Detecting multiple communities using quantum annealing on the D-Wave system
Open accessAbstract
A very important problem in combinatorial optimization is the partitioning of a network into communities of densely connected nodes; where the connectivity between nodes inside a particular community is large compared to the connectivity between nodes belonging to different ones. This problem is known as community detection, and has become very important in various fields of science including chemistry, biology and social sciences. The problem of community detection is a twofold problem that consists of determining the number of communities and, at the same time, finding those communities. This drastically increases the solution space for heuristics to work on, compared to traditional graph partitioning problems. In many of the scientific domains in which graphs are used, there is the need to have the ability to partition a graph into communities with the "highest quality" possible since the presence of even small isolated communities can become crucial to explain a particular phenomenon. We have explored community detection using the power of quantum annealers, and in particular the D-Wave 2X and 2000Q machines. It turns out that the problem of detecting at most two communities naturally fits into the architecture of a quantum annealer with almost no need of reformulation. This paper addresses a systematic study of detecting two or more communities in a network using a quantum annealer.
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QUBO formulations have been provided for the graph coloring problem, the k-community detection problem, the Maximum Independent Set problem, the Minimum Multicut problem, the most frequent itemset problem, consensus clustering, the online advertisement allocation problem, traffic signal optimization on a square lattice, the Multi-depot Capacitated Vehicle Routing problem in its static and dynamic版
“QUBO formulations for the graph coloring problem [126], the k-community detection problem [101], the Maximum Independent Set problem [148], the Minimum Multicut problem [34], the most frequent itemset problem [103], consensus clustering [32],”
From Quantum Combinatorial Optimization in the NISQ Era: A Systematic Mapping Study (2024) · cites this paper as [101]
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References 42 · Cited by 80
Research works printed but not linked: 2
- [33]Harris HSL David Money. 3.4.2 State Encodings. Elsevier; 2007. Available from: https://app.knovel.com/hotlink/khtml/id:kt009519R3/digital-design-computer/state-encodings.
- [38]Lanting T, Przybysz AJ, Smirnov AY, Spedalieri FM, Amin MH, Berkley AJ, et al Entanglement in a Quantum Annealing Processor. Phys Rev X. 2014; 4: 021041.
- Authors
- Negre, C. F. A., Ushijima-Mwesigwa, H., & Mniszewski, S. M.
- Affiliations
- Los Alamos National Laboratory (US)
- Corresponding author
- Mniszewski, Susan M.
- Venue
- PLOS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2020-02-13
- Volume
- 15
- Issue
- 2
- Pages
- e0227538
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC7018001
- OpenAlex
- W3005644271
- Cited by
- 80
- References
- 42
- Citations by year
- 2026: 5 · 2025: 6 · 2024: 14 · 2023: 15 · 2022: 17 · 2021: 8 · 2020: 8 · 2019: 6 · 2018: 1
- FWCI
- 4.72
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- public-domain
- creativecommons.org/publicdomain/zero/1.0/ (vor)
- Locations
- PLoS ONE (publishedVersion, public-domain)
- Europe PMC (PubMed Central) (publishedVersion, public-domain)
- PubMed Central (publishedVersion, public-domain)
- PubMed (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- arXiv (Cornell University)
- Funders
- U.S. Department of Energy (Contract No. 89233218NCA000001, 89233218NCA000001)
- National Nuclear Security Administration (89233218NCA000001)
- Laboratory Directed Research and Development (89233218NCA000001)
- Los Alamos National Laboratory (89233218NCA000001, Contract No. 89233218NCA000001)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Quantum Computing Algorithms and Architecture
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Complexity and Algorithms in Graphs
- Keywords
- community detection, quantum annealing, D-Wave quantum annealer, combinatorial optimization, graph partitioning, network partitioning, number of communities, quantum annealing hardware
- MeSH terms
- Algorithms, Models, Molecular, Proteins, Quantum Theory, Martial Arts
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