Benchmarking Variational Quantum Eigensolvers for Entanglement Detection in Many-Body Hamiltonian Ground States

Drinko, Alexandre; Correr, Guilherme I.; Medina, Ivan; Azado, Pedro C.; Canabarro, Askery; Soares-Pinto, Diogo O.

Benchmarking Variational Quantum Eigensolvers for Entanglement Detection in Many-Body Hamiltonian Ground States

Alexandre Drinko
(
- Sao Paulo U., Sao Carlos
)
,
Guilherme I. Correr
(
- Sao Paulo U., Sao Carlos
)
,
Ivan Medina
(
- Sao Paulo U., Sao Carlos and
- Trinity Coll., Dublin
)
,
Pedro C. Azado
(
- Sao Paulo U., Sao Carlos
)
,
Askery Canabarro
(
- Sao Paulo U., Sao Carlos and
- Lisbon, IFM and
- Alagoas U. and
- Harvard U. and
- Technol. Innovation Inst., UAE
)

Jul 5, 2024

e-Print:

2407.04453 [quant-ph]

View in:

ADS Abstract Service

pdf

reference search1 citation

Citations per year

Abstract: (arXiv)

Variational quantum algorithms (VQAs) have emerged in recent years as a promise to obtain quantum advantage. These task-oriented algorithms work in a hybrid loop combining a quantum processor and classical optimization. Using a specific class of VQA named variational quantum eigensolvers (VQEs), we choose some parameterized quantum circuits to benchmark them at entanglement witnessing and entangled ground state detection for many-body systems described by Heisenberg Hamiltonian, varying the number of qubits and shots. Quantum circuits whose structure is inspired by the Hamiltonian interactions presented better results on cost function estimation than problem-agnostic circuits.

References(73)

Figures(10)

[1]

Quantum Computing in the NISQ era and beyond

John Preskill
(
- Caltech, IQI
)

- Quantum 2 (2018) 79
•
e-Print:
- 1801.00862
•
DOI:
- 10.22331/q-2018-08-06-79

[2]

The bitter truth about gate-based quantum algorithms in the NISQ era

Frank Leymann
(
- Stuttgart U.
)
,
Johanna Barzen
(
- Stuttgart U.
)

- Quantum Sci.Technol. 5 (2020) 4, 044007
•
DOI:
- 10.1088/2058-9565/abae7d

[4]

Noisy intermediate-scale quantum algorithms

Kishor Bharti
(
- Singapore Natl. U.
)
,
Alba Cervera-Lierta
(
- Toronto U.
)
,
Thi Ha Kyaw
(
- Toronto U.
)
,
Tobias Haug
(
- Imperial Coll., London
)
,
Sumner Alperin-Lea
(
- Toronto U.
)

et al.

- Rev.Mod.Phys. 94 (2022) 1, 015004
•
e-Print:
- 2101.08448
•
DOI:
- 10.1103/RevModPhys.94.015004

[4]

Noisy intermediate-scale quantum algorithms

Kishor Bharti
(
- Singapore Natl. U.
)
,
Alba Cervera-Lierta
(
- Toronto U.
)
,
Thi Ha Kyaw
(
- Toronto U.
)
,
Tobias Haug
(
- Imperial Coll., London
)
,
Sumner Alperin-Lea
(
- Toronto U.
)

et al.

- Rev.Mod.Phys. 94 (2022) 1, 015004
•
e-Print:
- 2101.08448
•
DOI:
- 10.1103/RevModPhys.94.015004

[5]

Hybrid quantum-classical algorithms in the noisy intermediate-scale quantum era and beyond

- Phys.Rev.A 106 (2022) 1, 010101
•
e-Print:
- 2207.06850
•
DOI:
- 10.1103/PhysRevA.106.010101

[6]

Variational quantum algorithms

M. Cerezo
(
- Los Alamos and
- Oak Ridge
)
,
Andrew Arrasmith
(
- Los Alamos and
- Oak Ridge
)
,
Ryan Babbush
(
- Unlisted, US, CA
)
,
Simon C. Benjamin
(
- Oxford U.
)
,
Suguru Endo
(
- Nippon NTT, Kanagawa
)

et al.

- Nature Rev.Phys. 3 (2021) 9, 625-644
•
e-Print:
- 2012.09265
•
DOI:
- 10.1038/s42254-021-00348-9

[7]

Cost function dependent barren plateaus in shallow parametrized quantum circuits

- Nature Commun. 12 (2021) 1, 1791
•
e-Print:
- 2001.00550
•
DOI:
- 10.1038/s41467-021-21728-w

[8]

Abhinav Kandala, Antonio Mezzacapo, Kristan Temme, Maika Takita, Markus Brink

Jerry M. Chow
,
Jay M. Gambetta

[9]

Exploring Entanglement and Optimization within the Hamiltonian Variational Ansatz

Roeland Wiersema
(
- Unlisted, CA and
- Waterloo U.
)
,
Cunlu Zhou
(
- Unlisted, CA and
- Toronto U.
)
,
Yvette de Sereville
(
- Waterloo U.
)
,
Juan Felipe Carrasquilla
(
- Unlisted, CA and
- Waterloo U.
)
,
Yong Baek Kim
(
- Toronto U.
)

et al.

