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Probing baryonic feedback with fast radio bursts: joint analyses with cosmic shear and galaxy clustering

This paper forecasts that a joint analysis of weak lensing, fast radio burst dispersion measures, and galaxy clustering effectively mitigates baryonic feedback uncertainties, significantly improving cosmological constraints on $S_8$ by breaking degeneracies between cosmological and astrophysical parameters.

Original authors: Amy Wayland, David Alonso, Robert Reischke

Published 2026-03-20

📖 5 min read🧠 Deep dive

CC BY 4.0

Original authors: Amy Wayland, David Alonso, Robert Reischke

Original paper licensed under CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). ✨ This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

The Big Picture: The "Cosmic Fog" Problem

Imagine you are trying to map the shape of a giant, invisible mountain range (the Universe's structure) by looking at how light bends around it. This is what astronomers do with Weak Gravitational Lensing (WL). They look at distant galaxies and see how their shapes are slightly distorted by the gravity of everything in between.

However, there's a problem. The Universe isn't just empty space and dark matter; it's also filled with baryons (normal matter like gas and stars). These baryons are messy. They get heated up by black holes, blown around by exploding stars, and pushed out of galaxies. This "baryonic feedback" acts like a fog or a glitchy filter on your camera. It distorts the map, making it hard to measure the true shape of the mountains.

If you try to measure the Universe's expansion or its total mass without accounting for this fog, your results will be wrong.

The New Tool: Fast Radio Bursts (FRBs)

Enter Fast Radio Bursts (FRBs). These are mysterious, super-loud flashes of radio waves coming from deep space. As these flashes travel to Earth, they pass through the cosmic fog. The gas in the fog slows down the radio waves slightly, depending on how much gas is there. This delay is called the Dispersion Measure (DM).

Think of FRBs as raindrops falling through a storm. By measuring how much the rain is slowed down, you can figure out exactly how much water (gas) is in the storm, even if you can't see the raindrops themselves.

The Experiment: A Three-Way Team-Up

The authors of this paper asked: What if we combine three different ways of looking at the Universe to clear up the fog?

Weak Lensing (The Shape Shifter): Maps the total gravity (Dark Matter + Gas).
FRBs (The Gas Detector): Maps the gas specifically.
Galaxy Clustering (The Tracer): Maps where the galaxies (the "cities" in our cosmic landscape) are located.

They ran a massive computer simulation (a "forecast") to see how well this team-up would work compared to using Weak Lensing alone.

Key Findings (The "Aha!" Moments)

1. The "Fog" is No Longer a Problem

When they used Weak Lensing alone, the "fog" of baryonic feedback made their measurements of the Universe's structure (specifically a parameter called $S_8$ ) about 2.2 times less precise. It was like trying to guess the weight of a suitcase while wearing thick, blurry gloves.

But when they added the FRB data? The gloves came off.
By combining the two, they recovered the precision. The "degradation" dropped from 2.2 down to 1.2. In fact, with a future, super-powerful FRB telescope, they could get it down to 1.0, meaning they could measure the Universe perfectly despite the fog.

2. The "Lock and Key" Analogy

The paper found that FRBs and Weak Lensing are like a Lock and Key.

FRBs alone are sensitive to the gas, but they get confused. They see two different things (how much gas is trapped in galaxies vs. how far the gas is pushed out) and can't tell them apart. It's like trying to guess the price of a car when you only know the total cost of the car plus the tax, but you don't know the split.
Weak Lensing is sensitive to the total mass but doesn't care much about the gas details.
Together: Weak Lensing holds the "key" that unlocks the confusion. When you combine them, the math works out, and you can measure both the gas details and the total mass perfectly.

3. The "Hubble Constant" Breakthrough

One of the biggest headaches in cosmology is measuring the Hubble Constant (how fast the Universe is expanding). Weak Lensing is notoriously bad at measuring this; it's like trying to measure the speed of a car by looking at a blurry photo of its shadow.
However, FRBs are great at it. Because the delay in the radio signal depends on the distance, FRBs act like a cosmic ruler. When combined with Weak Lensing, they suddenly make the measurement of the Universe's expansion rate much sharper.

