Closed form logical error rate approximations for surface codes
This work provides a computationally efficient tool for quantum computing researchers to optimize surface code implementations without costly simulations.
The authors propose a closed-form method to compute logical error rates in surface codes, eliminating the need for expensive classical simulations. Their approach uses symmetry and configuration counting to achieve provably accurate approximations, enabling efficient comparison of quantum computer designs.
We propose a novel method to calculate logical error rates in surface codes, assuming independent and identically distributed physical errors. We show how to use our 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, we use the symmetry of the problem to count the configurations that result in a logical error with our novel software. Given a physical error rate, we can deduce the probability of a logical error, to provably good accuracy. We include an analysis of measurement errors to allow a more complete comparison of different surface code implementations.