Hybrid Quantum Solvers in Production: How to Succeed in the NISQ Era?

Eneko Osaba; Esther Villar-Rodríguez; Aitor Gomez-Tejedor; Izaskun Oregi

doi:10.1007/978-3-031-77738-7_35

Hybrid Quantum Solvers in Production: How to Succeed in the NISQ Era?

Eneko Osaba^*
, Esther Villar-Rodríguez
, Aitor Gomez-Tejedor
, Izaskun Oregi

^*Corresponding author for this work

Quantum

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5 Citations (Scopus)

Abstract

Hybrid quantum computing is considered the present and the future within the field of quantum computing. Far from being a passing fad, this trend cannot be considered just a stopgap to address the limitations of NISQ-era devices. The foundations linking both computing paradigms will remain robust over time. The contribution of this work is twofold: first, we describe and categorize some of the most frequently used hybrid solvers, resorting to two different taxonomies recently published in the literature. Secondly, we put a special focus on two solvers that are currently deployed in real production and that have demonstrated to be near the real industry. These solvers are the LeapHybridBQMSampler contained in D-Wave’s Hybrid Solver Service and Quantagonia’s Hybrid Solver. We analyze the performance of both methods using as benchmarks four combinatorial optimization problems.

Original language	English
Title of host publication	Intelligent Data Engineering and Automated Learning – IDEAL 2024 - 25th International Conference, Proceedings
Editors	Vicente Julian, David Camacho, Hujun Yin, Juan M. Alberola, Vitor Beires Nogueira, Paulo Novais, Antonio Tallón-Ballesteros
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	423-434
Number of pages	12
ISBN (Print)	9783031777370
DOIs	https://doi.org/10.1007/978-3-031-77738-7_35
Publication status	Published - 2025
Event	25th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2024 - Valencia, Spain Duration: 20 Nov 2024 → 22 Nov 2024

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	15347 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	25th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2024
Country/Territory	Spain
City	Valencia
Period	20/11/24 → 22/11/24

Keywords

Combinatorial Optimization
D-Wave
Hybrid Quantum-Classical Computing
Quantagonia
Quantum Computing

Access to Document

10.1007/978-3-031-77738-7_35

Cite this

Osaba, E., Villar-Rodríguez, E., Gomez-Tejedor, A., & Oregi, I. (2025). Hybrid Quantum Solvers in Production: How to Succeed in the NISQ Era? In V. Julian, D. Camacho, H. Yin, J. M. Alberola, V. B. Nogueira, P. Novais, & A. Tallón-Ballesteros (Eds.), Intelligent Data Engineering and Automated Learning – IDEAL 2024 - 25th International Conference, Proceedings (pp. 423-434). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 15347 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-77738-7_35

Osaba, Eneko ; Villar-Rodríguez, Esther ; Gomez-Tejedor, Aitor et al. / Hybrid Quantum Solvers in Production : How to Succeed in the NISQ Era?. Intelligent Data Engineering and Automated Learning – IDEAL 2024 - 25th International Conference, Proceedings. editor / Vicente Julian ; David Camacho ; Hujun Yin ; Juan M. Alberola ; Vitor Beires Nogueira ; Paulo Novais ; Antonio Tallón-Ballesteros. Springer Science and Business Media Deutschland GmbH, 2025. pp. 423-434 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Hybrid Quantum Solvers in Production: How to Succeed in the NISQ Era?",

abstract = "Hybrid quantum computing is considered the present and the future within the field of quantum computing. Far from being a passing fad, this trend cannot be considered just a stopgap to address the limitations of NISQ-era devices. The foundations linking both computing paradigms will remain robust over time. The contribution of this work is twofold: first, we describe and categorize some of the most frequently used hybrid solvers, resorting to two different taxonomies recently published in the literature. Secondly, we put a special focus on two solvers that are currently deployed in real production and that have demonstrated to be near the real industry. These solvers are the LeapHybridBQMSampler contained in D-Wave{\textquoteright}s Hybrid Solver Service and Quantagonia{\textquoteright}s Hybrid Solver. We analyze the performance of both methods using as benchmarks four combinatorial optimization problems.",

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author = "Eneko Osaba and Esther Villar-Rodr{\'i}guez and Aitor Gomez-Tejedor and Izaskun Oregi",