4. Adding More Galaxies (The "6x2" Analysis)

The authors also tried adding a third team member: Galaxy Clustering (counting how galaxies group together). They used two types of galaxies:

LRGs: Big, red, old galaxies (like the "elders" of the universe).
ELGs: Young, blue, star-forming galaxies (like the "teenagers").

They hoped that by looking at both, they could get even better results.

The Result: It helped a little bit with measuring the total amount of matter in the Universe ( $\Omega_m$ ), but it didn't make the "fog" measurement any better than the FRB + Weak Lensing duo already did. The FRB + Weak Lensing team was already doing the heavy lifting.

The Bottom Line

This paper is a "future forecast." It says: "Don't worry about the messy gas in the Universe anymore."

If we build the next generation of telescopes (like the Vera C. Rubin Observatory for lensing and the SKA for radio bursts), we can use Fast Radio Bursts as a special tool to calibrate our maps. By combining these different "eyes" on the Universe, we can finally see through the cosmic fog, measure the Universe's expansion accurately, and understand how black holes and stars shape the cosmos.

In short: FRBs are the missing piece of the puzzle that lets us clean up the blurry picture of the Universe.

1. Problem Statement

Cosmological inference from Weak Lensing (WL) surveys (e.g., Euclid, LSST) is increasingly limited by uncertainties in baryonic physics. Processes such as star formation and Active Galactic Nuclei (AGN) feedback redistribute gas within and around dark matter haloes, suppressing the non-linear matter power spectrum on small scales by up to 30%. If unaccounted for, these effects introduce significant biases in cosmological parameter estimation (specifically $S_8 = \sigma_8\sqrt{\Omega_m/0.3}$ ).

Current mitigation strategies, such as conservative scale cuts, discard valuable small-scale information. While hydrodynamical simulations offer models, they rely on sub-grid assumptions. Observational tracers like the Sunyaev-Zel'dovich (SZ) effect and X-rays probe dense, virialized gas but are less sensitive to the diffuse intergalactic medium (IGM) where the majority of "missing" baryons reside. The authors propose Fast Radio Bursts (FRBs) as a novel, complementary tracer to probe the full electron distribution and break degeneracies between cosmological and baryonic parameters.

2. Methodology

The authors perform a forecast analysis using a multi-tracer framework combining:

Weak Lensing (WL): Cosmic shear from a fiducial Stage-IV survey (LSST-like).
Fast Radio Bursts (FRBs): Dispersion Measure (DM) fluctuations, which trace the integrated column density of free electrons.
Galaxy Clustering (GC): Using Luminous Red Galaxies (LRGs) and Emission Line Galaxies (ELGs) as tracers of the matter density field.

Theoretical Framework:

Power Spectra: The analysis utilizes a $N \times 2$ -point framework (specifically $3\times2$ and $6\times2$ ), calculating auto- and cross-correlations of angular power spectra ( $C_\ell$ ) for WL ( $\gamma$ ), FRB DM ( $D$ ), and Galaxy Clustering ( $g$ ).
Baryonic Model: They employ a hydrostatic equilibrium halo model (based on Mead et al. and Ferreira et al.) to describe gas profiles. The model includes:
- Dark Matter (NFW profile).
- Stars (Fedeli et al. profile).
- Bound Gas (Mead et al. profile).
- Ejected Gas (Schneider & Teyssier Gaussian profile).
- Key Parameters: $\log_{10} M_c$ (characteristic mass where half the gas is ejected) and $\eta_b$ (scale of ejected gas).
FRB Systematics: The model explicitly incorporates:
- Source Clustering: FRBs are biased tracers of matter ( $b_f$ ), modulating the observed DM field.
- Redshift Uncertainties: Marginalization over parameters ( $\alpha, \delta z$ ) governing the FRB redshift distribution.
- Host Variance: Intrinsic scatter in host galaxy DM contributions ( $\sigma_{host}$ ).
- Milky Way Foreground: Modeled as a large-scale systematic, mitigated via scale cuts ( $\ell_{min}$ ).

Analysis Setup:

Data Vectors:
- $3\times2$ -point: WL + FRB DM (Auto: $C_{DD}, C_{\gamma\gamma}$ ; Cross: $C_{D\gamma}$ ).
- $6\times2$ -point: WL + FRB DM + GC (LRG + ELG).
Likelihood: Gaussian likelihood with a covariance matrix derived from the Knox formula. Marginalization is performed over nuisance parameters (intrinsic alignments, photometric redshifts, shape biases, HOD parameters, and FRB systematics) using MCMC (Cobaya).

