Algorithmic Error Mitigation Scheme for Current Quantum Processors

TL;DR

This paper introduces a hardware-agnostic error mitigation algorithm inspired by the Lanczos method, which improves the accuracy of quantum computations on near-term quantum processors without extra experimental overhead.

Contribution

The authors propose a novel error mitigation scheme that enhances quantum algorithm accuracy by increasing measurement counts, applicable across different hardware without additional experimental complexity.

Findings

Significantly improves cost function evaluation accuracy in variational quantum algorithms

Demonstrates effectiveness through numerical simulations and IBM Quantum hardware experiments

Achieves better ground-state calculations in quantum chemistry and physics problems

Abstract

We present a hardware agnostic error mitigation algorithm for near term quantum processors inspired by the classical Lanczos method. This technique can reduce the impact of different sources of noise at the sole cost of an increase in the number of measurements to be performed on the target quantum circuit, without additional experimental overhead. We demonstrate through numerical simulations and experiments on IBM Quantum hardware that the proposed scheme significantly increases the accuracy of cost functions evaluations within the framework of variational quantum algorithms, thus leading to improved ground-state calculations for quantum chemistry and physics problems beyond state-of-the-art results.