Wang Conducting Finite Temperature Simulation Of Non-Markovian Quantum Dynamics

Fei Wang, Assistant Professor, Chemistry and Biochemistry, received funding from the National Science Foundation for the project: "Finite temperature simulation of non-Markovian quantum dynamics in condensed phase using quantum computers."

For this research, Wang will develop efficient quantum algorithms to perform condensed phase quantum dynamics simulations on quantum computers.

Many important physical and chemical processes occur in the condensed phase, spanning chemical reactions in solutions, charge transfer at semiconductor interfaces, and solar energy conversion in molecular aggregates.

The scientific investigation of these processes not only promotes scientists' fundamental understanding but also offers practical solutions to materials design and environmental sustainability.

Wang aims to show quantum acceleration for quantum dynamics simulations in condensed phases and demonstrate practical applications of quantum computing in the area of quantum simulation.

New advances in this project will cover unitary operator construction, efficient quantum circuit compilation, model and real system simulations, and performance comparison between different types of quantum devices.

Wang will explore three mathematical methods (unitary dilation, singular value decomposition, and linear combinations of unitary operators) for non-unitary to unitary conversion. Wang will also assess their effectiveness based on complexity theory.

Wang will also investigate two general approaches for circuit compilation: one that performs the exact mathematical decomposition, and another that uses the variational quantum circuit method.

He will test the algorithm on spin-boson models as well as on realistic systems. He will also test the performance of trapped ions and compare superconducting devices.

The success of the algorithm will offer quantum acceleration in simulations of multi-state non-Markovian quantum dynamics at finite temperature.

A user-friendly and open-source platform will be put forward such that, with input parameters, dynamical simulations on a quantum computer can be carried out and the results analyzed. This work could potentially inspire future quantum algorithm design for simulating the dynamics of open quantum systems.

Graduate students and postdoctoral researchers involved in this project will receive rigorous training in quantum information science and master state-of-the-art quantum simulation tools. Through internship programs offered to undergraduate and high school students, Wang will support underrepresented and economically disadvantaged groups. These efforts will not only encourage broad participation in science, technology, engineering and mathematics (STEM), but also help to educate a future quantum workforce for careers in academia and industry.

Wang will receive total funding of $505,281 from NSF for this project. Funding began in June 2023 and will end in late May 2026.