3. Key Contributions

FRB as a Baryonic Calibrator: This is one of the first works to forecast the joint constraining power of FRB DMs and WL specifically for calibrating baryonic feedback models in a cosmological context.
Systematic Treatment: The paper provides a rigorous treatment of FRB-specific systematics, including the impact of source clustering ( $b_f$ ) and redshift distribution uncertainties on cosmological constraints.
Multi-Tracer Synergy: It extends the analysis to a unified $6\times2$ -point framework, incorporating two distinct galaxy populations (LRGs and ELGs) to probe the halo-mass dependence of the bound gas fraction.
Degeneracy Breaking: The study demonstrates how FRBs break the degeneracy between cosmological parameters and baryonic feedback parameters that plagues WL-only analyses.

4. Key Results

Cosmological Constraints ( $S_8$ and $\Omega_m$ ):

WL Alone: Marginalizing over baryonic parameters degrades the $S_8$ constraint by a factor of 2.2 compared to the fixed-baryon case.
WL + FRB ( $3\times2$ ): The joint analysis significantly recovers this loss. The degradation factor on $S_8$ drops to 1.2 (optimistic) and 1.3 (including FRB systematics). This represents an ~80% improvement over WL alone.
Hubble Constant ( $h$ ): FRB DMs provide a direct probe of the distance-redshift relation ( $DM \propto h$ ). The joint analysis significantly tightens constraints on $h$ , a parameter typically weakly constrained by WL alone.

Baryonic Parameters ( $\log_{10} M_c$ and $\eta_b$ ):

FRB Alone: FRB data alone is sensitive only to a degenerate combination of $\log_{10} M_c$ and $\eta_b$ . It cannot tightly constrain either parameter individually.
Joint Analysis: The inclusion of WL breaks this degeneracy. WL is more sensitive to $\log_{10} M_c$ (bound gas), while FRBs are sensitive to the ejected gas extent ( $\eta_b$ ).
Comparison with other tracers:
- X-rays: Best at constraining $\log_{10} M_c$ (bound gas) but poor at $\eta_b$ .
- kSZ: Slightly better than FRBs for $\eta_b$ but suffers from degeneracies with $\beta$ .
- FRBs: Unique in their sensitivity to the diffuse IGM, complementing X-ray and kSZ.

Systematics and Future Surveys:

FRB Systematics: Marginalizing over redshift uncertainties ( $\alpha, \delta z$ ) and source clustering ( $b_f$ ) causes only a modest degradation in constraints (degradation factor increases from 1.2 to 1.3).
Future FRB Density: Increasing FRB number density by an order of magnitude (from $0.5$ to $5.0 \text{ deg}^{-2}$ , achievable by SKA/DSA-2000) reduces the $S_8$ degradation factor to 1.0, effectively recovering all information lost to baryonic uncertainties.
Galaxy Clustering ( $6\times2$ ): Adding LRGs and ELGs tightens constraints on $\Omega_m$ and $\log_{10} M_c$ but does not significantly improve $S_8$ constraints beyond the WL+FRB ( $3\times2$ ) case. This suggests galaxy clustering adds information on matter density and halo occupation but less on the specific baryonic feedback physics governing $S_8$ .

Tomography:

Splitting FRBs into redshift bins to probe the evolution of $\log_{10} M_c$ yields negligible improvement in $S_8$ constraints for the current survey configurations.

5. Significance

This work establishes Fast Radio Bursts as a critical, complementary probe for the era of precision cosmology.

Self-Calibration: It demonstrates that FRBs can act as an external calibrator for baryonic feedback, allowing WL surveys to utilize small-scale data without relying solely on theoretical simulations.
Robustness: The results hold even when accounting for realistic FRB systematics (redshift errors, clustering), making the approach viable for upcoming surveys like LSST and SKA.
Complementarity: The study highlights that no single tracer (WL, X-ray, kSZ, or FRB) is sufficient; a multi-probe approach is required to fully disentangle cosmological parameters from complex baryonic physics.
Future Outlook: The findings suggest that next-generation FRB surveys could fully recover the cosmological information currently lost to baryonic uncertainties, enabling more precise tests of the $\Lambda$ CDM model.