The Cost of Improving the Precision of the Variational Quantum
Eigensolver for Quantum Chemistry

J 2022

The Cost of Improving the Precision of the Variational Quantum Eigensolver for Quantum Chemistry

MIHÁLIKOVÁ, Ivana, Matej PIVOLUSKA, Martin PLESCH, Martin FRIÁK, Daniel NAGAJ et. al.

Basic information

Original name

The Cost of Improving the Precision of the Variational Quantum Eigensolver for Quantum Chemistry

Authors

MIHÁLIKOVÁ, Ivana (703 Slovakia, belonging to the institution), Matej PIVOLUSKA (703 Slovakia, belonging to the institution), Martin PLESCH (703 Slovakia, belonging to the institution), Martin FRIÁK (203 Czech Republic, belonging to the institution), Daniel NAGAJ (703 Slovakia, belonging to the institution) and Mojmír ŠOB (203 Czech Republic, guarantor, belonging to the institution)

Edition

Nanomaterials, London, MDPI, 2022, 2079-4991

Other information

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

10301 Atomic, molecular and chemical physics

Country of publisher

Switzerland

Confidentiality degree

není předmětem státního či obchodního tajemství

References:

URL

Impact factor

Impact factor: 5.300

RIV identification code

RIV/00216224:14610/22:00125538

Organization unit

Institute of Computer Science

DOI

http://dx.doi.org/10.3390/nano12020243

UT WoS

000747685100001

Keywords in English

noisy quantum processors; variational quantum eigensolver; quantum chemistry

Abstract

V originále

New approaches into computational quantum chemistry can be developed through the use of quantum computing. While universal, fault-tolerant quantum computers are still not available, and we want to utilize today's noisy quantum processors. One of their flagship applications is the variational quantum eigensolver (VQE)-an algorithm for calculating the minimum energy of a physical Hamiltonian. In this study, we investigate how various types of errors affect the VQE and how to efficiently use the available resources to produce precise computational results. We utilize a simulator of a noisy quantum device, an exact statevector simulator, and physical quantum hardware to study the VQE algorithm for molecular hydrogen. We find that the optimal method of running the hybrid classical-quantum optimization is to: (i) allow some noise in intermediate energy evaluations, using fewer shots per step and fewer optimization iterations, but ensure a high final readout precision; (ii) emphasize efficient problem encoding and ansatz parametrization; and (iii) run all experiments within a short time-frame, avoiding parameter drift with time. Nevertheless, current publicly available quantum resources are still very noisy and scarce/expensive, and even when using them efficiently, it is quite difficult to perform trustworthy calculations of molecular energies.

Links

MUNI/G/1596/2019, interní kód MU

Name: Development of algorithms for application of quantum computers in electronic-structure calculations in solid-state physics and chemistry (Acronym: Qubits4PhysChem)

Investor: Masaryk University, INTERDISCIPLINARY - Interdisciplinary research projects

Citovat

MIHÁLIKOVÁ, Ivana, Matej PIVOLUSKA, Martin PLESCH, Martin FRIÁK, Daniel NAGAJ and Mojmír ŠOB. The Cost of Improving the Precision of the Variational Quantum Eigensolver for Quantum Chemistry. Nanomaterials. London: MDPI, 2022, vol. 12, No 2, p. 1-22. ISSN 2079-4991. Available from: https://dx.doi.org/10.3390/nano12020243.

@article{1841543,
   author = {Miháliková, Ivana and Pivoluska, Matej and Plesch, Martin and Friák, Martin and Nagaj, Daniel and Šob, Mojmír},
   article_location = {London},
   article_number = {2},
   doi = {http://dx.doi.org/10.3390/nano12020243},
   keywords = {noisy quantum processors; variational quantum eigensolver; quantum chemistry},
   language = {eng},
   issn = {2079-4991},
   journal = {Nanomaterials},
   title = {The Cost of Improving the Precision of the Variational Quantum Eigensolver for Quantum Chemistry},
   url = {https://www.mdpi.com/2079-4991/12/2/243},
   volume = {12},
   year = {2022}
}

TY  - JOUR
ID  - 1841543
AU  - Miháliková, Ivana - Pivoluska, Matej - Plesch, Martin - Friák, Martin - Nagaj, Daniel - Šob, Mojmír
PY  - 2022
TI  - The Cost of Improving the Precision of the Variational Quantum Eigensolver for Quantum Chemistry
JF  - Nanomaterials
VL  - 12
IS  - 2
SP  - 1-22
EP  - 1-22
PB  - MDPI
SN  - 20794991
KW  - noisy quantum processors
KW  - variational quantum eigensolver
KW  - quantum chemistry
UR  - https://www.mdpi.com/2079-4991/12/2/243
N2  - New approaches into computational quantum chemistry can be developed through the use of quantum computing. While universal, fault-tolerant quantum computers are still not available, and we want to utilize today's noisy quantum processors. One of their flagship applications is the variational quantum eigensolver (VQE)-an algorithm for calculating the minimum energy of a physical Hamiltonian. In this study, we investigate how various types of errors affect the VQE and how to efficiently use the available resources to produce precise computational results. We utilize a simulator of a noisy quantum device, an exact statevector simulator, and physical quantum hardware to study the VQE algorithm for molecular hydrogen. We find that the optimal method of running the hybrid classical-quantum optimization is to: (i) allow some noise in intermediate energy evaluations, using fewer shots per step and fewer optimization iterations, but ensure a high final readout precision; (ii) emphasize efficient problem encoding and ansatz parametrization; and (iii) run all experiments within a short time-frame, avoiding parameter drift with time. Nevertheless, current publicly available quantum resources are still very noisy and scarce/expensive, and even when using them efficiently, it is quite difficult to perform trustworthy calculations of molecular energies.
ER  -

MIHÁLIKOVÁ, Ivana, Matej PIVOLUSKA, Martin PLESCH, Martin FRIÁK, Daniel NAGAJ and Mojmír ŠOB. The Cost of Improving the Precision of the Variational Quantum Eigensolver for Quantum Chemistry. \textit{Nanomaterials}. London: MDPI, 2022, vol.~12, No~2, p.~1-22. ISSN~2079-4991. Available from: https://dx.doi.org/10.3390/nano12020243.

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