Stellar atmosphere parameters with MAx, a MAssive compression of x^2 for spectral fitting

TL;DR

MAx is a new spectral fitting tool that compresses likelihood information to efficiently estimate stellar parameters with high accuracy, suitable for large spectral surveys.

Contribution

It introduces a likelihood compression method that conserves information, enabling faster and scalable stellar parameter estimation from spectral data.

Findings

Achieved parameter estimation accuracies of 0.24 dex for metallicity, 130K for temperature, and 0.5 dex for gravity.

Demonstrated good agreement with SEGUE pipeline results on low-resolution spectra.

Validated performance on high-resolution spectra with classical methods.

Abstract

MAx is a new tool to estimate parameters from stellar spectra. It is based on the maximum likelihood method, with the likelihood compressed in a way that the information stored in the spectral fluxes is conserved. The compressed data are given by the size of the number of parameters, rather than by the number of flux points. The optimum speed-up reached by the compression is the ratio of the data set to the number of parameters. The method has been tested on a sample of low-resolution spectra from the Sloan Extension for Galactic Understanding and Exploration (SEGUE) survey for the estimate of metallicity, effective temperature and surface gravity, with accuracies of 0.24 dex, 130K and 0.5 dex, respectively. Our stellar parameters and those recovered by the SEGUE Stellar Parameter Pipeline agree reasonably well. A small sample of high-resolution VLT-UVES spectra were also used to test the method and the results have been compared to a more classical approach. The speed and multi-resolution capability of MAx combined with its performance compared with other methods indicates that it will be a useful tool for the analysis of upcoming spectral surveys.