[Paper Review] Snowmass2021 Cosmic Frontier White Paper: Prospects for obtaining Dark Matter Constraints with DESI

Monica Valluri, Solene Chabanier+30 more|arXiv (Cornell University)|Mar 14, 2022

Dark Matter and Cosmic Phenomena4 citations

TL;DR

This paper proposes that the Dark Energy Spectroscopic Instrument (DESI) can significantly improve constraints on dark matter properties through wide-field spectroscopic surveys of the Ly-α forest and Milky Way stellar velocities. By combining DESI data with large-scale cosmological simulations and emulators, it enables precision constraints on alternative dark matter models—such as warm, self-interacting, or fuzzy dark matter—beyond standard cold dark matter.

ABSTRACT

Despite efforts over several decades, direct-detection experiments have not yet led to the discovery of the dark matter (DM) particle. This has led to increasing interest in alternatives to the Lambda CDM (LCDM) paradigm and alternative DM scenarios (including fuzzy DM, warm DM, self-interacting DM, etc.). In many of these scenarios, DM particles cannot be detected directly and constraints on their properties can ONLY be arrived at using astrophysical observations. The Dark Energy Spectroscopic Instrument (DESI) is currently one of the most powerful instruments for wide-field surveys. The synergy of DESI with ESA's Gaia satellite and future observing facilities will yield datasets of unprecedented size and coverage that will enable constraints on DM over a wide range of physical and mass scales and across redshifts. DESI will obtain spectra of the Lyman-alpha forest out to z~5 by detecting about 1 million QSO spectra that will put constraints on clustering of the low-density intergalactic gas and DM halos at high redshift. DESI will obtain radial velocities of 10 million stars in the Milky Way (MW) and Local Group satellites enabling us to constrain their global DM distributions, as well as the DM distribution on smaller scales. The paradigm of cosmological structure formation has been extensively tested with simulations. However, the majority of simulations to date have focused on collisionless CDM. Simulations with alternatives to CDM have recently been gaining ground but are still in their infancy. While there are numerous publicly available large-box and zoom-in simulations in the LCDM framework, there are no comparable publicly available WDM, SIDM, FDM simulations. DOE support for a public simulation suite will enable a more cohesive community effort to compare observations from DESI (and other surveys) with numerical predictions and will greatly impact DM science.

Motivation & Objective

• To leverage DESI’s wide-field spectroscopy to constrain non-cold dark matter models using astrophysical observables.
• To address the lack of publicly available simulations for alternative dark matter scenarios like warm (WDM), self-interacting (SIDM), and fuzzy dark matter (FDM).
• To improve statistical precision in dark matter constraints by combining DESI data with high-resolution hydrodynamical simulations and emulator techniques.
• To enable joint inference of cosmological and astrophysical parameters by modeling feedback and reionization effects via post-processing analytical corrections.
• To advocate for DOE funding of a public simulation suite to support community-wide comparison of dark matter models.

Proposed method

• Use DESI’s survey of ~1 million Ly-α forest spectra at z ≲ 5 to probe clustering of low-density intergalactic gas and infer dark matter properties.
• Combine DESI radial velocities of ~10 million Milky Way and Local Group stars with Gaia astrometry to constrain the global dark matter distribution and subhalo mass function.
• Construct grids of ~10 high-resolution hydrodynamical simulations with simplified astrophysics to model IGM response to cosmological parameters, including dark matter nature.
• Develop fast interpolation schemes (emulators) trained on simulated grids to enable efficient posterior inference over millions of parameter combinations.
• Apply analytical corrections derived from auxiliary full galaxy formation simulations to account for star formation and AGN feedback effects on Ly-α statistics.
• Integrate DESI data with future facilities (e.g., Roman Space Telescope, LSST) to extend constraints across redshifts and mass scales.

Experimental results

Research questions

• RQ1 How can DESI’s Ly-α forest data improve constraints on the mass and interaction cross-section of non-cold dark matter candidates like WDM or FDM?
• RQ2 To what extent can stellar velocity measurements from DESI and Gaia constrain the subhalo mass function and dark matter distribution in the Milky Way halo?
• RQ3 What level of simulation fidelity is required to accurately model the IGM’s response to dark matter physics while accounting for astrophysical feedback?
• RQ4 Can emulator-based inference techniques enable precise cosmological parameter estimation from DESI’s large-scale spectroscopic data?
• RQ5 How can a publicly available simulation suite for alternative dark matter models accelerate community-wide progress in dark matter research?

Key findings

• DESI’s Ly-α forest survey will obtain four times more quasar spectra than previous surveys, yielding ~1 million spectra and enabling tighter constraints on low-density IGM clustering.
• The combination of DESI radial velocities and Gaia astrometry will allow precise mapping of the Milky Way’s dark matter halo and subhalo population down to low masses.
• Grids of ~10 high-resolution hydrodynamical simulations with simplified astrophysics are sufficient to model the dependence of the Ly-α forest power spectrum on cosmological parameters, including dark matter nature.
• Emulators trained on these simulation grids can efficiently interpolate between model outcomes, enabling posterior inference over millions of parameter combinations with only tens of full simulations.
• Analytical corrections derived from auxiliary full-physics simulations can account for feedback effects on Ly-α statistics without requiring full re-simulation for each parameter set.
• A next-generation DESI survey could simultaneously address dark energy and dark matter science goals by expanding quasar and stellar velocity surveys to improve statistical precision.