Simulation, Compilation and Error Mitigation Techniques for Quantum Computing and Quantum Machine Learning

Ang Li, Pacific Northwest National Laboratory

Wegmans Hall 1400

Abstract: Over the past five years, the field of quantum computing, especially noisy-intermediate scale quantum (NISQ) computing has witnessed exciting developments. In this talk, I will discuss several research projects we have conducted over the past three years on topics such as quantum system simulation, quantum error mitigation, quantum machine learning, and distributive quantum computing. I will also explore future research opportunities in these areas. These efforts are supported by the NQISRC, quantum science center (QSC) and co-design center for quantum advantage (C2QA).

Ang Li is a senior computer scientist in the Physical and Computational Sciences directory of Pacific Northwest National Laboratory. He received B.S. degree on computer science from Zhejiang University, China, in 2010 and two Ph.D. degrees on electrical and computer engineering from National University of Singapore, and Eindhoven University of Technology, Netherlands in 2016.  His research has been focusing on software-hardware co-design for scalable heterogeneous HPC and quantum computing. His work was nominated for the best paper award in Supercomputing’15/17/20, IISWC’18 and ISCA’22 and won the best paper award in ICCD’21, Cluster’22.

Refreshments will be provided.