Dr. Shaked Regev, ORNL
Abstract:
The authors propose a novel method to calculate logical error rates in surface codes, assuming independent and identically distributed physical errors. These results fit well known scaling laws for studied physical error rates and code distances but break down in some other regimes. They show how to use their method to analyze hypothetical quantum computers with various configurations and select designs with lower error rates. Currently, this requires expensive classical simulations of quantum decoders for various distances and physical error rates or inaccurate extrapolation from minimal experimental data. Instead, they use the symmetry of the problem to count the configurations that result in a logical error with their novel software. Given a physical error rate, the method can deduce the probability of a logical error to provably good accuracy. The authors include an analysis of measurement errors to allow for a more complete comparison of different surface code implementations. They extend this counting method to a particular locally correlated error model.
Speaker’s Bio:
Dr. Shaked Regev is a Research Scientist at Oak Ridge National Laboratory whose research interests include Quantum Error Correction, Numerical Linear Algebra, Mathematical Optimization, GPU Programming, and High-Performance Computing. He received his Ph.D. in Computational and Mathematical Engineering from Stanford University for his thesis on “Preconditioning Techniques for Sparse Linear Systems.“
Host:
Elaine Wong, [email protected], 865-341-2325