Role of future SNIa data from Rubin LSST in reinvestigating cosmological models
Shah R. Mitra A. Mukherjee P. Pal B. Pal S.
1 May 2024Oxford University Press
Monthly Notices of the Royal Astronomical Society
2024#530Issue 32627 - 2636 pp.
We study how future Type Ia supernovae (SNIa) standard candles detected by the Vera C. Rubin Observatory (LSST) can constrain some cosmological models. We use a realistic 3-yr SNIa simulated data set generated by the LSST Dark Energy Science Collaboration time domain pipeline, which includes a mix of spectroscopic and photometrically identified candidates. We combine these data with cosmic microwave background (CMB) and baryon acoustic oscillation (BAO) measurements to estimate the dark energy model parameters for two models – the baseline Lambda cold dark matter (CDM) and Chevallier–Polarski–Linder (CPL) dark energy parametrization. We compare them with the current constraints obtained from the joint analysis of the latest real data from the Pantheon SNIa compilation, CMB from Planck 2018 and BAO. Our analysis finds tighter constraints on the model parameters along with a significant reduction of correlation between H0 and σ8,0. We find that LSST is expected to significantly improve upon the existing SNIa data in the critical analysis of cosmological models.
(cosmology:) cosmological parameters , (cosmology:) dark energy , (stars:) supernovae: general , cosmology: observations , instrumentation: detectors , methods: data analysis
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Physics and Applied Mathematics Unit, Indian Statistical Institute, 203 B.T. Road, Kolkata, 700 108, India
Center for AstroPhysical Surveys, National Center for Supercomputing Applications, University of Illinois Urbana-Champaign, Urbana, 61801, IL, United States
Department of Astronomy, University of Illinois at Urbana-Champaign, Urbana, 61801, IL, United States
School of Material Science, Kazakh-British Technical University, 59 Tole bi street, Almaty, 050000, Kazakhstan
Department of Mathematics, Netaji Nagar College for Women, 170/13/1 N.S.C. Bose Road, Regent Estate, Kolkata, 700092, India
Technology Innovation Hub on Data Science, Big Data Analytics and Data Curation, Indian Statistical Institute, 203 B.T. Road, Kolkata, 700 108, India
Physics and Applied Mathematics Unit
Center for AstroPhysical Surveys
Department of Astronomy
School of Material Science
Department of Mathematics
Technology Innovation Hub on Data Science
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