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.
Highlights
One of the main limitations of available quantum computers is the sensitivity to noise
We present a hardware agnostic error mitigation algorithm for near term quantum processors inspired by the classical Lanczos method
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, leading to improved ground state calculations for quantum chemistry and physics problems beyond state-of-the-art results
Summary
One of the main limitations of available quantum computers is the sensitivity to noise. While quantum error correction techniques [1,2,3] could in principle offer a solution, all the proposed schemes demand technological advancements which are still beyond state-of-the-art capabilities. Within a near-term perspective [4], the available algorithmic implementations are limited to shallow circuits applied on easy-to-prepare initial states [5,6,7,8,9,10]. Only proof-of-principle experiments have been performed [11,12,13,14,15,16], whose performances are not compared to classical coun-
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