Quantum control and quantum machine learning
Abstract
This project is concerned with exploring how quantum computing (QC) and machine learning (ML) can interact and assist together and investigating how to use the outcomes and technologies of one field to solve problems in the other field. In particular, it focuses on using deep reinforcement learning (DRL) as a tool for quantum control to construct high-fidelity universal quantum gates for promising and realistic quantum computing systems, and investigating using QC to obtain quantum advantages on ML tasks. The outcome of this project will use deep reinforcement learning (DRL) to construct control pulses for high-fidelity universal quantum gates for promising and realistic quantum computing systems. It will also investigate using QC to obtain quantum advantages on ML tasks and explore problems in molecular electronic energy structure, quantum chemistry, and quantum optimization.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Feb 16, 2024
- Source ID
- FA23862314052
Entities
People
- Hsi-Sheng Goan
Organizations
- Air Force Office of Scientific Research
- National Taiwan University
- United States Air Force