh, Aritra; Ananna, Tonima Tasnim; Torres-Alba, Nuria; Treister, Ezequiel
    We present an enhanced version of the publicly available Stripe 82X catalog (S82-XL), featuring a comprehensive set of 22,737 unique X-ray point sources identified with a significance greater than or similar to 4 sigma. This catalog is four times larger than the original Stripe 82X catalog, by including additional archival data from the Chandra and XMM-Newton telescopes. Now covering similar to 54.8 deg(2 )of nonoverlapping sky area, the S82-XL catalog roughly doubles the area and depth of the original catalog, with limiting fluxes (half-area fluxes) of 3.4 x 10(-16) (2.4 x 10(-15)), 2.9 x 10(-15) (1.5 x 10(-14)), and 1.4 x 10(-15) (9.5 x 10(-15)) erg s(-1) cm(-2) across the soft (0.5-2 keV), hard (2-10 keV), and full (0.5-10 keV) bands, respectively. S82-XL occupies a unique region of flux-area parameter space compared to other X-ray surveys, identifying sources with rest-frame luminosities from 1.2 x 1038 to 1.6 x 1047 erg s(-1) in the 2-10 keV band (median X-ray luminosity, 7.2 x 1043 erg s(-1)), and spectroscopic redshifts up to z similar to 6. By using hardness ratios, we derived the obscuration of active galactic nuclei (AGNs), obtaining a median value of log(NH/cm(-2))=21.6-1.6+1.0 and an overall, obscured fraction ( log(NH/cm-2)>22 ) of similar to 36.9%. S82-XL serves as a benchmark in X-ray surveys and, with its extensive multiwavelength data, is especially valuable for comprehensive studies of luminous AGNs.