aiqbench analysis
This research introduces a quantum algorithm specifically designed for path homology on directed graphs, offering significant computational speedups over classical methods for analyzing data with intrinsic directional structures. By establishing a universal encoding protocol and proving key theoretical properties, the study advances topological data analysis within the quantum computing domain. The results demonstrate that exponential speedup is achievable when path spaces are efficiently accessible, while standard inputs yield polynomial improvements.
Quantum Topological Analysis on Digraphs
arXiv:2509.13862v3 Announce Type: replace Abstract: Quantum algorithms for topological data analysis provide significant advantages over the best known classical algorithms. Unlike previous work on simplicial complexes built from point clouds, path homology on digraphs is defined for directed graphs and provides a natural topological framework for analyzing data with intrinsic directional structures. Path homology has become an emerging area in Topological Data Analysis (TDA), attracting increasing attention in recent years. We propose a quantum algorithm for path homology on digraphs that offers a significant advantage over the best known classical algorithms. We design a universal encoding protocol for the paths and boundary operators of digraphs on quantum systems. We prove a property of path homology that provides the theoretical guarantee for the algorithm. The speedup of the quantum algorithm for path homology depends on input-access assumptions. The exponential speedup arises when the path space can be efficiently accessed, while for standard digraph input the algorithm provides polynomial speedup.
Abstract:Quantum algorithms for topological data analysis provide significant advantages over the best known classical algorithms. Unlike previous work on simplicial complexes built from point clouds, path homology on digraphs is defined for directed graphs and provides a natural topological framework for analyzing data with intrinsic directional structures. Path homology has become an emerging area in Topological Data Analysis (TDA), attracting increasing attention in recent years. We propose a quantum algorithm for path homology on digraphs that offers a significant advantage over the best known classical algorithms. We design a universal encoding protocol for the paths and boundary operators of digraphs on quantum systems. We prove a property of path homology that provides the theoretical guarantee for the algorithm. The speedup of the quantum algorithm for path homology depends on input-access assumptions. The exponential speedup arises when the path space can be efficiently accessed, while for standard digraph input the algorithm provides polynomial speedup.
arXiv:2509.13862 [quant-ph]
(or arXiv:2509.13862v3 [quant-ph] for this version)
https://doi.org/10.48550/arXiv.2509.13862 Focus to learn more arXiv-issued DOI via DataCite
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