🔭 astrophysics

Impact of baryons on the population of Galactic subhalos and implications for dark matter searches

Using Auriga hydrodynamical simulations, this study demonstrates that baryonic physics significantly reduces the abundance and concentration of Galactic subhalos compared to dark-matter-only models, a finding that is crucial for optimizing dark matter search strategies via gamma-ray observations and gravitational signatures.

Original authors: Sara Porras-Bedmar, Miguel Á. Sánchez-Conde, Alejandra Aguirre-Santaella

Published 2026-03-24

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CC BY 4.0

Original authors: Sara Porras-Bedmar, Miguel Á. Sánchez-Conde, Alejandra Aguirre-Santaella

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

Imagine the Milky Way galaxy not just as a giant spinning disk of stars, but as a bustling city. In this city, the "stars" we see are the skyscrapers and bright lights. But according to our best theories of the universe, there is also a massive, invisible "fog" called Dark Matter that makes up most of the city's weight.

This invisible fog isn't just a smooth blanket; it's clumpy. It's filled with tiny, invisible islands called subhalos. Some of these islands are huge, but many are tiny, like pebbles or even dust motes. Scientists are desperate to find these tiny islands because if Dark Matter is made of certain particles (called WIMPs), they might bump into each other and vanish, releasing a burst of gamma-ray light. Finding these "ghostly" islands could finally solve the mystery of what Dark Matter is.

However, there's a problem: We can't see them directly.

The Problem: The "Resolution Limit"

To study these islands, astronomers use super-computer simulations. Think of these simulations like a high-definition video game. But even the best video games have a limit: if an object is too small (too few pixels), the game engine deletes it to save memory.

In the past, scientists ran simulations that only included the invisible Dark Matter (called DMO runs). These showed a galaxy packed with millions of tiny subhalos. But recent, more advanced simulations (called MHD runs) added "baryons"—the normal stuff we are made of, like gas, stars, and planets.

When they added the "normal stuff," something surprising happened: The number of tiny subhalos dropped by half. The presence of stars and gas seemed to be crushing the tiny dark islands, stripping them away like wind blowing sand off a dune.

The Experiment: "Repopulating" the Galaxy

The authors of this paper asked a crucial question: Did the tiny islands actually get destroyed by the stars, or did the computer just delete them because they were too small to see?

To answer this, they used a clever trick called "repopulation."

Imagine you have a photo of a forest, but the camera is too blurry to see the small saplings. You can't count them. So, you take the photo, analyze the big trees you can see, and then use a mathematical recipe to "draw in" all the missing saplings based on what you know about how forests grow.

The team did exactly this with the Auriga simulations:

They analyzed the "big" subhalos that the computer could actually see.
They used math to "repopulate" the galaxy with millions of tiny subhalos that were too small for the computer to resolve originally.
They tested two different scenarios for how these tiny islands survive the "wind" of the galaxy:
- The "Fragile" Scenario: The islands are like soap bubbles. If they get too close to the center of the galaxy (where the stars and gas are), the tidal forces crush them completely.
- The "Resilient" Scenario: The islands are like rocks. Even if the wind blows hard, the core of the rock survives. Maybe the computer thought they were destroyed, but in reality, they are just hiding in plain sight.

The Findings: Baryons Change Everything

The results were significant:

Baryons are the "Great Filter": When you include normal matter (stars/gas), the total number of subhalos drops significantly (by a factor of roughly 2). The galaxy is less "clumpy" than we thought if we only looked at Dark Matter.
The "Resilient" Hope: If the "Resilient" scenario is true (meaning the islands are tougher than the simulations suggest), then there are still plenty of tiny subhalos hiding near the center of our galaxy, close to Earth.
The "Fragile" Reality: If the "Fragile" scenario is true, the center of the galaxy is a graveyard for these islands. They are mostly gone, leaving us with fewer targets to search.

Why This Matters for Dark Matter Hunters

Scientists use telescopes (like the Fermi-LAT) to scan the sky for gamma rays, hoping to spot a "ghost" island. They need to know: How bright should these islands be? How many are there? Where are they likely to be?

Old View (DMO only): "There are billions of islands, and they are very bright. We should find them easily!"
New View (With Baryons): "Actually, there are fewer islands, and they are dimmer because the normal matter has stripped them down."

The paper shows that if you ignore the normal matter (stars and gas), you are overestimating how easy it is to find Dark Matter. You might be looking for a signal that isn't there, or setting your search parameters too loosely.

