Can chaotic quantum circuits maintain quantum supremacy under noise?

Examples include the power & limitations of near-term quantum devices, quantum machine learning and quantum optimization algorithms. I would also like to explore quantum error correction and quantum-inspired approaches to design classical algorithms.

Dr. Xun Gao finished his PhD with Prof. Luming Duan at Tsinghua University in 2018. His research interests include quantum machine learning, application and computational power of near-term quantum computer and tensor network method.

Xun Gao Assistant Professor, Department of Physics, University of Colorado Boulder Associate Fellow, JILA [email protected] · (+1) 857-472-4775

2023年9月1日 · The Department of Physics at the University of Colorado Boulder is excited to welcome Assistant Professor Xun Gao to the faculty this fall! Professor Gao has also been named an Associate Fellow of JILA and he is very enthusiastic about the collaborative environment between CU Physics and JILA.

2017年9月22日 · Here, we give a proof that, assuming a widely believed computational complexity conjecture, a deep neural network can efficiently represent most physical states, including the ground states of...

2025年3月13日 · Along type 1, I focus on quantum machine learning by combining ideas and techniques from statistical physics, quantum foundation and computational complexity theory, such as path integral quantization, quantum contextuality and polynomial hierarchy. I also study variational method for quantum many-body problems based on quantum circuits.

Xun GAO, Professor | Cited by 793 | of Changchun University of Science and Technology, Changchun (CUST) | Read 109 publications | Contact Xun GAO

Postdoctoral Researcher, Department of Physics, Harvard. Extended Reunion: The Quantum Wave in Computing, Summer 2022, Visiting Scientist. The Simons Institute for the Theory of …

My interests are the theory of quantum computing, include quantum algorithm, quantum simulation and quantum machine learning. I'm also interested in applying tensor network theory to other areas, e.g. computational complexity theory, …