Randomized Benchmarking of Quantum Gates

TL;DR

This paper introduces a randomized benchmarking method to accurately estimate quantum gate errors without relying on perfect state preparation, enabling scalable error assessment in quantum computing.

Contribution

It presents a novel randomized benchmarking technique that overcomes limitations of process tomography, providing reliable error estimates for quantum gates in long sequences.

Findings

Achieved a one-qubit error probability of 0.00482(17) per gate.

Demonstrated the method on trapped ion qubits.

Error rates are expected to improve with technical modifications.

Abstract

A key requirement for scalable quantum computing is that elementary quantum gates can be implemented with sufficiently low error. One method for determining the error behavior of a gate implementation is to perform process tomography. However, standard process tomography is limited by errors in state preparation, measurement and one-qubit gates. It suffers from inefficient scaling with number of qubits and does not detect adverse error-compounding when gates are composed in long sequences. An additional problem is due to the fact that desirable error probabilities for scalable quantum computing are of the order of 0.0001 or lower. Experimentally proving such low errors is challenging. We describe a randomized benchmarking method that yields estimates of the computationally relevant errors without relying on accurate state preparation and measurement. Since it involves long sequences of randomly chosen gates, it also verifies that error behavior is stable when used in long computations. We implemented randomized benchmarking on trapped atomic ion qubits, establishing a one-qubit error probability per randomized pi/2 pulse of 0.00482(17) in a particular experiment. We expect this error probability to be readily improved with straightforward technical modifications.