The Bottom Line

This paper is a reality check for the Dark Matter search. It tells us:

Don't ignore the "normal" stuff: You can't understand the invisible Dark Matter without understanding how it interacts with the visible stars and gas.
Adjust your search: If we are looking for these ghostly islands, we need to look in the right places and expect them to be dimmer than we previously thought.
The "Resilient" vs. "Fragile" debate: We still don't know if these tiny islands are soap bubbles or rocks. But by testing both, the authors have given scientists a better map of where to look, whether the islands are fragile or tough.

In short, the universe is a bit more complex and a bit more "empty" of these tiny dark islands than we hoped, but by understanding the role of normal matter, we are finally learning how to hunt for them properly.

1. Problem Statement

The search for Dark Matter (DM) via indirect detection (specifically gamma-rays from Weakly Interacting Massive Particle, or WIMP, annihilation) relies heavily on accurate models of the Galactic subhalo population.

The Resolution Limit: State-of-the-art cosmological simulations (like Auriga) are limited by numerical resolution, typically unable to resolve subhalos below $\sim 10^5 - 10^6 M_\odot$ . This creates an artificial cutoff in the subhalo mass function, missing the vast population of low-mass subhalos predicted by $\Lambda$ CDM cosmology.
The Baryon Effect: While Dark Matter Only (DMO) simulations have been used to estimate subhalo populations, they ignore baryonic physics (gas dynamics, star formation, feedback). Baryons deepen the gravitational potential of the host galaxy, potentially enhancing tidal stripping and disrupting subhalos more efficiently than in DMO scenarios. However, the extent of this disruption and the survival of low-mass subhalos in the presence of baryons remains debated.
The Uncertainty: It is unclear whether the lack of subhalos near the Galactic Center (GC) in simulations is due to physical tidal disruption or numerical artifacts. This uncertainty directly impacts the calculation of the "J-factor" (the integral of DM density squared), which determines the sensitivity of DM searches.

2. Methodology

The authors utilize the Auriga simulation suite, which provides a unique set of "zoom-in" cosmological simulations of Milky Way-like galaxies with both Magnetohydrodynamic (MHD) runs (including baryons) and Dark Matter Only (DMO) counterparts starting from identical initial conditions.

Key Steps:

Characterization of Resolved Data: The authors analyze the subhalo population in the "Level 3" resolution of Auriga ( $z=0$ $z = 0$ ) for both DMO and MHD runs. They characterize three independent components:
- Subhalo Velocity Function (SHVF): The number of subhalos as a function of maximum circular velocity ( $V_{max}$ ).
- Subhalo Radial Distribution (SRD): The spatial distribution of subhalos relative to the host center.
- Velocity Concentration ( $c_V$ ): A measure of subhalo internal structure defined by $V_{max}$ and the radius at which it occurs ( $R_{max}$ ).
Repopulation Algorithm: To overcome resolution limits, they employ a repopulation algorithm (adapted from Aguirre-Santaella & Sánchez-Conde) to generate millions of low-mass subhalos ( $V_{max} \in [0.1, 120]$ $V_{ma x} \in [0.1, 120]$ km/s) below the simulation's resolution limit.
- They extrapolate the SHVF, SRD, and $c_V$ relations derived from the resolved data down to $V_{max} = 0.1$ km/s.
Agnostic Scenarios: Since the physical survival of low-mass subhalos in the inner galaxy is uncertain, they test four distinct scenarios combining:
- Physics: DMO vs. MHD (Baryons).
- Resilience:
  - Fragile: Subhalos are disrupted as the simulations suggest (SRD drops to zero near the GC).
  - Resilient: Subhalos survive tidal forces despite numerical resolution limits (SRD remains constant or non-zero near the GC).
Gamma-Ray Constraints: They calculate the J-factors for the brightest subhalos in 500 independent repopulations per scenario. They then rescale existing WIMP annihilation cross-section constraints (specifically from Coronado-Blázquez et al. 2022, "CB22") to assess how including baryons and varying resilience affects the limits.

