{"id":"https://openalex.org/W7165726656","doi":"https://doi.org/10.48550/arxiv.2606.24421","title":"Can Aggregate Invariants Accelerate Continuous Subgraph Matching? Limits, Laws, and a Dynamic Spectral Index","display_name":"Can Aggregate Invariants Accelerate Continuous Subgraph Matching? Limits, Laws, and a Dynamic Spectral Index","publication_year":2026,"publication_date":"2026-06-23","ids":{"openalex":"https://openalex.org/W7165726656","doi":"https://doi.org/10.48550/arxiv.2606.24421"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.24421","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.24421","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":null,"license_id":null,"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.2606.24421","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100730798","display_name":"Minghao Chen","orcid":"https://orcid.org/0000-0001-7709-7355"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Minghao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5028129695","display_name":"Jiale Zheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zheng, Jiale","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/T12292","display_name":"Graph Theory and Algorithms","score":0.7698000073432922,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12292","display_name":"Graph Theory and Algorithms","score":0.7698000073432922,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.1535000056028366,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10720","display_name":"Complexity and Algorithms in Graphs","score":0.015799999237060547,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/pruning","display_name":"Pruning","score":0.5837000012397766},{"id":"https://openalex.org/keywords/aggregate","display_name":"Aggregate (composite)","score":0.505299985408783},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4575999975204468},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.4325000047683716},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4300999939441681},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.3968000113964081},{"id":"https://openalex.org/keywords/degeneracy","display_name":"Degeneracy (biology)","score":0.3747999966144562},{"id":"https://openalex.org/keywords/laplacian-matrix","display_name":"Laplacian matrix","score":0.35899999737739563},{"id":"https://openalex.org/keywords/bipartite-graph","display_name":"Bipartite graph","score":0.3562000095844269}],"concepts":[{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.5837000012397766},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5152000188827515},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.505299985408783},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.47679999470710754},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4575999975204468},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.4325000047683716},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4300999939441681},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.42399999499320984},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.3968000113964081},{"id":"https://openalex.org/C2777727622","wikidata":"https://www.wikidata.org/wiki/Q5251772","display_name":"Degeneracy (biology)","level":2,"score":0.3747999966144562},{"id":"https://openalex.org/C115178988","wikidata":"https://www.wikidata.org/wiki/Q772067","display_name":"Laplacian matrix","level":3,"score":0.35899999737739563},{"id":"https://openalex.org/C197657726","wikidata":"https://www.wikidata.org/wiki/Q174733","display_name":"Bipartite graph","level":3,"score":0.3562000095844269},{"id":"https://openalex.org/C165700671","wikidata":"https://www.wikidata.org/wiki/Q203484","display_name":"Laplace operator","level":2,"score":0.3488999903202057},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.3395000100135803},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.3109999895095825},{"id":"https://openalex.org/C168773036","wikidata":"https://www.wikidata.org/wiki/Q264164","display_name":"Recursion (computer science)","level":2,"score":0.31040000915527344},{"id":"https://openalex.org/C149629883","wikidata":"https://www.wikidata.org/wiki/Q660926","display_name":"Fraction (chemistry)","level":2,"score":0.3100999891757965},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.29919999837875366},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.29409998655319214},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2930999994277954},{"id":"https://openalex.org/C156340839","wikidata":"https://www.wikidata.org/wiki/Q2704791","display_name":"Enumeration","level":2,"score":0.28459998965263367},{"id":"https://openalex.org/C176641082","wikidata":"https://www.wikidata.org/wiki/Q2446767","display_name":"Spectral signature","level":2,"score":0.2822999954223633},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.2761000096797943},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.27250000834465027},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.27250000834465027},{"id":"https://openalex.org/C205606062","wikidata":"https://www.wikidata.org/wiki/Q5249645","display_name":"Decoupling (probability)","level":2,"score":0.2712000012397766},{"id":"https://openalex.org/C160403385","wikidata":"https://www.wikidata.org/wiki/Q220543","display_name":"Queue","level":2,"score":0.2676999866962433},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.25119999051094055},{"id":"https://openalex.org/C2776029896","wikidata":"https://www.wikidata.org/wiki/Q3935810","display_name":"Relaxation (psychology)","level":2,"score":0.25099998712539673}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.24421","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.24421","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.24421","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.24421","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Spectral":[0],"filtering":[1],"recently":[2],"delivered":[3],"substantial":[4],"pruning":[5,51,73,86],"for":[6,212],"\\emph{static}":[7],"subgraph":[8,30],"matching:":[9],"Laplacian":[10],"interlacing":[11],"rejects":[12],"candidates":[13,136],"whose":[14],"neighborhoods":[15],"cannot":[16],"host":[17],"the":[18,56,129,153,179,182],"query.":[19],"We":[20,207],"study":[21],"whether":[22],"such":[23],"aggregate":[24],"structural":[25],"tests":[26,130,192],"can":[27],"accelerate":[28,193],"\\emph{continuous}":[29],"matching":[31],"(CSM)":[32],"over":[33,60],"dynamic":[34,220],"graphs,":[35,166],"and":[36,65,88,170,216],"answer":[37],"in":[38],"three":[39],"parts.":[40],"First,":[41],"lazily":[42],"maintained":[43],"spectral":[44,50],"bounds":[45],"are":[46,91],"infeasible":[47],"exactly":[48],"where":[49],"has":[52],"value:":[53],"we":[54],"characterize":[55],"tightest":[57],"safe":[58],"rule":[59],"a":[61,121,174,218],"formalized":[62],"perturbation":[63],"relaxation":[64],"show":[66],"that":[67],"even":[68],"it":[69],"loses":[70],"essentially":[71],"all":[72],"power":[74],"within":[75],"four":[76,164],"touching":[77],"updates.":[78],"Second,":[79],"exact":[80,108],"maintenance":[81],"is":[82],"affordable":[83],"when":[84,184],"selective:":[85],"utility":[87],"recomputation":[89],"cost":[90],"anti-correlated":[92],"across":[93,161],"vertices":[94],"--":[95,100,151,160,199,203],"hubs":[96],"provably":[97],"never":[98,204],"prune":[99],"so":[101],"recomputing":[102],"small-neighborhood":[103],"spectra":[104,110],"on":[105],"touch":[106],"sustains":[107],"local":[109],"at":[111],"microseconds":[112],"per":[113],"update,":[114],"complete":[115],"by":[116],"construction.":[117],"Third,":[118],"integrated":[119],"into":[120],"decoupled":[122],"CSM":[123,214],"benchmark":[124],"against":[125],"an":[126,209],"identical-minus-spectra":[127],"control,":[128],"remove":[131],"up":[132,140],"to":[133,141],"$51\\%$":[134],"of":[135,143],"or":[137],"safely":[138],"skip":[139],"$47\\%$":[142],"update":[144],"enumerations,":[145],"yet":[146],"enumeration":[147],"intermediates":[148],"remain":[149],"unchanged":[150],"beyond":[152],"gates'":[154],"skipped":[155],"first-level":[156],"bindings,":[157],"typically":[158],"zero":[159],"two":[162,167],"engines,":[163],"real":[165],"stream":[168],"types,":[169],"$77$":[171],"solved":[172],"queries;":[173],"constructed":[175],"radius-stratified":[176],"workload":[177],"confirms":[178],"instrument":[180],"detects":[181],"exception":[183],"one":[185],"exists":[186],"($-99.9\\%$":[187],"intermediates,":[188],"$748\\times$":[189],"faster).":[190],"Aggregate":[191],"what":[194],"scales":[195],"with":[196],"candidate":[197],"sets":[198],"construction,":[200],"list":[201],"scans":[202],"adjacency-guided":[205],"exploration.":[206],"distill":[208],"intermediate-invariance":[210],"methodology":[211],"evaluating":[213],"filters":[215],"release":[217],"reusable":[219],"local-spectra":[221],"index.":[222]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-25T00:00:00"}
