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Detecting multiple communities using quantum annealing on the D-Wave system.

Christian F A Negre1, Hayato Ushijima-Mwesigwa2, Susan M Mniszewski2

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Summary
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Quantum annealers can detect communities in networks. This study explores using quantum computing for community detection, finding it effective for identifying two or more communities in complex networks.

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Area of Science:

  • Combinatorial Optimization
  • Network Science
  • Quantum Computing

Background:

  • Community detection identifies densely connected groups in networks, crucial for understanding complex systems in various scientific fields.
  • The challenge lies in simultaneously determining the number of communities and their membership, increasing computational complexity.
  • High-quality community partitioning is vital for explaining phenomena, even with small, isolated communities.

Purpose of the Study:

  • To explore the application of quantum annealers for community detection in networks.
  • To systematically investigate the capability of quantum annealers in identifying two or more communities.
  • To assess the suitability of quantum annealer architecture for community detection problems.

Main Methods:

  • Utilized quantum annealers, specifically D-Wave 2X and 2000Q machines.
  • Adapted the community detection problem to fit the quantum annealer architecture.
  • Conducted a systematic study on detecting multiple communities.

Main Results:

  • The problem of detecting up to two communities maps naturally onto quantum annealer architecture.
  • Demonstrated the potential of quantum annealers for network community detection.
  • Explored the systematic detection of two or more communities.

Conclusions:

  • Quantum annealers offer a promising approach for community detection.
  • The architecture is well-suited for detecting at least two communities with minimal reformulation.
  • Further systematic studies are warranted for complex community structures.