Markov Chain Monte Carlo Optimization applied to Dyson’s Visual Double Stars

Volume 51 number 2 (2023)

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Isabella Soh Xiao Si

Department of Statistics and Data Science, National University of Singapore, Blk S16, Level 7, 6 Science Drive 2, Singapore 117546

Michael D. Rhodes

Brigham Young University, Provo, Utah 84602

Edwin Budding

Carter Observatory, 40 Salamanca Road, Kelburn, Wellington 6012, New Zealand, and School of Chemical and Physical Sciences, Victoria University of Wellington, P.O. Box 600, Wellington 6140, New Zealand

Timothy Banks

Department of Physical Science and Engineering, Harper College, 1200 W Algonquin Road, Palatine, IL 60067, and Data Science, Nielsen, 200 W Jackson, Chicago, IL 60606; corresponding author, tim.banks@nielsen.com

Abstract

Estimates of orbital parameters were made using a Bayesian optimization technique on astrometric data for 25 visual binary systems catalogued a century ago by the ninth Astronomer Royal, Sir Frank Dyson. An advantage of this method is that it provides reliable, unbiased uncertainty estimates for the optimized parameters. Reasonable agreement is found for the short period (< 100 yr) systems between the current study and Dyson, with superior estimation for the longer systems through the inclusion of an additional century of data. Dynamical masses are presented for the systems through the inclusion of parallax measurements.