Constraining $M_\nu$ with the Bispectrum II: The Total Information Content of the Galaxy Bispectrum
ChangHoon Hahn, Francisco Villaescusa-Navarro

TL;DR
This paper demonstrates that the galaxy bispectrum, especially in redshift space, provides significantly improved constraints on neutrino mass and other cosmological parameters over traditional power spectrum analyses, using extensive simulations.
Contribution
It quantifies the total information content of the galaxy bispectrum down to nonlinear scales using large mock catalogs, showing substantial improvements in parameter constraints.
Findings
Galaxy bispectrum improves neutrino mass constraints by over 4.6 times compared to power spectrum.
Including bispectrum reduces uncertainties on key cosmological parameters by a factor of 2 to 4.
Constraints on $M_\nu$ can reach 0.048 eV with bispectrum and Planck priors, surpassing current limits.
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, . With standard analyses of two-point clustering statistics, 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 and other cosmological parameters. In this paper, we present the constraining power of the redshift-space galaxy bispectrum, . We construct the Molino suite of 75,000 mock galaxy catalogs from the Quijote -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…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
