{"id":"https://openalex.org/W7213013117","doi":"https://doi.org/10.48550/arxiv.2609.12797","title":"The Wavelet Detection Filter: a real time unmodeled pipeline for gravitational wave transients, ranking coincidences with a graph neural network","display_name":"The Wavelet Detection Filter: a real time unmodeled pipeline for gravitational wave transients, ranking coincidences with a graph neural network","publication_year":2026,"publication_date":"2026-09-11","ids":{"openalex":"https://openalex.org/W7213013117","doi":"https://doi.org/10.48550/arxiv.2609.12797"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2609.12797","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.12797","pdf_url":"https://arxiv.org/pdf/2609.12797","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2609.12797","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5074113580","display_name":"E. Cuoco","orcid":"https://orcid.org/0000-0002-6528-3449","observed_orcids":["https://orcid.org/0000-0002-6528-3449"]},"institutions":[{"id":"https://openalex.org/I4210148700","display_name":"Istituto Nazionale di Fisica Nucleare, Sezione di Bologna","ror":"https://ror.org/04j0x0h93","country_code":"IT","type":"facility","lineage":["https://openalex.org/I160013858","https://openalex.org/I4210148700"]},{"id":"https://openalex.org/I9360294","display_name":"University of Bologna","ror":"https://ror.org/01111rn36","country_code":"IT","type":"education","lineage":["https://openalex.org/I9360294"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Cuoco, Elena","raw_affiliation_strings":["INFN , Sezione di Bologna , Viale C. Berti Pichat 6/2 , 40126 Bologna , Italy","Physics and Astronomy Department (DIFA) , Alma Mater Studiorum - Universit\u00e0 di Bologna , Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"INFN , Sezione di Bologna , Viale C. Berti Pichat 6/2 , 40126 Bologna , Italy","institution_ids":["https://openalex.org/I4210148700"]},{"raw_affiliation_string":"Physics and Astronomy Department (DIFA) , Alma Mater Studiorum - Universit\u00e0 di Bologna , Italy","institution_ids":["https://openalex.org/I9360294"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5074113580"],"corresponding_institution_ids":["https://openalex.org/I4210148700","https://openalex.org/I9360294"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"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/T10463","display_name":"Pulsars and Gravitational Waves Research","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/3103","display_name":"Astronomy and Astrophysics"},"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/T10463","display_name":"Pulsars and Gravitational Waves Research","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/3103","display_name":"Astronomy and Astrophysics"},"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/T11323","display_name":"Gamma-ray bursts and supernovae","score":9.999999747378752e-05,"subfield":{"id":"https://openalex.org/subfields/3103","display_name":"Astronomy and Astrophysics"},"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/T13018","display_name":"Seismology and Earthquake Studies","score":9.999999747378752e-05,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/gravitational-wave-transients","display_name":"gravitational-wave transients","score":0.8640000224113464},{"id":"https://openalex.org/keywords/wavelet-coefficients","display_name":"wavelet coefficients","score":0.8569999933242798},{"id":"https://openalex.org/keywords/graph-neural-networks","display_name":"graph neural networks","score":0.7730000019073486},{"id":"https://openalex.org/keywords/compact-binary-coalescence","display_name":"compact binary coalescence","score":0.746999979019165},{"id":"https://openalex.org/keywords/core-collapse-supernovae","display_name":"core-collapse supernovae","score":0.875},{"id":"https://openalex.org/keywords/gw250114","display_name":"GW250114","score":0.9750000238418579},{"id":"https://openalex.org/keywords/signal-reconstruction","display_name":"signal reconstruction","score":0.45899999141693115}],"concepts":[{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.6439999938011169},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5799999833106995},{"id":"https://openalex.org/C197424946","wikidata":"https://www.wikidata.org/wiki/Q1165717","display_name":"Waveform","level":3,"score":0.5587999820709229},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5163999795913696},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.4733999967575073},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.46799999475479126},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4595000147819519},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.4521999955177307},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4494999945163727},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.43619999289512634},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.41769999265670776},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.37229999899864197},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.3569999933242798},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3467999994754791},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.34529998898506165},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.3409999907016754},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.3398999869823456},{"id":"https://openalex.org/C50151734","wikidata":"https://www.wikidata.org/wiki/Q1759577","display_name":"Matched filter","level":3,"score":0.33079999685287476},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.28130000829696655},{"id":"https://openalex.org/C190330329","wikidata":"https://www.wikidata.org/wiki/Q190035","display_name":"Gravitational