QUANTUM CONTROL AND QUANTUM COMPUTING
Abstract
Quantum computing is an entirely new paradigm of computation that promises to solve some of the most difficult problems that are currently intractable on classical supercomputers. To realize practical quantum computation, a set of high-fidelity universal quantum gates robust against noise in the qubit system is prerequisite. So one of the objectives of this project is to find robust control pulses for universal quantum gates of the realistic quantum computer qubits and devices (e.g., IBM, Google, Intel, … ) with fidelities enabling large-scale fault-tolerant quantum computation. Quantum computing and artificial intelligence (AI; or machine learning) are undoubtedly the two hottest and most promising research fields of this century. We will explore the interaction between quantum computing and machine learning, and study how to use the results and technologies of one field to solve problems in the other field. After decades of efforts in constructing practical quantum computers, we are now in the so-called noisy intermediate-scale quantum (NISQ) computer era without quantum error correction. It may still be a long way to go to realize a fullyfunctional error-corrected quantum computer. Thus it is important to find quantum algorithms or applications that can achieve a dramatic speedup for an important problem and yet just use the NISQ devices with imperfect gates and limited size (50 to a few hundreds of qubits). So another objective of this project is to investigate, in the NISQ device stage, problems in quantum machine learning, quantum chemistry and optimization using the hybrid variational quantum-classical algorithms to demonstrate significant quantum advantage over their classical counterparts.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Aug 11, 2021
- Source ID
- FA23862014033
Entities
People
- Hsi-Sheng Goan
Organizations
- Air Force Office of Scientific Research
- National Taiwan University
- United States Air Force