Optimization, quantum technology, and memory circuits

• Grant number: 24/09298-7
• Support Opportunities: Regular Research Grants
• Start date: December 01, 2024
• End date: November 30, 2027
• Field of knowledge: Physical Sciences and Mathematics - Physics
• Principal Investigator: Leonardo Kleber Castelano
• Grantee: Leonardo Kleber Castelano
• Host Institution: Centro de Ciências Exatas e de Tecnologia (CCET). Universidade Federal de São Carlos (UFSCAR). São Carlos , SP, Brazil

Abstract

This research project addresses critical challenges in developing scalable and reliable quantum computing systems and advanced memory technologies. The primary focus is on mitigating decoherence and crosstalk effects, major obstacles to the practical realization of fault-tolerant quantum computation. The project employs optimal quantum control theory, including advanced methods such as the Krotov method and neural network optimization, to enhance the fidelity of quantum gates. Additionally, Physics-Informed Neural Networks will be utilized to detect crosstalk during the execution of quantum gates.The project also explores the potential of memristor systems, which combine memory and resistor functionality, to revolutionize memory storage and neuromorphic computing. By analyzing systems that couple memristors with passive circuit elements, our research aims to optimize external pulses to achieve certain desired configurations. Collaborative efforts with the University of Wuerzburg facilitate a comprehensive approach, combining experimental results with theoretical analysis to advance the understanding of memristive behaviors. Finally, the feasibility of quantum memristors and their possible applications will be investigated.Through these investigations, the project seeks to contribute significantly to the fields of quantum computing and memory technologies, aiming to develop more resilient and efficient quantum information processing systems and versatile, high-performance memory devices. (AU)