Robust ground-state energy estimation under depolarizing noise

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 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, such as quantum phase estimation and robust phase estimation. Going beyond global depolarizing error channels, our work underscores the significance and practical advantages of utilizing randomized compiling techniques to tailor quantum noise toward 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.