A constrained linear model for continuum normalization of stellar spectra
Andrew R. Casey, Adam Wheeler, Megan Bedell, David W. Hogg, Andrew Sayjdari, Lily Zhao

TL;DR
This paper introduces a constrained linear model for continuum normalization in stellar spectra that efficiently fits multiple nuisances simultaneously, improving consistency and accuracy without requiring initial guesses.
Contribution
The proposed model factorizes theoretical spectra into basis components, enabling fast, convex inference that jointly models stellar absorption, telluric transmission, and continuum effects.
Findings
Achieves 0.2% consistency across time for high S/N spectra
Performs better than existing methods at lower S/N levels
Demonstrates robustness on ESO/HARPS spectra of various star types
Abstract
Inferring stellar parameters and chemical abundances by forward modeling stellar spectra usually requires a spectral synthesis code, or an emulator constructed from a curated training set. In these situations continuum normalization is often implemented as a pre-processing step that is independent of stellar parameters. This leads to results that are biased, or inconsistent across signal-to-noise ratios. A more justified approach is to forward model spectra with all nuisances simultaneously, but in practice this can be an expensive or non-convex optimization procedure. Here we describe a constrained linear model that can fit stellar absorption, telluric transmission, the joint continuum-instrument response. Stellar absorption and telluric transmission are each modeled by factorizing a grid of rectified theoretical spectra into two non-negative matrices with a chosen number of basis…
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Taxonomy
TopicsStellar, planetary, and galactic studies · Astronomy and Astrophysical Research · Scientific Research and Discoveries
