The Massive Binary System 9 Sgr Revisited: New Insights into Disentangling Methods

TL;DR

This paper introduces QER20, a new disentangling method that improves spectral analysis of binary stars, leading to more accurate classifications and resolving issues in previous algorithms.

Contribution

The paper presents QER20, a novel disentangling package that reduces errors and enhances performance over the traditional MME98 algorithm for analyzing binary star spectra.

Findings

QER20 yields different line fluxes compared to previous methods.

Revised spectral classifications for 9 Sgr to earlier subtypes.

QER20 eliminates classification errors present in MME98.

Abstract

Disentangling techniques are often needed to obtain the spectra of the individual components of binary or multiple systems. A thorough analysis of the shift-and-add algorithm of Marchenko, Moffat, & Eenens (1998) reveals that in many cases the line fluxes are poorly reproduced and spurious wings appear. The causes of these discrepancies are discussed and a new disentangling package, QER20, is presented which significantly reduces these errors and vastly increases the performance. When applied to the massive binary 9 Sgr, our new code yields line fluxes which are notably different from those previously published and lead us to revise the spectral classification to slightly earlier subtypes: O3V((f +)) for the primary and O5V((f)) for the secondary. We show that with the MME98 algorithm the classification of massive stars in binaries can be off by several subtypes whilst there are no such errors when the QER20 package is used.