Bachelor in Physics Education (Licenciatura) from UNESP (2023), currently pursuing a Bachelors degree in Materials Physics and a Masters degree in Computer Science at the same institution. FAPESP research fellow with experience in Quantum Computing, focusing on variational algorithms, optimization, and machine learning, including a research internship abroad (BEPE FAPESP) at Universidad Técnica Federico Santa María (Chile). Also engaged in teaching activities as a university teaching assistant, tutor in the PAADES program (Elementary Computational Analysis) at UNESP, and instructor in preparatory courses for university entrance exams. (Source: Lattes Curriculum)
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The objective of this study is to analyze how quantum algorithms can be used to enhance optimization and machine learning. We will explore how these algorithms operate in open quantum systems and how they can be combined with traditional machine learning methods to improve their outcomes. Furthermore, we will investigate how quantum algorithms can be applied in simpler scenarios of open q…
The study of the quantum phase transitions is an aspect of great interest in the scientific community.Despite the enormous efforts to detect the transitions and classify the phases, this is still a major problem today, given the computational effort required in the diagonalization of high dimension matrices. Our goal, in this sense, is to understand how Machine Learning (ML) techniques ca…
This project aims to study the application of quantum machine learning (QML) algorithms, focusing on QSVM (Quantum Support Vector Machine) and QPINN (Quantum Physics-Informed Neural Network) models. The objective is to understand their capabilities, limitations, and explanatory potential in small-scale quantum systems. An exploratory analysis of circuit structures and their behavior in cl…
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