Machine learning applied to the optical Stern-Gerlach effect

• Grant number: 22/15394-3
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: March 01, 2023
• End date: February 29, 2024
• Field of knowledge: Physical Sciences and Mathematics - Physics - General Physics
• Principal Investigator: Daniel Zini Rossatto
• Grantee: Gustavo Del Duque
• Host Institution: Instituto de Ciência e Engenharia. Universidade Estadual Paulista (UNESP). Campus Experimental de Itapeva. Itapeva , SP, Brazil

Abstract

Recently, the use of machine learning techniques has become increasingly relevant in different areas of research, including physics. In general, it is necessary to know the state of a quantum system to obtain some information about it, which experimentally requires a quantum state tomography of the system, a task which can become challenging since the total description of the quantum system state scales exponentially with the dimension of its Hilbert space. In this project we will apply machine learning techniques, in particular considering support vector machine algorithms, to classify or estimate characteristics of the electromagnetic field state of an optical cavity mode using the optical Stern-Gerlach effect, eliminating the need to perform intracavity state tomography. For this, the machine will be trained and fed from the characteristics of the scattering pattern that an atomic beam is subjected to when it crosses the cavity in a certain state (optical Stern-Gerlach effect). In addition, the project aims to train the candidate in Python programming, particularly for the simulation of the dynamics of quantum systems and for the practical application of machine learning.