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Bibliographic Details
Main Authors: Lee, Woo-Ram, Scott, Ryan, Scarola, V. W.
Format: Preprint
Published: 2022
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Online Access:https://arxiv.org/abs/2212.14039
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author Lee, Woo-Ram
Scott, Ryan
Scarola, V. W.
author_facet Lee, Woo-Ram
Scott, Ryan
Scarola, V. W.
contents Quantum simulation advantage over classical memory limitations would allow compact quantum circuits to yield insight into intractable quantum many-body problems, but the interrelated obstacles of large circuit depth in quantum time evolution and noise seem to rule out unbiased quantum simulation in the near term. We prove that classical post-processing, i.e., long-time filtering of an offline time series, exponentially improves the circuit depth needed for quantum time evolution. We apply the filtering method to the construction of a hybrid quantum-classical algorithm to estimate energy gap, an important observable not governed by the variational theorem. We demonstrate, within an operating range of filtering, the success of the algorithm in proof-of-concept simulation for finite-size scaling of a minimal spin model. Our findings set the stage for unbiased quantum simulation to offer memory advantage in the near term.
format Preprint
id arxiv_https___arxiv_org_abs_2212_14039
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle Hybrid quantum gap estimation algorithm using a filtered time series
Lee, Woo-Ram
Scott, Ryan
Scarola, V. W.
Quantum Physics
Strongly Correlated Electrons
Quantum simulation advantage over classical memory limitations would allow compact quantum circuits to yield insight into intractable quantum many-body problems, but the interrelated obstacles of large circuit depth in quantum time evolution and noise seem to rule out unbiased quantum simulation in the near term. We prove that classical post-processing, i.e., long-time filtering of an offline time series, exponentially improves the circuit depth needed for quantum time evolution. We apply the filtering method to the construction of a hybrid quantum-classical algorithm to estimate energy gap, an important observable not governed by the variational theorem. We demonstrate, within an operating range of filtering, the success of the algorithm in proof-of-concept simulation for finite-size scaling of a minimal spin model. Our findings set the stage for unbiased quantum simulation to offer memory advantage in the near term.
title Hybrid quantum gap estimation algorithm using a filtered time series
topic Quantum Physics
Strongly Correlated Electrons
url https://arxiv.org/abs/2212.14039