Optimization, qantum technology, and memory circuits

• Grant number: 25/08539-3
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• Start date: October 01, 2025
• End date: September 30, 2027
• Field of knowledge: Physical Sciences and Mathematics - Physics - General Physics
• Principal Investigator: Leonardo Kleber Castelano
• Grantee: Martín Daniel Jiménez
• Host Institution: Centro de Ciências Exatas e de Tecnologia (CCET). Universidade Federal de São Carlos (UFSCAR). São Carlos , SP, Brazil
• Associated research grant: 24/09298-7 - Optimization, quantum technology, and memory circuits, AP.R

Abstract

This project addresses key challenges in the development of quantum information technologies, with a focus on building scalable, resilient, and high-fidelity quantum computing systems. The primary objective is to mitigate adverse quantum effects such as decoherence and crosstalk, which hinder the implementation of fault-tolerant quantum computing. To this end, the project will employ advanced quantum optimal control techniques, including Krotov's method and neural network-based optimization, to design control pulses that enhance the fidelity of quantum gates.The research also explores the use of neural networks that satisfy quantum differential equations as tools to detect and compensate for dynamic crosstalk during gate execution. This hybrid approach, which combines machine learning with quantum control theory, aims to deliver innovative solutions for controlling quantum systems in realistic experimental settings.In addition, the project investigates the potential of memristors, devices that combine memory and resistive properties, in hybrid architectures for computation and data storage. The dynamics of circuits comprising memristors coupled with passive elements will be analyzed, with an emphasis on pulse optimization for targeted functional control. The feasibility and potential applications of quantum memristors will also be examined in the context of emerging quantum information technologies.