# Semi-analytic Inference of Dwarf Galaxy Densities and Implications for Dark Matter Searches

- Institution: CERN
- Speaker: Kailash Raman
- Year: 2026
- Language: English
- Source: [CERN](https://videos.cern.ch/record/3026522)
- Licence: [CERN](https://copyright.web.cern)
- Who can watch: Teens profiles and older (sources give no ratings; placed by Invisible Network from the source's own words)

Ultra-faint dwarf galaxies are critical testing grounds for the particle nature of dark matter. In this talk, I will present Milky Way dwarf density profiles inferred using a semi-analytic satellite generator that captures the Cold Dark Matter (CDM) halo population. We match halos to dwarfs via two criteria: a kinematic selection (using enclosed mass at the half-light radius) and a stellar-mass selection (via a galaxy formation model). The kinematic selection yields larger diversity in central densities than CDM predicts—the most compact ultra-faints are denser, the most diffuse less dense—a discrepancy robust to all systematic variations explored. I will also present updated astrophysical $J$-factors using the latest kinematic data. We find that observed Milky Way satellites set stronger annihilation constraints than a typical Milky Way–mass system, excluding a thermal relic cross section for annihilation to $b\bar{b}$ below 173 GeV at 95% confidence. A completeness analysis suggests future ultra-faint discoveries are unlikely to substantially strengthen these limits.

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## Lectures

1. [Semi-analytic Inference of Dwarf Galaxy Densities and Implications for Dark Matter Searches](https://invisiblenetwork.ai/learn/cern/3026522/536e0a01c886), 10 min (CERN's player)