Probing baryonic feedback with fast radio bursts: joint analyses with cosmic shear and galaxy clustering
Amy Wayland, David Alonso, and Robert Reischke

TL;DR
This paper forecasts how combining weak lensing, fast radio bursts, and galaxy clustering can improve constraints on cosmological parameters and baryonic feedback, addressing uncertainties in small-scale matter power spectrum modeling.
Contribution
It introduces a joint analysis framework that combines multiple cosmological probes to better constrain baryonic feedback and cosmological parameters, including systematics.
Findings
Joint WL and FRB analysis reduces $S_8$ constraint degradation by 80%.
FRBs alone constrain a degenerate combination of baryonic feedback parameters.
Adding galaxy clustering tightens some parameter constraints but doesn't significantly improve $S_8$ beyond WL and FRBs.
Abstract
Cosmological inference from weak lensing (WL) surveys is increasingly limited by uncertainties in baryonic physics, which suppress the non-linear matter power spectrum on small scales. Multi-probe analyses that incorporate complementary tracers of the gas distribution around haloes offer a pathway to calibrate these effects and recover unbiased cosmological information. In this work, we forecast the constraining power of a joint analysis combining fiducial data from a Stage-IV WL survey with measurements of the dispersion measure from fast radio bursts (FRBs). We evaluate the ability of this approach to simultaneously constrain cosmological parameters and the astrophysical processes governing baryonic feedback, and we quantify the impact of key FRB systematics, including redshift uncertainties and source clustering. We find that, even after accounting for these effects, a…
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.
