Chemical Abundances for 25 JWST Exoplanet Host Stars with KeckSpec

TL;DR

This study uses a machine learning tool to determine detailed chemical abundances and stellar parameters for 25 exoplanet host stars observed by JWST, revealing diverse disk compositions.

Contribution

Introduces a data-driven method to derive stellar parameters and elemental abundances for JWST exoplanet hosts, expanding the chemical characterization of these stars.

Findings

Some stars have solar-like disk chemistry.

Others show evidence of different disk compositions.

Sample will be part of a larger catalog of 4,500 stars.

Abstract

Using a data-driven machine learning tool we report $T_{\text{eff}}$, $\log{(g)}$, $v\sin{(i)}$, and elemental abundances for 15 elements (C, N, O, Na, Mg, Al, Si, Ca, Ti, V, Cr, Mn, Fe, Ni, Y) for a sample of 25 exoplanet host stars targeted by JWST's first year of observations. The chemical diversity of these stars show that, while a number of their companion planets may have formed in a disk with chemistry similar to Solar, some JWST targets likely experienced different disk compositions. This sample is part of a larger forthcoming catalog that will report homogeneous abundances of $\sim$4,500 FGK stars derived from Keck/HIRES spectra.