Application of multivariate analysis methods in heavy ion data from the ALICE experiment

• Grant number: 19/03743-0
• Support Opportunities: Scholarships in Brazil - Doctorate (Direct)
• Start date: April 01, 2019
• End date: September 30, 2023
• Field of knowledge: Physical Sciences and Mathematics - Physics - Nuclear Physics
• Principal Investigator: Jun Takahashi
• Grantee: Gabriel Reis Garcia
• Host Institution: Instituto de Física Gleb Wataghin (IFGW). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
• Associated research grant: 17/05685-2 - Hadronic physics in high energy nuclear collisions, AP.ESP
• Associated scholarship(s): 22/01562-1 - Application of machine learning methods for strangeness reconstruction in heavy ion collision data from the ALICE experiment, BE.EP.DD

Abstract

This is a proposal for a PhD Project that is part of the thematic project "Física Hadrônica em Colisões Nucleares de Altas Energias" that has the main focus on heavy Ion physics, working with data analysis of the ALICE experiment at the LHC. One of the goals of this project will be the application of the "Machine Learning" (ML) tools to analyze ALICE data, focusing in optimizing measurement efficiency of rare signals of some physical process, in particular related to the measurement of strange particles that are too difficult to measure with conventional analysis methods. The project will be developed within the HadrEx group of the Physics Institute "Gleb Wataghin" at Campinas State University. The group already is an official member of the ALICE collaboration. (AU)

Academic Publications

(References retrieved automatically from State of São Paulo Research Institutions)

GARCIA, Gabriel Reis. Métodos de machine learning para reconstrução de estranheza no ALICE. 2023. Doctoral Thesis - Universidade Estadual de Campinas (UNICAMP). Instituto de Física Gleb Wataghin Campinas, SP.