Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 88 tok/s
Gemini 2.5 Pro 47 tok/s Pro
GPT-5 Medium 21 tok/s Pro
GPT-5 High 13 tok/s Pro
GPT-4o 81 tok/s Pro
Kimi K2 175 tok/s Pro
GPT OSS 120B 450 tok/s Pro
Claude Sonnet 4 39 tok/s Pro
2000 character limit reached

Constraints on the Dark Matter Particle Mass from the Number of Milky Way Satellites (1004.1459v3)

Published 9 Apr 2010 in astro-ph.CO and hep-ph

Abstract: We have conducted N-body simulations of the growth of Milky Way-sized halos in cold and warm dark matter cosmologies. The number of dark matter satellites in our simulated Milky Ways decreases with decreasing mass of the dark matter particle. Assuming that the number of dark matter satellites exceeds or equals the number of observed satellites of the Milky Way we derive lower limits on the dark matter particle mass. We find with 95% confidence m_s > 13.3 keV for a sterile neutrino produced by the Dodelson and Widrow mechanism, m_s > 8.9 keV for the Shi and Fuller mechanism, m_s > 3.0 keV for the Higgs decay mechanism, and m_{WDM} > 2.3 keV for a thermal dark matter particle. The recent discovery of many new dark matter dominated satellites of the Milky Way in the Sloan Digital Sky Survey allows us to set lower limits comparable to constraints from the complementary methods of Lyman-alpha forest modeling and X-ray observations of the unresolved cosmic X-ray background and of dark matter halos from dwarf galaxy to cluster scales. Future surveys like LSST, DES, PanSTARRS, and SkyMapper have the potential to discover many more satellites and further improve constraints on the dark matter particle mass.

Citations (149)

Summary

We haven't generated a summary for this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Don't miss out on important new AI/ML research

See which papers are being discussed right now on X, Reddit, and more:

“Emergent Mind helps me see which AI papers have caught fire online.”

Philip

Philip

Creator, AI Explained on YouTube