New limits on light dark matter - proton cross section from the cosmic large-scale structure
Reviewed by Pithpith:SJQHLGZAopen to challenge →
read the original abstract
We set the strongest limits to-date on the velocity-independent dark matter (DM) - proton cross section $\sigma$ for DM masses $m = 10\,\mathrm{keV}$ to $100\,\mathrm{GeV}$, using large-scale structure traced by the Lyman-alpha forest: e.g., a 95% lower limit $\sigma < 6 \times 10^{-30}\,\mathrm{cm}^2$, for $m = 100\,\mathrm{keV}$. Our results complement direct detection, which has limited sensitivity to sub-GeV DM. We use an emulator of cosmological simulations, combined with data from the smallest cosmological scales used to-date, to model and search for the imprint of primordial DM-proton collisions. Cosmological bounds are improved by up to a factor of 25.
This paper has not been read by Pith yet.
Forward citations
Cited by 5 Pith papers
-
Galactic Center Neutrinos from Cosmic Ray-Dark Matter Interactions
ANTARES Galactic Ridge neutrino observations constrain DM-nucleon elastic scattering cross sections down to keV-scale DM masses via cosmic ray–dark matter deep inelastic scattering.
-
Lyman-Alpha Forest and its Cross-Correlation with High-Redshift Galaxies in Effective Field Theory at the Field Level
An EFT-based field-level forward model for the Lyman-alpha forest matches simulations at the percent level on quasi-linear scales and generates mocks for DESI and DESI-II analyses.
-
Irreducible Constraints on Hadronically Interacting Sub-GeV Dark Matter
Sub-GeV dark matter that interacts hadronically is ruled out for nucleon scattering cross sections above 10^{-36} cm² across the keV to 100 MeV mass range by combined cosmological and particle-decay constraints.
-
Lyman-$\alpha$ forest constraints on pure and mixed fuzzy dark matter
Lyman-alpha forest data yield m_FDM > 1.9e-21 eV (95% CL) for pure FDM and f_FDM upper limits of 0.07-0.65 for mixed FDM at log10(m_FDM/eV) = -23 to -21.
-
Machine Learning Techniques for Astrophysics and Cosmology: Lyman-$\alpha$ forest
Review of machine learning applications for analyzing Lyman-alpha forest observations to probe cosmology, reionization, and dark matter.
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.