wave","level":2,"score":0.26750001311302185},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.2632000148296356},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.2581999897956848},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.25769999623298645}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2609.12797","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.12797","pdf_url":"https://arxiv.org/pdf/2609.12797","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2609.12797","doi":"https://doi.org/10.48550/arxiv.2609.12797","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2609.12797","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2609.12797","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.12797","pdf_url":"https://arxiv.org/pdf/2609.12797","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320320912","display_name":"Ministry of Education, Culture, Sports, Science and Technology","ror":"https://ror.org/048rj2z13"},{"id":"https://openalex.org/F4320321041","display_name":"Academia Sinica","ror":"https://ror.org/05bxb3784"},{"id":"https://openalex.org/F4320322892","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73"},{"id":"https://openalex.org/F4320323553","display_name":"Universit\u00e0 di Bologna","ror":"https://ror.org/01111rn36"},{"id":"https://openalex.org/F4320327843","display_name":"Istituto Nazionale di Fisica Nucleare","ror":null},{"id":"https://openalex.org/F4320328359","display_name":"Ministry of Science and ICT, South Korea","ror":"https://ror.org/01wpjm123"},{"id":"https://openalex.org/F4320331164","display_name":"National Science and Technology Council","ror":"https://ror.org/00wnb9798"},{"id":"https://openalex.org/F4320334632","display_name":"Science and Technology Facilities Council","ror":"https://ror.org/057g20z61"},{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7213013117.pdf","grobid_xml":"https://content.openalex.org/works/W7213013117.grobid-xml"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W1134494461","https://openalex.org/W1777070175","https://openalex.org/W1891707817","https://openalex.org/W1994870116","https://openalex.org/W2106532428","https://openalex.org/W2214545089","https://openalex.org/W2523600896","https://openalex.org/W2606780347","https://openalex.org/W2766393346","https://openalex.org/W2904931307","https://openalex.org/W3006452559","https://openalex.org/W3019006595","https://openalex.org/W3044565425","https://openalex.org/W3062583422","https://openalex.org/W3121692012","https://openalex.org/W4200123111","https://openalex.org/W4234856688","https://openalex.org/W4307082099","https://openalex.org/W4376117893","https://openalex.org/W4379767006","https://openalex.org/W4388767363","https://openalex.org/W4393851770","https://openalex.org/W4403655315","https://openalex.org/W4404346302","https://openalex.org/W4404414081","https://openalex.org/W4414090563","https://openalex.org/W4414985203","https://openalex.org/W6931476371","https://openalex.org/W7077893727","https://openalex.org/W7077912376","https://openalex.org/W7162516731","https://openalex.org/W7163780866"],"related_works":["https://openalex.org/W4407904178","https://openalex.org/W7214764528","https://openalex.org/W4393300507","https://openalex.org/W2143033550","https://openalex.org/W7170165274","https://openalex.org/W4404414081","https://openalex.org/W1903892469","https://openalex.org/W2999376051","https://openalex.org/W3036158726","https://openalex.org/W3214758319"],"abstract_inverted_index":{"Accurate":[0],"waveform":[1,199],"models":[2],"are":[3,215],"unavailable":[4],"for":[5,53],"many":[6],"potential":[7],"sources":[8],"of":[9,40,100,144,206],"gravitational":[10],"wave":[11],"transients,":[12],"motivating":[13],"searches":[14],"that":[15,32,64,75],"do":[16],"not":[17],"assume":[18],"a":[19,49,68,80,93,97,116,126,218,226],"predefined":[20],"template":[21],"family.":[22],"The":[23],"Wavelet":[24],"Detection":[25],"Filter":[26],"(WDF)":[27],"is":[28],"an":[29],"unmodeled":[30],"pipeline":[31,52,111,155,208],"identifies":[33,184],"excess":[34],"energy":[35],"in":[36,193,228],"the":[37,86,101,110,142,145,154,162,185,188,194,203,207,210],"wavelet":[38,88],"coefficients":[39,89,105],"whitened":[41],"detector":[42],"data.":[43,151],"Here,":[44],"we":[45,84],"develop":[46],"WDF":[47,183,222],"into":[48],"low":[50,219],"latency":[51,82,211,220],"both":[54,92],"detection":[55,94],"and":[56,58,62,83,96,129,134,167,175,209],"reconstruction":[57],"this":[59],"paper":[60],"describes":[61],"validates":[63],"pipeline.":[65],"We":[66,119,140,152,201],"use":[67,85],"zero":[69,190],"phase":[70],"streaming":[71],"autoregressive":[72],"whitening":[73],"filter":[74],"preserves":[76],"transient":[77],"morphology":[78],"with":[79,125,132,217],"fixed":[81],"retained":[87],"to":[90,161,181],"provide":[91],"statistic":[95],"sparse":[98],"representation":[99],"signal.":[102],"By":[103],"combining":[104],"across":[106],"consecutive":[107],"analysis":[108],"windows,":[109],"reconstructs":[112],"transients":[113],"longer":[114],"than":[115],"single":[117],"window.":[118],"represent":[120],"candidate":[121,192],"coincidences":[122,147],"between":[123],"detectors":[124],"trigger":[127],"graph":[128,136],"rank":[130],"them":[131],"supervised":[133],"unsupervised":[135],"neural":[137],"networks":[138],"(GNNs).":[139],"estimate":[141],"significance":[143],"ranked":[146],"from":[148],"time":[149],"shifted":[150],"validate":[153],"on":[156,168,225],"Gaussian":[157],"noise":[158],"colored":[159],"according":[160],"Advanced":[163],"LIGO":[164],"sensitivity":[165],"curve":[166],"real":[169,229],"O4":[170],"strain":[171],"containing":[172],"compact":[173],"binary":[174],"core":[176],"collapse":[177],"supernova":[178],"injections.":[179],"Applied":[180],"GW250114,":[182],"event":[186],"as":[187],"loudest":[189],"lag":[191],"analyzed":[195],"segment":[196],"without":[197],"using":[198],"templates.":[200],"measure":[202],"computational":[204],"cost":[205],"it":[212],"introduces.":[213],"Both":[214],"compatible":[216],"search,so":[221],"can":[223],"run":[224],"stream":[227],"time.":[230]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2026-09-15T00:00:00"}