Work

PhotoD with LSST

Year: 2025

Type: article

Abstract: As demonstrated with the Sloan Digital Sky Survey (SDSS), Pan-STARRS, and most recently with Gaia data, broadband near-UV to near-IR stellar photometry can be used to estimate distance, metallicity, and interstellar dust extinction along the line of sight for stars in the Galaxy. Anticipating photometric catalogs with tens of billions of stars from Rubin's Legacy Survey of Space and Time (LSST), we present a Bayesian model and pipeline that build on previous work and can handle LSST-sized datasets. Likelihood computations utilize MIST/Dartmouth isochrones and priors are derived from TRILEGAL-based simulated LSST catalogs from P. Dal Tio et al. The computation speed is about 10 ms per star on a single core for both optimized grid search and Markov Chain Monte Carlo methods

Source: RUNG

Authors: Palaversa, Lovro, Ivezić, Željko, Caplar, Neven, Mrakovčić, Karlo, Abel, Bob, Razim, Oleksandra, Matković, Filip, Yablonski, Connor, Šarić, Toni, Jurkić, Tomislav

Institutions: Ruđer Bošković Institute, University of Washington, University of Rijeka, Olympic College, University of Zagreb

Language: English

Topic: Stellar, planetary, and galactic studies

Subfield: Astronomy and Astrophysics

Field: Physics and Astronomy

Domain: Physical Sciences

Open Access status: green

Funders: National Science Foundation, U.S. Department of Energy, National Aeronautics and Space Administration, Alfred P. Sloan Foundation, Washington Research Foundation, University of Washington, European Space Agency, Max-Planck-Gesellschaft, Hrvatska Zaklada za Znanost, Institut Ruđer Bošković

Awards: AXS - Enabling Analysis of Petascale Astronomical Datasets, Mining the Variable Sky

OpenAlex ID: W7143262983

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