Robust ground-state energy estimation under depolarizing noise

TL;DR

This paper introduces a robust ground-state energy estimation algorithm that effectively handles depolarizing noise, improving accuracy and efficiency over previous methods by leveraging spectral gap and randomized compiling techniques.

Contribution

The paper presents a new algorithm building on QCELS that is robust under depolarizing noise and maintains polynomial cost, advancing quantum energy estimation techniques.

Findings

Algorithm achieves accurate energy estimation under depolarizing noise

Utilizes spectral gap and randomized compiling for noise mitigation

Demonstrates feasibility of quantum energy estimation with noise robustness

Abstract

We present a novel ground-state energy estimation algorithm that is robust under global depolarizing error channels. Building upon the recently developed Quantum Exponential Least Squares (QCELS) algorithm, our new approach incorporates significant advancements to ensure robust estimation while maintaining a polynomial cost in precision. By leveraging the spectral gap of the Hamiltonian effectively, our algorithm overcomes limitations observed in previous methods like quantum phase estimation (QPE) and robust phase estimation (RPE). Going beyond global depolarizing error channels, our work underscores the significance and practical advantages of utilizing randomized compiling techniques to tailor quantum noise towards depolarizing error channels. Our research demonstrates the feasibility of ground-state energy estimation in the presence of depolarizing noise, offering potential advancements in error correction and algorithmic-level error mitigation for quantum algorithms.