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Osaba, E , Villar-Rodríguez, E, Gomez-Tejedor, A & Oregi, I 2025, Hybrid Quantum Solvers in Production: How to Succeed in the NISQ Era? in V Julian, D Camacho, H Yin, JM Alberola, VB Nogueira, P Novais & A Tallón-Ballesteros (eds), Intelligent Data Engineering and Automated Learning – IDEAL 2024 - 25th International Conference, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 15347 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 423-434, 25th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2024, Valencia, Spain, 20/11/24. https://doi.org/10.1007/978-3-031-77738-7_35

Hybrid Quantum Solvers in Production: How to Succeed in the NISQ Era? / Osaba, Eneko ; Villar-Rodríguez, Esther; Gomez-Tejedor, Aitor et al.
Intelligent Data Engineering and Automated Learning – IDEAL 2024 - 25th International Conference, Proceedings. ed. / Vicente Julian; David Camacho; Hujun Yin; Juan M. Alberola; Vitor Beires Nogueira; Paulo Novais; Antonio Tallón-Ballesteros. Springer Science and Business Media Deutschland GmbH, 2025. p. 423-434 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 15347 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Hybrid Quantum Solvers in Production

T2 - 25th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2024

AU - Osaba, Eneko

AU - Villar-Rodríguez, Esther

AU - Gomez-Tejedor, Aitor

AU - Oregi, Izaskun

N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

PY - 2025

Y1 - 2025

N2 - Hybrid quantum computing is considered the present and the future within the field of quantum computing. Far from being a passing fad, this trend cannot be considered just a stopgap to address the limitations of NISQ-era devices. The foundations linking both computing paradigms will remain robust over time. The contribution of this work is twofold: first, we describe and categorize some of the most frequently used hybrid solvers, resorting to two different taxonomies recently published in the literature. Secondly, we put a special focus on two solvers that are currently deployed in real production and that have demonstrated to be near the real industry. These solvers are the LeapHybridBQMSampler contained in D-Wave’s Hybrid Solver Service and Quantagonia’s Hybrid Solver. We analyze the performance of both methods using as benchmarks four combinatorial optimization problems.

AB - Hybrid quantum computing is considered the present and the future within the field of quantum computing. Far from being a passing fad, this trend cannot be considered just a stopgap to address the limitations of NISQ-era devices. The foundations linking both computing paradigms will remain robust over time. The contribution of this work is twofold: first, we describe and categorize some of the most frequently used hybrid solvers, resorting to two different taxonomies recently published in the literature. Secondly, we put a special focus on two solvers that are currently deployed in real production and that have demonstrated to be near the real industry. These solvers are the LeapHybridBQMSampler contained in D-Wave’s Hybrid Solver Service and Quantagonia’s Hybrid Solver. We analyze the performance of both methods using as benchmarks four combinatorial optimization problems.

KW - Combinatorial Optimization

KW - D-Wave

KW - Hybrid Quantum-Classical Computing

KW - Quantagonia

KW - Quantum Computing

UR - https://www.scopus.com/pages/publications/85210849617

U2 - 10.1007/978-3-031-77738-7_35

DO - 10.1007/978-3-031-77738-7_35

M3 - Conference contribution

AN - SCOPUS:85210849617

SN - 9783031777370

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 423

EP - 434

BT - Intelligent Data Engineering and Automated Learning – IDEAL 2024 - 25th International Conference, Proceedings

A2 - Julian, Vicente

A2 - Camacho, David

A2 - Yin, Hujun

A2 - Alberola, Juan M.

A2 - Nogueira, Vitor Beires

A2 - Novais, Paulo

A2 - Tallón-Ballesteros, Antonio

PB - Springer Science and Business Media Deutschland GmbH

Y2 - 20 November 2024 through 22 November 2024

ER -

Osaba E , Villar-Rodríguez E, Gomez-Tejedor A, Oregi I. Hybrid Quantum Solvers in Production: How to Succeed in the NISQ Era? In Julian V, Camacho D, Yin H, Alberola JM, Nogueira VB, Novais P, Tallón-Ballesteros A, editors, Intelligent Data Engineering and Automated Learning – IDEAL 2024 - 25th International Conference, Proceedings. Springer Science and Business Media Deutschland GmbH. 2025. p. 423-434. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-031-77738-7_35

Hybrid Quantum Solvers in Production: How to Succeed in the NISQ Era?

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

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Results of Quantagonia's Hybrid Solver and D-Wave's LeapBQMHybrid Solver on the QOPTLib Optimization Benchmark

Cite this

Hybrid Quantum Solvers in Production: How to Succeed in the NISQ Era?

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Datasets

Results of Quantagonia's Hybrid Solver and D-Wave's LeapBQMHybrid Solver on the QOPTLib Optimization Benchmark

Cite this