Standard
Solving Large Maximum Clique Problems on a Quantum Annealer. / Pelofske, Elijah
; Hahn, Georg; Djidjev, Hristo.
Quantum Technology and Optimization Problems - 1st International Workshop, QTOP 2019, Proceedings. ed. / Sebastian Feld; Claudia Linnhoff-Popien. Springer-Verlag, 2019. p. 123-135 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11413 LNCS).
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Harvard
Pelofske, E
, Hahn, G & Djidjev, H 2019,
Solving Large Maximum Clique Problems on a Quantum Annealer. in S Feld & C Linnhoff-Popien (eds),
Quantum Technology and Optimization Problems - 1st International Workshop, QTOP 2019, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11413 LNCS, Springer-Verlag, pp. 123-135, 1st International Workshop on Quantum Technology and Optimization Problems, QTOP 2019 was held in conjunction with the International Conference on Networked Systems, NetSys 2019, Munich, Germany,
18/03/19.
https://doi.org/10.1007/978-3-030-14082-3_11APA
Vancouver
Pelofske E
, Hahn G, Djidjev H.
Solving Large Maximum Clique Problems on a Quantum Annealer. In Feld S, Linnhoff-Popien C, editors, Quantum Technology and Optimization Problems - 1st International Workshop, QTOP 2019, Proceedings. Springer-Verlag. 2019. p. 123-135. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-14082-3_11
Author
Pelofske, Elijah
; Hahn, Georg ; Djidjev, Hristo. /
Solving Large Maximum Clique Problems on a Quantum Annealer. Quantum Technology and Optimization Problems - 1st International Workshop, QTOP 2019, Proceedings. editor / Sebastian Feld ; Claudia Linnhoff-Popien. Springer-Verlag, 2019. pp. 123-135 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
Bibtex
@inproceedings{cb8c2efbbc3c4ab8b1b84e41a6abd7e9,
title = "Solving Large Maximum Clique Problems on a Quantum Annealer",
abstract = "Commercial quantum annealers from D-Wave Systems can find high quality solutions of quadratic unconstrained binary optimization problems that can be embedded onto its hardware. However, even though such devices currently offer up to 2048 qubits, due to limitations on the connectivity of those qubits, the size of problems that can typically be solved is rather small (around 65 variables). This limitation poses a problem for using D-Wave machines to solve application-relevant problems, which can have thousands of variables. For the important Maximum Clique problem, this article investigates methods for decomposing larger problem instances into smaller ones, which can subsequently be solved on D-Wave. During the decomposition, we aim to prune as many generated subproblems that don{\textquoteright}t contribute to the solution as possible, in order to reduce the computational complexity. The reduction methods presented in this article include upper and lower bound heuristics in conjunction with graph decomposition, vertex and edge extraction, and persistency analysis.",
keywords = "Branch-and-bound, D-Wave, Decomposition, Graph algorithms, Maximum clique, Optimization, Quantum annealing",
author = "Elijah Pelofske and Georg Hahn and Hristo Djidjev",
year = "2019",
month = jan,
day = "1",
doi = "10.1007/978-3-030-14082-3_11",
language = "English",
isbn = "9783030140816",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer-Verlag",
pages = "123--135",
editor = "Sebastian Feld and Claudia Linnhoff-Popien",
booktitle = "Quantum Technology and Optimization Problems - 1st International Workshop, QTOP 2019, Proceedings",
note = "1st International Workshop on Quantum Technology and Optimization Problems, QTOP 2019 was held in conjunction with the International Conference on Networked Systems, NetSys 2019 ; Conference date: 18-03-2019 Through 18-03-2019",
}
RIS
TY - GEN
T1 - Solving Large Maximum Clique Problems on a Quantum Annealer
AU - Pelofske, Elijah
AU - Hahn, Georg
AU - Djidjev, Hristo
PY - 2019/1/1
Y1 - 2019/1/1
N2 - Commercial quantum annealers from D-Wave Systems can find high quality solutions of quadratic unconstrained binary optimization problems that can be embedded onto its hardware. However, even though such devices currently offer up to 2048 qubits, due to limitations on the connectivity of those qubits, the size of problems that can typically be solved is rather small (around 65 variables). This limitation poses a problem for using D-Wave machines to solve application-relevant problems, which can have thousands of variables. For the important Maximum Clique problem, this article investigates methods for decomposing larger problem instances into smaller ones, which can subsequently be solved on D-Wave. During the decomposition, we aim to prune as many generated subproblems that don’t contribute to the solution as possible, in order to reduce the computational complexity. The reduction methods presented in this article include upper and lower bound heuristics in conjunction with graph decomposition, vertex and edge extraction, and persistency analysis.
AB - Commercial quantum annealers from D-Wave Systems can find high quality solutions of quadratic unconstrained binary optimization problems that can be embedded onto its hardware. However, even though such devices currently offer up to 2048 qubits, due to limitations on the connectivity of those qubits, the size of problems that can typically be solved is rather small (around 65 variables). This limitation poses a problem for using D-Wave machines to solve application-relevant problems, which can have thousands of variables. For the important Maximum Clique problem, this article investigates methods for decomposing larger problem instances into smaller ones, which can subsequently be solved on D-Wave. During the decomposition, we aim to prune as many generated subproblems that don’t contribute to the solution as possible, in order to reduce the computational complexity. The reduction methods presented in this article include upper and lower bound heuristics in conjunction with graph decomposition, vertex and edge extraction, and persistency analysis.
KW - Branch-and-bound
KW - D-Wave
KW - Decomposition
KW - Graph algorithms
KW - Maximum clique
KW - Optimization
KW - Quantum annealing
U2 - 10.1007/978-3-030-14082-3_11
DO - 10.1007/978-3-030-14082-3_11
M3 - Conference contribution/Paper
AN - SCOPUS:85064037597
SN - 9783030140816
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 123
EP - 135
BT - Quantum Technology and Optimization Problems - 1st International Workshop, QTOP 2019, Proceedings
A2 - Feld, Sebastian
A2 - Linnhoff-Popien, Claudia
PB - Springer-Verlag
T2 - 1st International Workshop on Quantum Technology and Optimization Problems, QTOP 2019 was held in conjunction with the International Conference on Networked Systems, NetSys 2019
Y2 - 18 March 2019 through 18 March 2019
ER -
