On the origin of sinusoidal brightness variations in F to O-type stars through radial velocities

TL;DR

This study investigates the origins of sinusoidal brightness variations in hot main-sequence stars, revealing that at least half are binaries, and emphasizes the importance of combined photometric and spectroscopic analysis for accurate classification.

Contribution

The paper provides a comprehensive spectroscopic follow-up of TESS data, identifying new binary systems, pulsators, and spotted stars among hot stars with sinusoidal brightness variations.

Findings

Half of the sinusoidally variable stars are binaries.

Discovered 7 new binary systems and 1 triple-star candidate.

Highlights the need for combined photometric and spectroscopic analysis.

Abstract

Stellar variability may originate from various phenomena such as binarity, pulsations, or rotation. These mechanisms can induce flux variations of similar magnitudes, shapes, and periods. We aim to determine mechanisms responsible for the sinusoidal variations in main-sequence stars hotter than 6500 K. We conducted our analysis using TESS long-cadence data complemented with high-resolution spectra from three spectrographs. From the initial sample of almost 46000 objects, we selected 35 targets for spectroscopic follow-up. Comparison of light curves and radial velocity curves allowed for robust classification of these targets. Among the 35 selected objects, 18 displayed variability, suggesting the presence of a companion (including the discovery of 7 new binary systems and 1 candidate for a triple-star system), 1 was identified as a new pulsator, 9 as new candidates for spotted stars, and 7 objects had uncertain classification. Our analysis shows that at least half of randomly selected stars with sinusoidal brightness variations are binaries. The presented results illustrate the need for an individual approach to stellar classification, especially in cases where the photometric data alone is insufficient for determining the underlying phenomena behind the observed variations.