3. Key Contributions

First MHD Repopulation: This is the first study to extend the subhalo repopulation technique to high-resolution MHD simulations, incorporating baryonic effects into the prediction of the low-mass subhalo population.
Quantification of Baryonic Suppression: The study provides precise factors by which baryons reduce the subhalo population and alter their structural properties compared to DMO runs.
Dual-Scenario Analysis: By explicitly modeling both "fragile" and "resilient" subhalo populations, the authors bracket the systematic uncertainties regarding tidal disruption, providing a range of possible outcomes for DM searches.
Updated J-Factor Distributions: The paper derives new J-factor distributions for the brightest subhalos in MHD environments, which are critical for setting indirect detection limits.

4. Key Results

A. Impact of Baryons on Subhalo Population:

Abundance: The inclusion of baryons (MHD) significantly reduces the total number of subhalos. The normalization of the SHVF in MHD is lower than in DMO by a factor of $\sim 2.4$ (fragile) and $\sim 1.9$ (resilient).
Concentration: Subhalos in MHD runs are less concentrated than in DMO runs. The velocity concentration normalization ( $c_0$ ) in DMO is $\sim 1.5$ times higher than in MHD. This is attributed to the deeper potential well of the host galaxy in MHD runs, which strips outer material more efficiently.
Radial Distribution: In MHD runs, the closest surviving subhalo to the Galactic Center is significantly further away ( $\sim 15.7$ kpc) compared to DMO ( $\sim 5.6$ kpc).

B. J-Factor and Brightness:

Overall Brightness: Due to lower concentrations and reduced abundance, the J-factors ( $J_S$ $J_{S}$ ) of the brightest subhalos in MHD scenarios are lower than in DMO.
- In the fragile scenario, MHD J-factors are 0.80 dex (factor $\sim 6.3$ ) lower than DMO.
- In the resilient scenario, MHD J-factors are 0.48 dex (factor $\sim 3$ ) lower than DMO.
Resilience Effect: Resilient subhalos (those surviving near the GC) have significantly higher J-factors than fragile ones because proximity to Earth ( $D_{Earth}$ $D_{E a r t h}$ ) dominates the J-factor calculation.
- Resilient MHD subhalos boost the probability of finding a bright subhalo within 10 kpc of the GC by a factor of $\sim 2550$ compared to the fragile MHD scenario.
- In the resilient MHD scenario, 2% of the brightest subhalos have $V_{max} < 1$ km/s, making them potentially detectable despite their low mass, provided they are close to Earth.

C. Implications for Dark Matter Constraints:

WIMP Cross-Section Limits: The study recalculates constraints on the WIMP annihilation cross-section ( $\langle \sigma v \rangle$ $⟨ σ v ⟩$ ) based on the new J-factors.
- Including baryons (MHD) worsens (weakens) the constraints by a factor of $\sim 3.6$ (fragile) and $\sim 1.6$ (resilient) compared to DMO.
- Assuming resilient subhalos improves constraints (makes them tighter) by factors of $\sim 4.5$ (DMO) and $\sim 10$ (MHD) compared to their fragile counterparts.
Thermal Relic Limit: The tightest constraints (DMO Resilient) reach the thermal relic cross-section ( $\langle \sigma v \rangle_{th}$ ) at $m_\chi \sim 10$ GeV. However, the more realistic MHD Resilient scenario only reaches this limit at $m_\chi \sim 6$ GeV (for the $\tau^+\tau^-$ channel), indicating that current limits are less constraining when baryons are included.

5. Significance and Conclusion

This paper demonstrates that ignoring baryonic physics leads to an overestimation of the Galactic subhalo population and an overly optimistic assessment of indirect DM detection prospects.

Realism: MHD simulations provide a more realistic characterization of the subhalo population, showing that baryons significantly suppress the number and concentration of subhalos.
Search Strategy: The results imply that search strategies for dark satellites must account for the "resilience" of subhalos. If subhalos are fragile, the inner Galaxy is largely empty of dark substructure, pushing searches to larger radii. If they are resilient, the inner Galaxy could host numerous bright, low-mass subhalos.
Systematic Uncertainties: The authors highlight that the level of subhalo resilience is a major source of systematic uncertainty. Future work must focus on resolving the physical mechanisms of tidal disruption to distinguish between numerical artifacts and true physical suppression.
Broader Impact: Beyond gamma-ray searches, these findings are crucial for other DM detection methods, such as analyzing gaps in stellar streams and strong gravitational lensing, where the subhalo population properties dictate the expected signal signatures.

In summary, the inclusion of baryons and a careful treatment of subhalo resilience are essential for accurately interpreting null results in DM searches and for setting robust constraints on WIMP properties.