Matthew Ho

Researchers enhance galaxy studies through simulation-based inference methods for better accuracy.

A new pipeline integrates machine learning methods in astrophysics for better analysis.

This study examines how metallicity affects star formation rates and interstellar medium behavior.

Innovative approach connects N-body simulations to accurate galaxy counts efficiently.

Researchers develop CHARM for faster galaxy distribution analysis using dark matter data.

A look at how stars reveal the universe's mysteries through light and color.

RTFAST speeds up black hole research, offering new insights into cosmic mysteries.