Tools for probing new physics with newly discovered gamma-ray targets

TL;DR

This paper introduces TweedleDEE, a computational tool for modeling gamma-ray backgrounds and searching for dark matter signals in new astrophysical targets, exemplified by the Leo VI dwarf galaxy.

Contribution

The paper presents a novel data-driven background modeling tool and a scaling relation for dark matter analysis, enabling new physics searches in gamma-ray data.

Findings

First dark matter search in Leo VI dwarf galaxy.

Constraints on dark matter annihilation channels and velocity dependence.

A scalable method for deriving J-factors from stellar parameters.

Abstract

We present a computational tool, TweedleDEE, for empirically modeling diffuse gamma-ray background emission in a 1 degree region of the sky, using publicly available gamma-ray data off-axis from the region of interest. This background model allows a user to perform a purely data-driven search for anomalous localized sources of gamma-ray emission, including new physics. A major application of this tool would be in searching for dark matter annihilation in newly discovered astrophysical targets. For this purpose, we derive a scaling relation for determining velocity-dependent $J$-factors using only the stellar parameters, which can be broadly applied to obtain dark matter constraints from new targets. As an application of these tools, we use TweedleDEE and MADHATv2 to perform the first search for dark matter annihilation in the newly discovered Leo VI dwarf spheroidal galaxy, and present model constraints for a variety of choices of the annihilation channel and velocity dependence of the cross section.