The standard method for benchmarking quantum error corr ection is \nrandomized fault-injection testing. \nThe state-of-the-a rt tool Stim is efficient for error-correction implementations with di stances of up to 10\, but scales poorly to larger distances for low ph ysical error rates. In this talk\, I will present a scalable approach that combines stratified fault injection with extrapolation. \nThe ins ight is that some of the fault space can be sampled efficiently\, afte r which extrapolation is sufficient to complete the testing task. As a result\, our tool scales to distance 17 for \na physical error rate o f 0.0005 with a two-hour time budget on a desktop. For this case\, it estimated a logical error rate of \n$1.51 \\times 10^{-11}$ with high confidence. \nJoint work with John Zhuoyang Ye\, https://arxiv.org/abs/2602.04921
\nBi o: Jens Palsberg is a Professor and a former Department Chair of Compu ter Science at the University of California\, Los Angeles (UCLA). His research interests span the areas of programming languages\, software engineering\, and quantum computing. \nHe is the director of the UCLA- Amazon Science Hub for Humanity and Artificial Intelligence\, an assoc iate editor of ACM Transactions on Quantum Computing\, and a member of the ACM Council. In 2012\, he received the ACM SIGPLAN Distinguished Service Award\, and in 2023 he received the Excellence in Teaching Awa rd from the UCLA Samueli Engineering School for his courses on quantum computing.
URL:https://www.physics.wisc.edu/events/?id=9628 END:VEVENT END:VCALENDAR