ExpandQISE: Track 1: Quantum Correlations in Quantum Approximate Optimization Algorithms and Their Implementation

As quantum computing hardware develops, exploring practical applications of near-term quantum devices has attracted an increasing interest. This Expanding Capacity in Quantum Information Science and Engineering (ExpandQISE) project supports research that explores the fundamental theory of the potential of hybrid quantum-classical algorithms for solving complex optimization problems and their implementation in near-term quantum devices. The project also develops an undergraduate quantum computing course for STEM students with diverse backgrounds to enter the field. Through these research and education activities, postdocs, graduate students, and undergraduate students are trained in quantum computing for the quantum workforce needs of industry, government, and academia. Hybrid quantum-classical algorithms, such as the Quantum Approximate Optimization Algorithm (QAOA), emerge as a potential tool for solving complex problems. However, no speedup of these algorithms over classical algorithms for any practically relevant tasks have been demonstrated. Quantum entanglement, on the other hand, is considered a resource for quantum computing to go beyond classical computing. However, the role of entanglement in quantum-classical algorithms is subtle. In this project, the research team focuses on the role of quantum correlations, including multipartite entanglement and spin squeezing, to investigate the theory and performance of algorithms based on QAOA. The Principal Investigator will leverage the direct access to IBM Quantum Computers at the University of Rhode Island and the expertise and experience of the Co-Principal Investigator and the collaborators in the fields of quantum computing and quantum algorithms to explore 1) theoretical analysis of the performance of low depth QAOA under different variations, including initial entangled states and entangling mixing operators, 2) numerical simulation of the new variations in QAOA using high-performance computers, and 3) experimental implementation of these new QAOA variations on large quantum computing devices with tens of qubits. This award was jointly funded by the Directorate for Engineering, Division of Civil, Mechanical and Manufacturing Innovation, the Directorate for Mathematical and Physical Sciences, Office of Strategic Initiatives, and the Directorate for Computer and Information Science and Engineering, Division of Computing and Communication Foundations. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.