Speaker
Description
We present the code tonalli (“heat of the sun” in Náhuatl), a python implementation of an asexual GA (Cantó et al. 2009) to solve the optimization problem of finding the best-fit synthetic spectrum for a given APOGEE-2 observed spectrum, thus effectively obtaining the stellar parameters that best characterize the spectrum.
The observed spectrum is randomly and efficiently contrasted with an user-selected synthetic spectral library. The search parameter space, which depends on the limits of the synthetic spectral grid, can be constrained further by comparing the GAIA and 2MASS photometry of the star to the photometry from the PARSEC evolutionary models (Bressan et al 2012, Nguyen et al 2022); the photometry best-fit parameters become the input of tonalli.
From the minimization of the figure of merit, we derive the metallicity and the alpha-elements abundance, the surface gravity logarithm, the effective temperature, the projected rotational speed, and the radial velocity, with the option to optimize the limb darkening parameter. Our method allowed us to improve the characterization of the young stellar APOGEE-2 spectra, and the framework can be readily translated to combine infrared and optical spectra to characterize the SDSS-V APOGEE and BOSS spectra.
