A Comparison of Three Ways to Measure Time-Dependent Densities With Quantum Simulators

Quantum algorithms are touted as a way around some classically intractable problems such as the simulation of quantum mechanics. At the end of all quantum algorithms is a quantum measurement whereby classical data is extracted and utilized. In fact, many of the modern hybrid-classical approaches are...

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Main Authors: Jun Yang, James Brown, James Daniel Whitfield
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-03-01
Series:Frontiers in Physics
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fphy.2021.546538/full
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spelling doaj-078acfe487734aa4ac9e2465f7c653a02021-03-19T06:01:02ZengFrontiers Media S.A.Frontiers in Physics2296-424X2021-03-01910.3389/fphy.2021.546538546538A Comparison of Three Ways to Measure Time-Dependent Densities With Quantum SimulatorsJun YangJames BrownJames Daniel WhitfieldQuantum algorithms are touted as a way around some classically intractable problems such as the simulation of quantum mechanics. At the end of all quantum algorithms is a quantum measurement whereby classical data is extracted and utilized. In fact, many of the modern hybrid-classical approaches are essentially quantum measurements of states with short quantum circuit descriptions. Here, we compare and examine three methods of extracting the time-dependent one-particle probability density from a quantum simulation: direct Z-measurement, Bayesian phase estimation, and harmonic inversion. We have tested these methods in the context of the potential inversion problem of time-dependent density functional theory. Our test results suggest that direct measurement is the preferable method. We also highlight areas where the other two methods may be useful and report on tests using Rigetti's quantum virtual device. This study provides a starting point for imminent applications of quantum computing.https://www.frontiersin.org/articles/10.3389/fphy.2021.546538/fullquantum measurementTDDFTBayesian inferenceharmonic inversionpotential inversion
collection DOAJ
language English
format Article
sources DOAJ
author Jun Yang
James Brown
James Daniel Whitfield
spellingShingle Jun Yang
James Brown
James Daniel Whitfield
A Comparison of Three Ways to Measure Time-Dependent Densities With Quantum Simulators
Frontiers in Physics
quantum measurement
TDDFT
Bayesian inference
harmonic inversion
potential inversion
author_facet Jun Yang
James Brown
James Daniel Whitfield
author_sort Jun Yang
title A Comparison of Three Ways to Measure Time-Dependent Densities With Quantum Simulators
title_short A Comparison of Three Ways to Measure Time-Dependent Densities With Quantum Simulators
title_full A Comparison of Three Ways to Measure Time-Dependent Densities With Quantum Simulators
title_fullStr A Comparison of Three Ways to Measure Time-Dependent Densities With Quantum Simulators
title_full_unstemmed A Comparison of Three Ways to Measure Time-Dependent Densities With Quantum Simulators
title_sort comparison of three ways to measure time-dependent densities with quantum simulators
publisher Frontiers Media S.A.
series Frontiers in Physics
issn 2296-424X
publishDate 2021-03-01
description Quantum algorithms are touted as a way around some classically intractable problems such as the simulation of quantum mechanics. At the end of all quantum algorithms is a quantum measurement whereby classical data is extracted and utilized. In fact, many of the modern hybrid-classical approaches are essentially quantum measurements of states with short quantum circuit descriptions. Here, we compare and examine three methods of extracting the time-dependent one-particle probability density from a quantum simulation: direct Z-measurement, Bayesian phase estimation, and harmonic inversion. We have tested these methods in the context of the potential inversion problem of time-dependent density functional theory. Our test results suggest that direct measurement is the preferable method. We also highlight areas where the other two methods may be useful and report on tests using Rigetti's quantum virtual device. This study provides a starting point for imminent applications of quantum computing.
topic quantum measurement
TDDFT
Bayesian inference
harmonic inversion
potential inversion
url https://www.frontiersin.org/articles/10.3389/fphy.2021.546538/full
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