Probing Physics Beyond the Standard Model through Combined Analyses of Next-Generation Type Ia Supernova, CMB, and BAO Surveys

TL;DR

This paper forecasts how combining future supernova, CMB, and BAO data can improve constraints on dark energy, neutrino masses, and extensions to the standard cosmological model.

Contribution

It introduces a comprehensive forecast framework for combined analyses of next-generation surveys, highlighting potential improvements in cosmological parameter constraints.

Findings

LSST Year-3 supernova sample can double dark energy constraint precision.

DESI-DR3 improves low-redshift BAO measurements by up to 80%.

Joint datasets could enable a 2-3 sigma detection of neutrino mass sum.

Abstract

Observations of Type Ia supernovae (\sne), which probe the late Universe, together with baryon acoustic oscillations (BAO) and the cosmic microwave background (CMB), which probe the intermediate and early epochs, provide complementary constraints on the expansion history of the Universe. In this work, we forecast constraints on dark energy and other extensions to the standard cosmological model by combining the SNIa sample expected from the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST), data from current and forthcoming CMB surveys, and BAO measurements from the Dark Energy Spectroscopic Instrument (DESI). For the CMB, we use temperature, polarization, and lensing power spectra ($TT/EE/TE/\phi\phi$) from South Pole Telescope, the planned Advanced Simons Observatory, and a CMB-S4-like experiment. We derive constraints on $\Lambda {\rm CDM}$ and its extensions involving the dark energy equation of state parameters $(w_{0}, w_{a})$ and the sum of neutrino masses $\sum m_{\nu}$, using a Markov Chain Monte Carlo (MCMC) sampling framework. We find that the LSST Year-3 SNIa sample can improve upon the DES Year-5 dark energy constraints by a factor of $\times2-\times2.5$, with the gains driven primarily by the significantly higher SNIa density in the LSST sample. Similarly, DESI-DR3 shows up to a $\times1.8$ improvement on dark energy parameters over DR2, driven largely by the substantial increase in low-redshift sample. Combining CMB with LSST-Y3-SNIa and DESI-DR3-BAO yields $\sigma(w_{0}) = 0.028$ and $\sigma(w_{a}) = 0.11$ for $w_{0} w_{a} {\rm CDM}$ cosmology with the results being largely independent of the CMB dataset. The constraints weaken by 10%-30% when freeing $\sum m_{\nu}$ and spatial curvature. Moreover, the joint analysis of the three datasets can enable a $2-3\sigma$ detection of $\sum m_{\nu}$.