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A short review on the maximum clique problem algorithms with classical, AI, and quantum methods

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arxiv 2403.09742 v2 pith:EIBOK7F6 submitted 2024-03-13 cs.AI cond-mat.dis-nncs.DScs.LGmath.OCquant-ph

Raffaele Marino , Lorenzo Buffoni , Bogdan Zavalnij This is my paper · ORCID
classification cs.AIcond-mat.dis-nncs.DScs.LGmath.OCquant-ph
keywords reviewalgorithmsproblemclassicalcliquegraphmanuscriptmaximum
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This manuscript provides a comprehensive review of the Maximum Clique Problem, a computational problem that involves finding subsets of vertices in a graph that are all pairwise adjacent to each other. As such, this review is a continuation of the series of previous reviews from 1994, 1999 and 2014. The manuscript covers in a simple way classical algorithms and includes a review of recent developments in graph neural networks and quantum algorithms.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Efficient Maximum Clique Detection via Grover's Algorithm with Real-time Global Size Tracking

    quant-ph 2025-09 reject novelty 4.0 of 10

    A proposed Grover-based maximum clique solver claims O(sqrt(2^n)) iterations and O(1) measurements by pre-encoding the clique size, but the pre-encoding itself costs exponentially many gates and is excluded from the h...

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