Antideuteron fluxes from dark matter annihilation in diffusion models
Fiorenza Donato (U. Torino, INFN/Torino), Nicolao Fornengo (U., Torino, INFN/Torino), David Maurin (LPNHE, CNRS-IN2P3/Universite' Paris VI, et VII)

TL;DR
This paper provides an updated calculation of antideuteron fluxes from dark matter annihilation using a diffusion model, highlighting the potential of upcoming experiments to detect dark matter signals amidst astrophysical uncertainties.
Contribution
It introduces a novel two-zone diffusion model for antideuteron flux calculation, incorporating comprehensive uncertainties and assessing detection prospects for future experiments.
Findings
Secondary fluxes are well constrained with current models.
Propagation uncertainties significantly affect primary flux predictions.
Future experiments could detect signals from low to intermediate mass WIMPs.
Abstract
Antideuterons are among the most promising galactic cosmic ray-related targets for dark matter indirect detection. Currently only upper limits exist on the flux, but the development of new experiments, such as GAPS and AMS-02, provides exciting perspectives for a positive measurement in the near future. In this Paper, we present a novel and updated calculation of both the secondary and primary antideuteron fluxes. We employ a two-zone diffusion model which successfully reproduces cosmic-ray nuclear data and the observed antiproton flux. We review the nuclear and astrophysical uncertainties and provide an up to date secondary (i.e. background) antideuteron flux. The primary (i.e. signal) contribution is calculated for generic WIMPs annihilating in the galactic halo: we explicitly consider and quantify the various sources of uncertainty in the theoretical evaluations. Propagation…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
