Abstract: Quantum computers now have the size and reliability to allow more widespread experimentation and educational outreach. With more research and students using quantum computers, a natural question lies in how to simulate, reason about, and debug quantum programs and circuits. Probabilistic graphical models such as Bayesian networks offer a natural description of a quantum computer's quantum states and probabilistic noise. In this seminar talk I will discuss a case study presented at ASPLOS 2021 in simulating variational algorithms. Then, I will discuss extensions in modeling correlated noise and higher-dimensional quantum states.
Bio: Yipeng Huang joined Rutgers University as an assistant professor in 2020. His research and teaching are in quantum computing and emerging computer architectures. He is interested in quantum computer systems: how to program them, simulate them, and debug them. His research has previously been supported by a DARPA STTR grant, and his work had been cited among IEEE MICRO top picks. https://people.cs.rutgers.edu/yh804