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[Paper Review] TASI Lectures on the Particle Physics and Astrophysics of Dark Matter

Benjamin R. Safdi|arXiv (Cornell University)|Mar 3, 2023
Dark Matter and Cosmic Phenomena5 citations
TL;DR

This paper provides a pedagogical overview of indirect probes of dark matter (DM) using particle physics and astrophysical observables, focusing on weakly interacting massive particles (WIMPs) and axions. It details theoretical frameworks, including the higgsino as a WIMP candidate and axion cosmology, and presents statistical methods for analyzing gamma-ray data—such as from the Fermi-LAT toward Segue I—highlighting the Fermi Galactic Center Excess as a key anomaly. The key contribution is a comprehensive, accessible toolkit for upcoming indirect DM searches using next-generation instruments like the Cherenkov Telescope Array.

ABSTRACT

These lecture notes on the particle physics and astrophysics of dark matter (DM) were delivered at TASI 2022 ``Ten Years After the Higgs Discovery: Particle Physics Now and Future." The focus of these lecture notes, aimed at the level of advanced graduate students and beginning postdocs, is on indirect (i.e., astrophysical and cosmological) probes of particle DM models. While DM models and indirect detection are broadly discussed, the examples of weakly interacting massive particles (WIMPs) and axions are worked out in detail. The topics covered include: the role of DM in the cosmology and astrophysics of structure formation, including DM density profiles in galaxies, general constraints on particle DM models, the theory of minimal DM, with the higgsino as a relevant and illustrative example, indirect detection with gamma-rays, including with the upcoming Cherenkov Telescope Array, axions as a solution to the strong-CP problem and a DM candidate, including discussions of possible ultraviolet completions and of axion string cosmology, and astrophysical probes of axions such as with isocurvature perturbations, $N_{ m eff}$, black hole superradiance, radio telescopes, spectral modulations, stellar polarization, and stellar cooling, amongst other topics. Example Jupyter notebooks are provided that walk the reader through relevant analyses, including an example statistical analysis of a DM annihilation search towards the Segue I dwarf galaxy with gamma-ray data from the Fermi Large Area Telescope that is relevant for DM explanations of the Fermi Galactic Center Excess. We also provide an introduction to frequentist statistics for particle and astro-particle physics. These lecture notes are meant to be pedagogical, with the focus on explaining the underlying physical principles and analysis techniques that are set to play crucial roles in the search for particle DM in the coming decade.

Motivation & Objective

  • To provide advanced graduate students and postdocs with a pedagogical foundation in indirect dark matter detection using astrophysical and cosmological observables.
  • To detail the theoretical and phenomenological frameworks for two leading DM candidates: WIMPs (especially the thermal higgsino) and axions.
  • To equip researchers with practical analysis techniques, including frequentist statistics and Jupyter notebook-based tools, for interpreting gamma-ray data from DM annihilation.
  • To explore the full range of astrophysical probes—such as black hole superradiance, stellar cooling, and isocurvature perturbations—that constrain DM models beyond direct and collider searches.

Proposed method

  • Uses effective field theory and quantum field theory to compute annihilation cross-sections for higgsino DM, including tree-level and one-loop processes.
  • Applies Mandelstam variables and trace technology to compute matrix elements for higgsino pair annihilation into W bosons and photons.
  • Derives the velocity-averaged annihilation cross-section ⟨σv⟩ for higgsino DM, showing it scales as g⁴/(512πmχ²) with tanθw dependence.
  • Integrates astrophysical constraints from structure formation, CMB, and X-ray observations to bound DM models.
  • Employs statistical analysis techniques, including frequentist hypothesis testing, to interpret Fermi-LAT data on the Galactic Center Excess.
  • Provides Jupyter notebooks that walk through real data analysis, such as a search for DM annihilation in the Segue I dwarf spheroidal galaxy.

Experimental results

Research questions

  • RQ1What is the velocity-averaged annihilation cross-section for higgsino dark matter into W bosons, and how does it compare to the observed relic density?
  • RQ2How do axion models resolve the strong-CP problem and simultaneously account for the observed dark matter abundance?
  • RQ3What are the key astrophysical signatures of axions, such as black hole superradiance and spectral modulations in stellar cooling?
  • RQ4Can the Fermi Galactic Center Excess be explained by higgsino DM annihilation, and what statistical significance does it achieve in gamma-ray data?
  • RQ5How do next-generation instruments like the Cherenkov Telescope Array enhance the sensitivity to indirect dark matter signals?

Key findings

  • The velocity-averaged annihilation cross-section for higgsino DM into W bosons is ⟨σv⟩ ≈ g⁴/(512πmχ²) × (21 + 3tan²θw + 11tan⁴θw), with the dominant contribution from χχ and χχ₊ annihilation.
  • The one-loop γγ final state for higgsino DM is suppressed but provides a distinctive indirect detection signal due to its monochromatic nature.
  • The higgsino, as a thermally produced WIMP, naturally achieves the correct relic density via freeze-out, making it a benchmark candidate for indirect detection.
  • Axion models are constrained by multiple astrophysical probes, including isocurvature perturbations, N_eff, and stellar cooling, which together limit the axion mass and coupling range.
  • The Fermi Galactic Center Excess remains a compelling but unconfirmed signal, with statistical analysis of Segue I data showing moderate significance under higgsino DM models.
  • The inclusion of Jupyter notebooks enables reproducible, end-to-end analysis of indirect detection data, bridging theory and observation for upcoming experiments.

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This review was created by AI and reviewed by human editors.