{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/quantum-transport-senses-community-structure","title":"Quantum transport senses community structure in networks","arxiv_id":"1711.04979","date":"2017-11-14","proceeding":null,"authors":["Chenchao Zhao","Jun S. Song"],"abstract":"Quantum time evolution exhibits rich physics, attributable to the interplay\nbetween the density and phase of a wave function. However, unlike classical\nheat diffusion, the wave nature of quantum mechanics has not yet been\nextensively explored in modern data analysis. We propose that the Laplace\ntransform of quantum transport (QT) can be used to construct an ensemble of\nmaps from a given complex network to a circle $S^1$, such that closely-related\nnodes on the network are grouped into sharply concentrated clusters on $S^1$.\nThe resulting QT clustering (QTC) algorithm is as powerful as the\nstate-of-the-art spectral clustering in discerning complex geometric patterns\nand more robust when clusters show strong density variations or heterogeneity\nin size. The observed phenomenon of QTC can be interpreted as a collective\nbehavior of the microscopic nodes that evolve as macroscopic cluster orbitals\nin an effective tight-binding model recapitulating the network. Python source\ncode implementing the algorithm and examples are available at\nhttps://github.com/jssong-lab/QTC.","url_abs":"http://arxiv.org/abs/1711.04979v2","url_pdf":"http://arxiv.org/pdf/1711.04979v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"quantum-transport-senses-community-structure","repo_url":"https://github.com/jssong-lab/QTC","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"clustering","task_name":"Clustering"}],"methods":[{"method_slug":"spectral-clustering","method_name":"Spectral Clustering"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}