Abstract
Atoms are natural qubits for their fundamental property of being identical, and the consequent convenience in achieving scalable quantum control of large number of qubits. The atomic platform becomes particularly attractive with recent developments of optical tweezer and digital micromirror device techniques, where spatial resolved control of atoms is now feasible and advancing rapidly. This talk will present several protocols for atoms to perform quantum computing and solve difficult problems. I will describe universal quantum optimization architectures, by which atoms can be used for solving binary optimization, 3-SAT, and vertex-cover problems. This has wide applications in factorization, combinatorial optimization, and graph partitioning. Then I will present a quantum kernel function expansion algorithm, for finite temperature quantum simulations. In this algorithm, the temperature dependence of observables is expanded in terms of complete basis functions, and the expansion moments are obtained on a quantum circuit. This quantum algorithm has a natural realization considering Rydberg atoms.
Biography
Xiaopeng Li is Professor of Physics in the Physics Department of Fudan University, China, jointly employed by Shanghai Qi Zhi Institute. He is active in quantum information science and condensed-matter theories, with his primary research interests in exploiting the quantum computation power of various quantum simulation platforms. He received his Ph.D. in physics from the University of Pittsburgh in 2013 and joined Fudan University as a faculty member in 2016 after three years at the University of Maryland, supported by a Joint Quantum Institute theoretical postdoctoral fellowship. He has been a full professor since 2019.
Anyone interested is welcome to attend.