paper

On the detectability and parameterisation of binary stars through spectral energy distributions

arXiv:2412.05606 · doi:10.1007/s12036-025-10042-2

Abstract

This study examines the characterization of binary star systems using Spectral Energy Distributions (SEDs), a technique increasingly essential with the rise of large-scale astronomical surveys. Binaries can emit flux at different regions of the electromagnetic spectrum, making SEDs a valuable tool in identifying and characterising unresolved binary systems. However, fitting multi-component models to SEDs and recovering accurate stellar parameters remains challenging due to nonlinear fitting methods and inherent uncertainties in the data and the spectral models. In this work, a simplified approach was used to model stars as blackbodies and we tested the accuracy of parameter recovery from SEDs, particularly focusing on secondary stars. We explored a range of primary properties, filter sets and noise models. Special attention was given to two case studies: one examining the detection of unresolved binaries using Gaia XP spectra, and the other focusing on identifying hotter companions in binary systems using UV-IR SEDs. Although an analytic prescription for recoverability is not possible, we present a simplified model and the necessary Python tools to analyse any potential binary system. Finally, we propose using blackbody models as a baseline for error estimation in SED fitting, offering a potential method for measuring fitting errors and improving the precision of binary star characterisations.

Accepted to Journal of Astrophysics & Astronomy. sed-analysis-tools is available on GitHub https://github.com/jikrant3/sed-analysis-tools/

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