Accurate ground state energy estimation with noise and imperfect state preparation
Alicja Dutkiewicz (1, 2), Thomas E. O'Brien (3, 2), Stefano Polla (2) ((1) QuSoft / CWI, (2) aQa / Instituut-Lorentz, (3) Google Quantum AI)

TL;DR
This paper presents a classical estimator for quantum phase estimation data that is robust to noise and imperfect state preparation, significantly improving bias and variance performance over naive methods, and is practical for early fault-tolerant quantum experiments.
Contribution
The authors introduce a moment-projection estimator for phase estimation that effectively filters signals within a promise region, achieving exponential bias suppression and noise robustness, with practical validation on the Ising model.
Findings
Estimator achieves exponential bias suppression in noiseless case.
Estimator reduces bias exponentially with circuit depth under depolarizing noise.
Validation on Ising model simulation shows improved performance under realistic noise.
Abstract
We introduce a classical estimator for the post-processing of quantum phase estimation data generated either by quantum-Fourier-transform-based or quantum-signal-processing-based methods. We focus on the estimation of a single target phase promised to be within an interval where no other phases are present, which is typical of e.g. ground state energy estimation of gapped quantum systems. This allows us to perform phase estimation by filtering the signal within the promise region and recovering the phase through a moment-projection estimator. We show that our methods are robust in the presence of both additional phases outside the promise region and global depolarizing noise. In the noiseless case our estimator can achieve an exponential suppression of bias with respect to a naive mean estimator. In the presence of global depolarizing noise our estimator achieves a bias exponentially…
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Quantum Information and Cryptography · Quantum many-body systems
