Velocity Curve Analysis of the Spectroscopic Binary Stars V373 Cas, V2388 Oph, V401 Cyg, GM Dra, V523 Cas, AB And, and HD 141929 by Artificial Neural Networks

TL;DR

This paper employs artificial neural networks to determine orbital parameters of seven spectroscopic binary stars from radial velocity data, demonstrating that ANN can produce results consistent with traditional methods.

Contribution

The study introduces the use of ANN for deriving orbital parameters of spectroscopic binaries, offering an alternative to conventional techniques.

Findings

ANN-derived orbital parameters agree with traditional methods.

ANN effectively analyzes radial velocity data for multiple binary systems.

Method provides a new tool for spectroscopic binary analysis.

Abstract

We used an Artificial Neural Network (ANN) to derive the orbital parameters of spectroscopic binary stars. Using measured radial velocity data of seven double-lined spectroscopic binary systems V373 Cas, V2388 Oph, V401 Cyg, GM Dra, V523 Cas, AB And, and HD 141929, we found corresponding orbital and spectroscopic elements. Our numerical results are in good agreement with those obtained by others using more traditional methods.