{"id":"https://openalex.org/W7135195565","doi":"https://doi.org/10.48550/arxiv.2603.12098","title":"Maximum-Entropy Random Walks on Hypergraphs","display_name":"Maximum-Entropy Random Walks on Hypergraphs","publication_year":2026,"publication_date":"2026-03-12","ids":{"openalex":"https://openalex.org/W7135195565","doi":"https://doi.org/10.48550/arxiv.2603.12098"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.12098","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.12098","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.12098","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129041573","display_name":"Anqi Dong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dong, Anqi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102712851","display_name":"Anzhi Sheng","orcid":"https://orcid.org/0000-0002-6044-707X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sheng, Anzhi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114728193","display_name":"Xin Mao","orcid":"https://orcid.org/0000-0002-2801-9761"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mao, Xin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5128961717","display_name":"Can Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Can","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.45829999446868896,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.45829999446868896,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.29660001397132874,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11896","display_name":"Opportunistic and Delay-Tolerant Networks","score":0.03590000048279762,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/random-walk","display_name":"Random walk","score":0.763700008392334},{"id":"https://openalex.org/keywords/multiplicative-function","display_name":"Multiplicative function","score":0.600600004196167},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5716999769210815},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.42010000348091125},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.4092999994754791},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.3982999920845032},{"id":"https://openalex.org/keywords/scaling","display_name":"Scaling","score":0.3871000111103058},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.3790000081062317}],"concepts":[{"id":"https://openalex.org/C121194460","wikidata":"https://www.wikidata.org/wiki/Q856741","display_name":"Random walk","level":2,"score":0.763700008392334},{"id":"https://openalex.org/C42747912","wikidata":"https://www.wikidata.org/wiki/Q1048447","display_name":"Multiplicative function","level":2,"score":0.600600004196167},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5716999769210815},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5313000082969666},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.42010000348091125},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.4092999994754791},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.3982999920845032},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.3871000111103058},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.38029998540878296},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.3790000081062317},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.35690000653266907},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.34950000047683716},{"id":"https://openalex.org/C90119067","wikidata":"https://www.wikidata.org/wiki/Q43260","display_name":"Polynomial","level":2,"score":0.3248000144958496},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.3190000057220459},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.30379998683929443},{"id":"https://openalex.org/C43711488","wikidata":"https://www.wikidata.org/wiki/Q7534783","display_name":"Skew","level":2,"score":0.2922999858856201},{"id":"https://openalex.org/C110157686","wikidata":"https://www.wikidata.org/wiki/Q922122","display_name":"Broadcasting (networking)","level":2,"score":0.2897999882698059},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2856999933719635},{"id":"https://openalex.org/C125112378","wikidata":"https://www.wikidata.org/wiki/Q176640","display_name":"Randomness","level":2,"score":0.27480000257492065},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.2718000113964081},{"id":"https://openalex.org/C2777759810","wikidata":"https://www.wikidata.org/wiki/Q149316","display_name":"Lemma (botany)","level":3,"score":0.27000001072883606},{"id":"https://openalex.org/C106286213","wikidata":"https://www.wikidata.org/wiki/Q898572","display_name":"Matroid","level":2,"score":0.2596000134944916},{"id":"https://openalex.org/C8272713","wikidata":"https://www.wikidata.org/wiki/Q176737","display_name":"Stochastic process","level":2,"score":0.2574000060558319},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.25619998574256897}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.12098","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.12098","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.12098","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.12098","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.6127833127975464,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Random":[0],"walks":[1,21],"are":[2],"fundamental":[3],"tools":[4],"for":[5,144,150],"analyzing":[6],"complex":[7,65],"networked":[8],"systems,":[9,14],"including":[10,140],"social":[11],"networks,":[12],"biological":[13],"and":[15,93,118,146,165],"communication":[16],"infrastructures.":[17],"While":[18],"classical":[19],"random":[20,37,74],"focus":[22,43],"on":[23,40,44,77],"pairwise":[24],"interactions,":[25],"many":[26],"real-world":[27,166],"systems":[28],"exhibit":[29],"higher-order":[30],"interactions":[31],"naturally":[32],"modeled":[33],"by":[34],"hypergraphs.":[35],"Existing":[36],"walk":[38,75],"models":[39],"hypergraphs":[41,79],"often":[42],"undirected":[45],"structures":[46],"or":[47,61],"do":[48],"not":[49],"incorporate":[50],"entropy-based":[51],"inference,":[52],"limiting":[53],"their":[54],"ability":[55],"to":[56],"capture":[57],"directional":[58],"flows,":[59],"uncertainty,":[60],"information":[62],"diffusion":[63],"in":[64,153],"systems.":[66],"In":[67],"this":[68],"article,":[69],"we":[70],"develop":[71],"a":[72,86,101,106,110,125],"maximum-entropy":[73],"framework":[76,159],"directed":[78],"with":[80,133,162],"two":[81],"interaction":[82],"mechanisms:":[83],"broadcasting":[84,145],"where":[85,95],"pivot":[87,97],"node":[88],"activates":[89],"multiple":[90,96],"receiver":[91,102],"nodes":[92,98],"merging":[94],"jointly":[99],"influence":[100],"node.":[103],"We":[104,136],"infer":[105],"transition":[107],"kernel":[108],"via":[109],"Kullback--Leibler":[111],"divergence":[112],"projection":[113],"onto":[114],"constraints":[115],"enforcing":[116],"stochasticity":[117],"stationarity.":[119],"The":[120,155],"resulting":[121],"optimality":[122],"conditions":[123],"yield":[124],"multiplicative":[126],"scaling":[127],"form,":[128],"implemented":[129],"using":[130],"Sinkhorn--Schr\u00f6dinger-type":[131],"iterations":[132],"tensor":[134,147],"contractions.":[135],"further":[137],"analyze":[138],"ergodicity,":[139],"projected":[141],"linear":[142],"kernels":[143],"spectral":[148],"criteria":[149],"polynomial":[151],"dynamics":[152],"merging.":[154],"effectiveness":[156],"of":[157],"our":[158],"is":[160],"demonstrated":[161],"both":[163],"synthetic":[164],"examples.":[167]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-14T00:00:00"}