Seminar: When A Network Scientist Meets Quantum Information Science
Computing Innovation Fellow
University of Massachusetts Amherst &
Massachusetts Institute of Technology (MIT)
Wednesday, February 16, 2022
1100 Torgersen Hall
What can a network scientist do in the field of quantum information science? In this talk, I will use entanglement distribution, an essential task in quantum networks, as an example to answer this question. Entanglement is a critical resource in quantum information science, and distributing entanglement across large distances enables various applications such as quantum cryptography, distributed quantum computing, and quantum sensing. Entanglement can be established between two nodes that are far apart by entanglement swapping. We start with a star-shaped network (quantum switch) and consider that entanglement requests randomly arrive at the network. We determine the capacity region for the rates of entanglement requests, and develop entanglement swapping protocols accordingly. Next we consider a general network and show how to maximize the entanglement distribution rate by introducing new concepts of e-nodes and e-flows. These concepts enable us to transform the entanglement distribution problem to a linear optimization program. Then we show the impact of finite memories to the entanglement distribution rate and propose several memory allocation methods. In the end, I will talk about potential future directions on building, evaluating, and using quantum networks.
Wenhan Dai a Computing Innovation Fellow at the University of Massachusetts Amherst and Massachusetts Institute of Technology (MIT). He received the S.M. and Ph.D. degrees from MIT. His research interests include quantum information science, network science, and statistical inference.