Partnership for Research and Training in QUantum, Artificial Intelligence, Non-Equilibrium Physics Theory and Applications (QUANTA)

University Of Massachusetts Boston, Dorchester MA

Investigators

Abstract

The Partnership for research and training in QUantum, Artificial intelligence, Non-equilibrium physics Theory and Applications (QUANTA) is a collaboration between the University of Massachusetts Boston (UMass Boston) and the NSF AI Institute for Artificial Intelligence and Fundamental Interactions (IAIFI) for advancing research and education in quantum science and technology using AI-based approaches. The goals of the partnership are to develop physics-informed reinforcement learning approaches to solve problems in quantum science and technology and to recruit and train students in these important fields by providing cutting-edge research and education opportunities in quantum physics and AI. The connections established between physics and AI will drive further research leading to new approaches and discoveries in each discipline. The tools, approaches and insights developed from the proposed research will positively impact research and innovations in broader fields in science and engineering, ranging from quantum computing to robotics. UMass Boston is well-positioned to provide access to training in Quantum Information Science and Engineering (QISE) and AI. Building upon existing resources, the planned curricular innovations and educational initiatives in collaboration with IAIFI will positively impact both recruitment and retention of students in undergraduate and graduate programs at UMass Boston. Additionally, it will expand the impact of IAIFI activities by providing direct access to these activities to a large population of students in the Boston area. The Partnership for research and training in QUantum, Artificial intelligence, Non-equilibrium physics Theory and Applications (QUANTA) will establish a collaboration between UMass Boston and IAIFI to advance research and education at the intersection of physics and AI. We will utilize joint group meetings and mentorship of graduate and undergraduate students between UMass Boston and IAIFI, development of curricular innovations at UMass Boston in coordination with IAIFI, and access to IAIFI educational and computing resources. With these resources, the collaboration will focus on the interdisciplinary opportunities between reinforcement learning and quantum physics with the following specific research objectives: 1) Reinforcement Learning (RL) for Quantum: Develop novel approaches for entropy-regularized RL to advance current research in quantum systems; and 2) Quantum Applications: Apply entropy-regularized RL tools to solve optimization problems in quantum science and technology. The proposed research will develop novel approaches for entropy-regularized RL using insights from statistical mechanics. The combination of physics-based approaches with entropy-regularized deep RL can lead to the development of powerful tools for exploring complex, high-dimensional spaces giving rise to promising approaches for analysis of quantum systems. Projects arising from the proposed research will provide interdisciplinary training opportunities for graduate and undergraduate students who will be jointly mentored by faculty at UMass Boston and IAIFI. The proposed research will also be integrated with curricular innovations at UMass Boston that will build on existing resources such as the undergraduate Quantum Information Certificate. The educational components of the project will focus on improvements in recruitment and retention at UMass Boston and workforce development within the fields of quantum information science and engineering (QISE) and AI. 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.