I am a Staff Researcher at the Institute for Quantum Computing at Baidu Research. At Baidu Quantum, I focus on the research on quantum computing and the development of Baidu Quantum Platform. In particular, I lead the development of Paddle Quantum, a Python library for quantum machine learning. My research investigates a broad range of perspectives of quantum computing and quantum information, including quantum communication, entanglement theory, near-term quantum applications, quantum machine learning, and quantum control. I am also an editor of Quantum.
I was a Hartree Postdoctoral Fellow at the Joint Center for Quantum Information and Computer Science (QuICS) at the University of Maryland, College Park. I received my doctorate in quantum information from the University of Technology Sydney in 2018 (Chancellor’s List for Outstanding Thesis), under the supervision of Prof. Runyao Duan and Prof. Andreas Winter. I obtained my B.S. in mathematics (with Wu Yuzhang Honor) from Sichuan University in 2014.
Hiring: We are looking for self-motivated student interns interested in quantum computation, quantum machine learning, and quantum control (details). If you are interested in joining the journey from the fundamentals of quantum information to the frontier of quantum computing industry, please feel free to contact!
PhD in Quantum Information, 2018
University of Technology Sydney
BSc in Mathematics, 2014
The main focus of my research is to better understand the power and limits of information processing with quantum systems. I also aim to explore new applications of quantum information and new approaches to overcome theatrical challenges in realizing quantum technologies.
My Ph.D. thesis Semidefinite Optimization for Quantum Information (pdf) aims to contribute to the development of quantum Shannon theory, entanglement theory, and zero-error information theory. It explores the fundamental properties of quantum entanglement and establishes efficiently computable approximations for elementary tasks in quantum information theory by using semidefinite optimization, matrix analysis, and information measures.
Quantum Shannon theory is the study of the ultimate performance of communication with quantum systems. One of my primary topics is to investigate the communication capabilities of quantum channels under both finite blocklength and asymptotic regime. The asymptotic regime focuses on the ultimate limits of communication, while the finite blocklength regime focuses on a more practical scenario involving only small and medium number of bits or qubits. Good examples of my results in this area are as follows:
Quantum entanglement is a key ingredient in many quantum information processing tasks, including teleportation, superdense coding, and quantum cryptography. I am interested in exploring the fundamental structure and the resource theory of entanglement. For example, I demonstrate the irreversibility of asymptotic entanglement manipulation under quantum operations that completely preserve the positivity of partial transpose (PPT), resolving a major open problem in quantum information theory.
I also established single-letter formulas to efficiently quantify the quantum entanglement required for quantum state preparation and quantum channel implementation:
Notably, the above work introduces the first entanglement measure that is efficiently computable while possessing a direct operational meaning for general bipartite states, thus solving a question that has remained open since the inception of entanglement theory over two decades ago. This unique feature helps us better understand the fundamental structure and power of entanglement.
Magic state manipulation is a crucial component in the leading approaches to realizing scalable, fault-tolerant, and universal quantum computation. Related to magic state manipulation is the resource theory of magic states, for which one of the goals is to characterize and quantify quantum “magic.” In the following two papers, we develop resource-theoretic approaches to study the non-stabilizer resources in fault-tolerant quantum computation. We, in particular, introduce efficiently computable magic measures to quantify the magic of quantum states as well as noisy quantum circuits and explore their applications in magic state distillation, gate synthesis, and classical simulation of noisy circuits.
Quantum resource theory (QRT) offers a powerful framework for studying different phenomena in quantum physics. It aims to capture and quantify the desirable quantum effect, and optimize its use for particular quantum applications. My interests in this area lie in the mathematical analysis and characterization of quantum resources, as well as the applications of QRT for other quantum technologies. Good examples of my results are as follows:
heorythe ordinary Shannon theory studies communication with asymptotically vanishing errors, Shannon also investigated the information theory when errors are required to be strictly zero, which is known as the zero-error information theory. In this area, the communication problem reduces to the study of the so-called confusability graph (non-commutative graph) of a classical channel (quantum channel). A good example of my research in this area is proving the separation between the quantum Lovász number and the entanglement-assisted zero-error capacity: