Noise tailoring for scalable quantum computation via randomized compiling

TL;DR

This paper introduces a randomized compiling method that transforms coherent errors into stochastic errors, significantly reducing error rates and enabling fault-tolerant quantum computing with current experimental error levels.

Contribution

The authors propose a noise tailoring technique using randomized compiling that converts coherent errors into stochastic Pauli errors, improving quantum computation robustness.

Findings

Reduces worst-case and cumulative error rates dramatically.

Enables fault-tolerant quantum computation at current error levels.

Allows efficient measurement of error rates via randomized benchmarking.

Abstract

Quantum computers are poised to radically outperform their classical counterparts by manipulating coherent quantum systems. A realistic quantum computer will experience errors due to the environment and imperfect control. When these errors are even partially coherent, they present a major obstacle to achieving robust computation. Here, we propose a method for introducing independent random single-qubit gates into the logical circuit in such a way that the effective logical circuit remains unchanged. We prove that this randomization tailors the noise into stochastic Pauli errors, leading to dramatic reductions in worst-case and cumulative error rates, while introducing little or no experimental overhead. Moreover we prove that our technique is robust to variation in the errors over the gate sets and numerically illustrate the dramatic reductions in worst-case error that are achievable. Given such tailored noise, gates with significantly lower fidelity are sufficient to achieve fault-tolerant quantum computation, and, importantly, the worst case error rate of the tailored noise can be directly and efficiently measured through randomized benchmarking experiments. Remarkably, our method enables the realization of fault-tolerant quantum computation under the error rates observed in recent experiments.