New Periodograms Separating Orbital Radial Velocities and Spectral Shape Variation

TL;DR

This paper introduces novel periodograms based on partial distance correlation to distinguish between orbital radial velocity signals and spectral shape variations in astronomical spectra, aiding the analysis of active stars and binaries.

Contribution

The paper develops new periodograms that effectively separate Doppler shifts from spectral shape variability, enhancing the analysis of complex spectroscopic data.

Findings

Demonstrated effectiveness through simulations

Validated with real-life case studies

Provided a publicly available Python implementation

Abstract

We present new periodograms that are effective in distinguishing Doppler shift from spectral shape variability in astronomical spectra. These periodograms, building upon the concept of partial distance correlation, separate the periodic radial velocity modulation induced by orbital motion from that induced by stellar activity. These tools can be used to explore large spectroscopic databases in search of targets in which spectral shape variations obscure the orbital motion; such systems include active planet-hosting stars or binary systems with an intrinsically variable component. We provide a detailed prescription for calculating the periodograms, demonstrate their performance via simulations and real-life case studies, and provide a public Python implementation.