- PRX Quantum 1 (2020) 2, 020319
•
DOI:
- 10.1103/PRXQuantum.1.020319

[10]

The theory of variational hybrid quantum-classical algorithms

Jarrod R. McClean
(
- LBNL, Berkeley
)
,
Jonathan Romero
(
- Harvard U. (main)
)
,
Ryan Babbush
(
- Unlisted, US, CA
)
,
Alán Aspuru-Guzik
(
- Harvard U. (main)
)

- New J.Phys. 18 (2016) 2, 023023
•
e-Print:
- 1509.04279
•
DOI:
- 10.1088/1367-2630/18/2/023023

[11]

Quantum Algorithms for Quantum Chemistry and Quantum Materials Science

- Chem.Rev. 120 (2020) 22, 12685-12717
•
e-Print:
- 2001.03685
•
DOI:
- 10.1021/acs.chemrev.9b00829

[12]

Alain Delgado, Juan Miguel Arrazola, Soran Jahangiri, Zeyue Niu, Josh Izaac, Chase Roberts, and Nathan Killoran. Variational quantum algorithm for molecular geometry optimization

- Phys.Rev.A 104 (2021) 052402

[13]

Variational-quantum-eigensolver–inspired optimization for spin-chain work extraction

- Phys.Rev.A 110 (2024) 1, 012443
•
e-Print:
- 2310.07617
•
DOI:
- 10.1103/PhysRevA.110.012443

[14]

Variational quantum algorithm for ergotropy estimation in quantum many-body batteries

et al.

- Phys.Rev.Res. 6 (2024) 1, 013038
•
e-Print:
- 2308.03334
•
DOI:
- 10.1103/PhysRevResearch.6.013038

[15]

Guillaume Verdon, Jacob Marks, Sasha Nanda, Stefan Leichenauer, and Jack Hidary. Quantum hamiltonianbased models and the variational quantum thermalizer algorithm

[16]

Variational Gibbs state preparation on noisy intermediate-scale quantum devices

Mirko Consiglio
(
- Malta U.
)
,
Jacopo Settino
(
- Calabria U. and
- INFN, Cosenza
)
,
Andrea Giordano
(
- Calabria U.
)
,
Carlo Mastroianni
(
- Calabria U.
)
,
Francesco Plastina
(
- Calabria U. and
- INFN, Cosenza
)

et al.

- Phys.Rev.A 110 (2024) 1, 012445
•
e-Print:
- 2303.11276
•
DOI:
- 10.1103/PhysRevA.110.012445

[17]

Adaptive variational algorithms for quantum Gibbs state preparation

Ada Warren
(
- Virginia Tech.
)
,
Linghua Zhu
(
- Virginia Tech.
)
,
Nicholas J. Mayhall
(
- Virginia Tech.
)
,
Edwin Barnes
(
- Virginia Tech.
)
,
Sophia E. Economou
(
- Virginia Tech.
)

e-Print:
- 2203.12757

[18]

Ana Clara das Neves Silva and Clebson Cruz. Simulating thermodynamic properties of dinuclear metal complexes using variational quantum algorithms

[19]

Machine learning phase transitions with a quantum processor

A.V. Uvarov
(
- Cambridge U., DAMTP
)
,
A.S. Kardashin
(
- Cambridge U., DAMTP
)
,
J.D. Biamonte
(
- Cambridge U., DAMTP
)

- Phys.Rev.A 102 (2020) 1, 012415
•
DOI:
- 10.1103/PhysRevA.102.012415

[20]

Askery Canabarro

Taysa M. Mendonça

[21]

Variational quantum eigensolver with linear depth problem-inspired ansatz for solving portfolio optimization in finance

et al.

e-Print:
- 2403.04296

[22]

Sebastian Brandhofer, Daniel Braun, Vanessa Dehn, Gerhard Hellstern, Matthias Hüls, Yanjun Ji, Ilia Polian, Amandeep Singh Bhatia, and Thomas Wellens. Benchmarking the performance of portfolio optimization with QAOA. Quantum Information Processing, 22(1), December

[23]

Practical Quantum Search by Variational Quantum Eigensolver on Noisy Intermediate-Scale Quantum Hardware

Chen-Yu Liu
(
- Taiwan, Natl. Taiwan U.
)

[24]

Vojtěch Havlíček

Antonio D. Córcoles

[25]

Jacob Biamonte, Peter Wittek, Nicola Pancotti, Patrick Rebentrost, Nathan Wiebe, and Seth Lloyd. Quantum machine learning. Nature, 549(7671):195-202

1-25 of 73
1
2
3
25 / page