Automated procedure to derive fundamental parameters of B and A stars: Application to the young cluster NGC 3293

TL;DR

This paper presents a Python-based automated method to determine fundamental stellar parameters of B and A stars using synthetic spectra fitting, applied to NGC 3293 cluster data, achieving high accuracy in temperature and gravity measurements.

Contribution

The paper introduces a new automated spectral fitting procedure combining LTE models and synthetic spectra to derive stellar parameters efficiently.

Findings

Achieved ±200 K accuracy in effective temperature.

Achieved ±0.2 dex accuracy in surface gravity.

Validated results against previous studies with good agreement.

Abstract

This work describes a procedure to derive several fundamental parameters such as the effective temperature, surface gravity, equatorial rotational velocity and microturbulent velocity. In this work, we have written a numerical procedure in Python which finds the best fit between a grid of synthetic spectra and the observed spectra by minimizing a standard chi-square. LTE model atmospheres were calculated using the ATLAS9 code and were used as inputs to the spectrum synthesis code SYNSPEC48 in order to compute a large grid of synthetic Balmer line profiles. This new procedure has been applied to a large number of new observations (GIRAFFE spectra) of B and A stars members of the young open cluster NGC3293. These observations are part of the GAIA ESO Survey. Takeda's procedure was also used to derive rotational velocities and microturbulent velocities. The results have been compared to previous determinations by other authors and are found to agree with them. As a first result, we concluded that using this procedure, an accuracy of +-200 K could be achieved in effective temperature and +-0.2 dex in surface gravities.