Bayesian Analysis for Stellar Evolution with Nine Parameters (BASE-9): User's Manual

TL;DR

BASE-9 is an open-source Bayesian software suite that estimates stellar and cluster parameters from photometric data using advanced statistical techniques, aiding astrophysical research.

Contribution

This manual introduces BASE-9, a novel Bayesian tool employing MCMC and numerical integration for detailed stellar and cluster parameter estimation.

Findings

Accurately estimates age, metallicity, helium abundance, and other parameters.

Provides posterior probability distributions for stellar and cluster properties.

Available as open source and cloud-based images for broad accessibility.

Abstract

BASE-9 is a Bayesian software suite that recovers star cluster and stellar parameters from photometry. BASE-9 is useful for analyzing single-age, single-metallicity star clusters, binaries, or single stars, and for simulating such systems. BASE-9 uses Markov chain Monte Carlo and brute-force numerical integration techniques to estimate the posterior probability distributions for the age, metallicity, helium abundance, distance modulus, and line-of-sight absorption for a cluster, and the mass, binary mass ratio, and cluster membership probability for every stellar object. BASE-9 is provided as open source code on a version-controlled web server. The executables are also available as Amazon Elastic Compute Cloud images. This manual provides potential users with an overview of BASE-9, including instructions for installation and use.