Averaged circuit eigenvalue sampling

TL;DR

ACES is a scalable quantum noise metrology method that estimates detailed error rates across large quantum circuits, surpassing previous techniques in information depth and assumptions, enabling advanced quantum error management.

Contribution

Introduces ACES, a comprehensive and scalable method for detailed error characterization in quantum circuits, generalizing and improving upon existing benchmarking techniques.

Findings

Successfully estimates all Pauli error rates in 100-qubit devices

Requires fewer than 20 shallow Clifford circuits for precise results

Operates under weaker assumptions than prior methods

Abstract

We introduce ACES, a method for scalable noise metrology of quantum circuits that stands for Averaged Circuit Eigenvalue Sampling. It simultaneously estimates the individual error rates of all the gates in collections of quantum circuits, and can even account for space and time correlations between these gates. ACES strictly generalizes randomized benchmarking (RB), interleaved RB, simultaneous RB, and several other related techniques. However, ACES provides much more information and provably works under strictly weaker assumptions than these techniques. Finally, ACES is extremely scalable: we demonstrate with numerical simulations that it simultaneously and precisely estimates all the Pauli error rates on every gate and measurement in a 100 qubit quantum device using fewer than 20 relatively shallow Clifford circuits and an experimentally feasible number of samples. By learning the detailed gate errors for large quantum devices, ACES opens new possibilities for error mitigation, bespoke quantum error correcting codes and decoders, customized compilers, and more.