Constraining $M_{\nu }$ with the Bispectrum II: The Total Information Content of the Galaxy Bispectrum

Abstract

Massive neutrinos suppress the growth of structure on small scales and leave an imprint on large-scale structure that can be measured to constrain their total mass, $M_{\nu }$. With standard analyses of two-point clustering statistics, $M_{\nu }$ constraints are severely limited by parameter degeneracies. Hahn et al.(2020) demonstrated that the bispectrum, the next higher-order statistic, can break these degeneracies and dramatically improve constraints on $M_{\nu }$ and other cosmological parameters. In this paper, we present the constraining power of the redshift-space galaxy bispectrum, $B_0^g$. We construct the Molino suite of 75,000 mock galaxy catalogs from the Quijote $N$-body simulations using the halo occupation distribution (HOD) model, which provides a galaxy bias framework well-suited for simulation-based approaches. Using these mocks, we present Fisher matrix forecasts for $\{{\Omega }_m,{\Omega }_b,h,n_s,{\sigma }_8,M_{\nu }\}$ and quantify, for the first time, the total information content of $B_0^g$ down to nonlinear scales. For $k_{\max }=0.5h/Mpc$, $B_0^g$ improves constraints on ${\Omega }_m,{\Omega }_b,h,n_s,{\sigma }_8$, and $M_{\nu }$ by 2.8, 3.1, 3.8, 4.2, 4.2, and $4.6\times$ over the power spectrum, after marginalizing over HOD parameters. Even with priors from $Planck$, $B_0^g$ improves all of the cosmological constraints by $\gtrsim 2\times$. In fact, for $P_{\ell }^g$ and $B_0^g$ out to $k_{\max }=0.5h/Mpc$ with $Planck$ priors, we achieve a $1\sigma$ $M_{\nu }$ constraint of 0.048 eV, which is tighter than the current best cosmological constraint. While effects such as survey geometry and assembly bias will have an impact, these constraints are derived for $(1h^{-1}\mathrm{Gpc}{)}^3$, a substantially smaller volume than upcoming surveys. Therefore, we conclude that the galaxy bispectrum will significantly improve cosmological constraints for upcoming galaxy surveys -- especially for $M_{\nu }$.

24 pages, 4 figures, the Molino catalog is publicly available at https://changhoonhahn.github.io/molino/

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