Shunichi Horigome

I'm a researcher in astrophysics working on dark matter detection and the analysis of dwarf spheroidal galaxies. My work focuses on developing novel computational methods to understand dark matter halos and their observational signatures, particularly through stellar kinematics and J-factor estimation. My research spans both theoretical and observational aspects of dark matter physics. I have extensive experience in developing statistical methods for analyzing stellar data from dwarf galaxies, with particular attention to addressing contamination from foreground stars and improving the robustness of dark matter density profile reconstructions. Recently, I've been working on machine learning approaches to solve the spherical Jeans equation in a model-independent way, using equivariant continuous normalizing flows to estimate stellar phase space densities without relying on traditional parametric models. I'm also deeply involved in constraining self-interacting dark matter models using kinematic observations of Milky Way satellite galaxies. My work includes developing semi-analytical frameworks like SASHIMI-SIDM that can efficiently model subhalo populations across different dark matter scenarios. Additionally, I investigate particle physics aspects of dark matter, particularly leptophilic WIMP models and their detectability at future collider experiments. Through combining cosmological modeling with observational data analysis, I aim to advance our understanding of dark matter's nature and distribution on galactic and sub-galactic scales.