PySSED: an automated method of collating and fitting stellar spectral energy distributions

TL;DR

PySSED is an automated Python tool that combines photometric data from various sources to efficiently fit stellar spectral energy distributions and identify deviations from models across large datasets.

Contribution

The paper introduces PySSED, a fully automated routine for collating photometry and fitting stellar SEDs, enabling rapid analysis of large astronomical datasets.

Findings

Automates the process of fitting stellar spectral energy distributions.

Capable of analyzing large datasets within seconds per star.

Identifies deviations from stellar atmosphere models such as IR or UV excess.

Abstract

Stellar atmosphere modelling predicts the luminosity and temperature of a star, together with parameters such as the effective gravity and the metallicity, by reproducing the observed spectral energy distribution. Most observational data comes from photometric surveys, using a variety of passbands. We herein present the Python Stellar Spectral Energy Distribution (PySSED) routine, designed to combine photometry from disparate catalogues, fit the luminosity and temperature of stars, and determine departures from stellar atmosphere models such as infrared or ultraviolet excess. We detail the routine's operation, and present use cases on both individual stars, stellar populations, and wider regions of the sky. PySSED benefits from fully automated processing, allowing fitting of arbitrarily large datasets at the rate of a few seconds per star.