PhotoD with LSST
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
Authors
- Bob Abel (ORCID: https://orcid.org/0000-0001-8418-3083)
- Tomislav Jurkić (ORCID: https://orcid.org/0000-0002-4993-2939)
- L. Palaversa (ORCID: https://orcid.org/0000-0003-3710-0331)
- Oleksandra Razim (ORCID: https://orcid.org/0000-0002-3045-0446)
- Neven Čaplar (ORCID: https://orcid.org/0000-0003-3287-5250)
- Karlo Mrakovčić (ORCID: https://orcid.org/0009-0009-8154-3827)
- Connor Yablonski (ORCID: https://orcid.org/0009-0000-0990-8339)
- Željko Ivezić
- Filip Matković
- Toni Šarić
Institutions
- University of Rijeka (HR)
- University of Zagreb (HR)
- University of Washington (US)
- Olympic College (US)
- Ruđer Bošković Institute (HR)
- University of Washington Applied Physics Laboratory (US)
- City University of Seattle (US)
Publication Details
- Journal
- RUNG
- Published
- 2025-02-04
- Primary Topic
- Galaxies: Formation, Evolution, Phenomena
- Type
- article
- Field-Weighted Citation Impact
- 0.00