Weighting the Model-Agnostic Dark Halo Analysis Tool: MADHAT v2.0

MADHAT (Model-Agnostic Dark Halo Analysis Tool) is a computational tool that uses processed data from Fermi Gamma-ray Space Telescope observations of dwarf galaxies and dwarf-like objects. MADHAT calculates the probability that some number of photons from each target object could be coming from non-standard astrophysics, including dark matter, and produces bounds on dark matter properties, such as the annihilation cross section or the decay rate. Unlike the majority of similar analyses, MADHAT can be used to constrain the number of dark-matter-produced photons coming from a set of dwarf galaxies for any model of dark matter particle physics or astrophysics. Here, I report on MADHAT v2.0, which includes a number of improvements relative to the original MADHAT package, including weighting photons based on their sky direction and making use of information in the energy spectrum of observed photons, both of which can improve sensitivity to dark matter models.