Fast radio burst dispersion is an unbiased tracer of matter on large scales
Shion Andrew, Haochen Wang, Kiyoshi Masui, Josh Borrow, Calvin Leung, Ryan Raikman, Matthieu Schaller, Joop Schaye, and James M. Sullivan

TL;DR
Fast radio burst dispersion measures can serve as an unbiased large-scale matter tracer, providing a new cosmological probe comparable to weak lensing and redshift-space distortions.
Contribution
This work demonstrates that FRB dispersion is an unbiased matter tracer on large scales and introduces a method to constrain cosmological parameters using FRB data.
Findings
FRB dispersion measures trace matter distribution with minimal bias.
The dispersion-galaxy cross-power spectrum constrains $B_8$ independently of feedback physics.
Approximately 10^5 localized FRBs can match the statistical power of 10^8 weak-lensing galaxy measurements.
Abstract
The dispersion of fast radio bursts (FRBs) measures the column density of free electrons, tracing the diffuse ionized gas that contains more than of all baryons. On linear scales the FRB dispersion field is an approximately unbiased tracer of the matter distribution, an idea long assumed in the FRB large-scale structure literature and recently formalized by Zhou and Zhang [arXiv:2510.11022]. This follows from baryon-mass conservation, which forces the total baryon field to have unit linear bias, with dispersion inheriting this bias up to small corrections from the stellar and neutral-gas components. We show these corrections can be bounded at the percent level using existing galaxy and 21 cm surveys, and confirm with the FLAMINGO hydrodynamical simulations that the electron bias varies at the percent level across a wide range of feedback prescriptions. The dispersion-galaxy…
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.
