Scalable error mitigation for noisy quantum circuits produces competitive expectation values

TL;DR

This paper demonstrates scalable error mitigation techniques, particularly zero-noise extrapolation, for large quantum circuits up to 26 qubits, significantly improving the accuracy of quantum simulations beyond classical methods.

Contribution

It extends error mitigation to larger quantum systems and complex dynamics, showing practical scalability and potential for quantum advantage.

Findings

Error mitigation improves expectation value accuracy in large circuits

Combining error suppression techniques enhances performance

Quantum simulations surpass classical tensor network methods

Abstract

Noise in existing quantum processors only enables an approximation to ideal quantum computation. However, these approximations can be vastly improved by error mitigation, for the computation of expectation values, as shown by small-scale experimental demonstrations. However, the practical scaling of these methods to larger system sizes remains unknown. Here, we demonstrate the utility of zero-noise extrapolation for relevant quantum circuits using up to 26 qubits, circuit depths of 60, and 1080 CNOT gates. We study the scaling of the method for canonical examples of product states and entangling Clifford circuits of increasing size, and extend it to the quench dynamics of 2-D Ising spin lattices with varying couplings. We show that the efficacy of the error mitigation is greatly enhanced by additional error suppression techniques and native gate decomposition that reduce the circuit time. By combining these methods, we demonstrate an accuracy in the approximate quantum simulation of the quench dynamics that surpasses the classical approximations obtained from a state-of-the-art 2-D tensor network method. These results reveal a path to a relevant quantum advantage with noisy, digital, quantum processors.