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Bayesian Analysis for Stellar Evolution with Nine Parameters (BASE-9): User's Manual
Publications
  • Ted von Hippel, Embry-Riddle Aeronautical University
  • Elliot Robinson, Argiope Technical Solutions
  • Elizabeth Jeffery, Brigham Young University
  • Rachel Wagner-Kaiser, University of Florida
  • Steven DeGennaro, Studio 42
  • Nathan Stein, University of Pennsylvania
  • David Stenning, University of California
  • William H. Jefferys, University of Texas
  • David van Dyk, Imperial College London
Submitting Campus
Daytona Beach
Department
Physical Sciences
Document Type
Article
Publication/Presentation Date
11-14-2014
Abstract/Description

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.

Citation Information
Ted von Hippel, Elliot Robinson, Elizabeth Jeffery, Rachel Wagner-Kaiser, et al.. "Bayesian Analysis for Stellar Evolution with Nine Parameters (BASE-9): User's Manual" (2014)
Available at: http://works.bepress.com/ted-vonhippel/38/