Dissertation Defense
Student: Giulia Martos
Program: Astronomy
Title: "Chemical signatures of planets in the spectrum of solar twins"
Advisor: Prof. Dr. Jorge Luis M. Moreno
Judging Committee:
- Presidente banca: Prof. Dr. Jorge Luis Melendez Moreno – IAG/USP
- Profa. Dra. Beatriz Leonor Silveira Barbuy – IAG/USP
- Prof. Dr. Diogo Martins Souto – UFS
- Profa. Dra. Adriana Benetti Marques Valio -Universidade Mackenzie
Abstract
Precise chemical abundances are key for the characterization of planet hosts, since the formation and the presence of planets around the stars can alter their chemical composition, creating fingerprints that are revealed through a detailed analysis of the spectrum. In this work, a Machine Learning algorithm was developed to obtain the atmospheric parameters and chemical abundances of 20 elements for a sample 100 solar twins automatically from their high quality spectra obtained with the HARPS spectrograph, installed at the 3.6 meters telescope at the La Silla Observatory from ESO. The results obtained are in line with the literature, with average differences and standard deviations of (2 ± 27) K for Teff, (0.00 ± 0.06) dex for log g, (0.00 ± 0.02) dex for [Fe/H], (−0.01 ± 0.05) km/s for micro turbulence velocity, (0.02 ± 0.08) km/s for macro turbulence velocity and (−0.12 ± 0.26) km/s for projected rotational velocity. Regarding the chemical abundances, we reached a precision of 0.01 dex for the elements Na, Mg, Al, Si, Ca, Ti, Cr, Co, Ni e Cu, and most of the other elements agree within 0.01 and 0.02 dex with the literature. The abundances were corrected from the effects of the Galactic Chemical Evolution through a fitting versus the age of the stars and analyzed with the condensation temperature to verify if the stars presented depletion of refractories compared to volatiles. It was found that the Sun is more depleted in refractories than 89% of the twins, with a significance of ∼ 9σ.
Keywords: solar twins, precise chemical abundances, exoplanets, spectroscopy, machine learning