Application of Probability Theory to the Identification and Analysis of Binary Star Systems

Mathematics – Probability

Scientific paper

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Scientific paper

Accurate identification of physical binary star systems has become of increasing interest in recent years. The frequency of occurrence of binary and multiple star systems remains uncertain at the present time, and is a stumbling block to our understanding of the formation of stars, stellar systems, and planetary systems. Identification of physical binary star systems, with an estimated reliability of such identifications based on the theory of probability, is also important for current and future efforts to identify binary star systems that are candidates for future observations which aim to determine their orbits and components masses. In this paper I shall present methods and algorithms which allow the identification of physical binary stars in a probabilistic sense. The application of probability theory provides a more complete picture of the frequency of stellar binarity than simple methods based only on proximity or proper motion. Identification of physical binary systems: 1. The probability that two stars in a binary system randomly have similar proper motions, and, therefore, are an apparent binary may be expressed as the product of the probability distributions in angular separation, proper motion, and magnitude differential. 2. The probability function may be explicitly defined using the real an observed distribution of stars in proper motion: source - some catalogue (PPM for example) 3. Catalogs of known physical and apparent binaries yield the criterion for identification, and allow selection between likely physical binaries and likely apparent binaries in some sample of interest. 4. The most sensitive selector for true physical binaries is found to be proper motion. I will demonstrate the application of this method to specific samples of potential binary stars, and outline how such methods might be applied to present and future high precision astrometric catalogues.

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