Exponential Enhancement of Dark Matter Freezeout Abundance

TL;DR

This paper introduces 'bouncing dark matter,' a new thermal dark matter paradigm where the abundance can increase exponentially during freezeout, potentially enhancing indirect detection prospects.

Contribution

It presents a novel class of thermal dark matter models where the abundance can deviate from the standard exponential decline, including exponential growth during freezeout.

Findings

Dark matter abundance can rise exponentially in certain models.

Enhanced annihilation cross sections improve indirect detection prospects.

Broader class of thermal DM models beyond canonical scenarios.

Abstract

A novel paradigm for thermal dark matter (DM), termed "bouncing dark matter", is presented. In canonical thermal DM scenarios, the DM abundance falls exponentially as the temperature drops below the mass of DM, until thermal freezeout occurs. This note explores a broader class of thermal DM models that are exceptions to this rule, where the DM abundance can deviate from the exponentially falling curve, and even rise exponentially, while in thermal equilibrium. Such scenarios can feature present day DM annihilation cross sections much larger than the canonical thermal target, improving the prospects for indirect detection of DM annihilation signals.