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

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 characterizing 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 by 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 impossible, we present a simplified model and the necessary python tools to analyze any potential binary system. Finally, we propose using blackbody models as a baseline for error estimation in SED fitting. We offer a possible method for measuring fitting errors and improving the precision of binary star characterizations.