{"id":"https://openalex.org/W7131398554","doi":"https://doi.org/10.48550/arxiv.2602.20317","title":"TokEye: Fast Signal Extraction for Fluctuating Time Series via Offline Self-Supervised Learning From Fusion Diagnostics to Bioacoustics","display_name":"TokEye: Fast Signal Extraction for Fluctuating Time Series via Offline Self-Supervised Learning From Fusion Diagnostics to Bioacoustics","publication_year":2026,"publication_date":"2026-02-23","ids":{"openalex":"https://openalex.org/W7131398554","doi":"https://doi.org/10.48550/arxiv.2602.20317"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2602.20317","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.20317","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2602.20317","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5037729656","display_name":"Nathaniel Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Chen, Nathaniel","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5092048122","display_name":"Kouroche Bouchiat","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bouchiat, Kouroche","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126792351","display_name":"Peter Steiner","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Steiner, Peter","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113618100","display_name":"Andrew Rothstein","orcid":"https://orcid.org/0000-0003-2183-0997"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rothstein, Andrew","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126806057","display_name":"David Smith","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Smith, David","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126844223","display_name":"Max Austin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Austin, Max","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011243523","display_name":"Mike van Zeeland","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"van Zeeland, Mike","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058400740","display_name":"Azarakhsh Jalalvand","orcid":"https://orcid.org/0000-0001-8739-1793"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jalalvand, Azarakhsh","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5115024394","display_name":"Egemen Kolemen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kolemen, Egemen","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5037729656"],"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/T10346","display_name":"Magnetic confinement fusion research","score":0.7904000282287598,"subfield":{"id":"https://openalex.org/subfields/3106","display_name":"Nuclear and High Energy 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/T10346","display_name":"Magnetic confinement fusion research","score":0.7904000282287598,"subfield":{"id":"https://openalex.org/subfields/3106","display_name":"Nuclear and High Energy 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/T11367","display_name":"Particle accelerators and beam dynamics","score":0.013799999840557575,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10384","display_name":"Laser-Plasma Interactions and Diagnostics","score":0.008100000210106373,"subfield":{"id":"https://openalex.org/subfields/3106","display_name":"Nuclear and High Energy Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5231999754905701},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.5131000280380249},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.4909000098705292},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4894999861717224},{"id":"https://openalex.org/keywords/transient","display_name":"Transient (computer programming)","score":0.41440001130104065},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.41260001063346863},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4059000015258789},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.3862999975681305}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6801999807357788},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5612000226974487},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5231999754905701},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.5131000280380249},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.4909000098705292},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4894999861717224},{"id":"https://openalex.org/C2780799671","wikidata":"https://www.wikidata.org/wiki/Q17087362","display_name":"Transient (computer programming)","level":2,"score":0.41440001130104065},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.41260001063346863},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4059000015258789},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.3862999975681305},{"id":"https://openalex.org/C13600138","wikidata":"https://www.wikidata.org/wiki/Q8799","display_name":"Petabyte","level":3,"score":0.37869998812675476},{"id":"https://openalex.org/C116515362","wikidata":"https://www.wikidata.org/wiki/Q188589","display_name":"Tokamak","level":3,"score":0.37209999561309814},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.362199991941452},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3395000100135803},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.3292999863624573},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.31470000743865967},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.31360000371932983},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2957000136375427},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.2793999910354614},{"id":"https://openalex.org/C142433447","wikidata":"https://www.wikidata.org/wiki/Q7806653","display_name":"Time\u2013frequency analysis","level":3,"score":0.27880001068115234},{"id":"https://openalex.org/C138827492","wikidata":"https://www.wikidata.org/wiki/Q6661985","display_name":"Data processing","level":2,"score":0.27309998869895935},{"id":"https://openalex.org/C119666444","wikidata":"https://www.wikidata.org/wiki/Q5977280","display_name":"Temporal resolution","level":2,"score":0.2615000009536743},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.2542000114917755},{"id":"https://openalex.org/C34951282","wikidata":"https://www.wikidata.org/wiki/Q864191","display_name":"Bioacoustics","level":2,"score":0.25049999356269836}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2602.20317","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.20317","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2602.20317","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.20317","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":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Next-generation":[0],"fusion":[1],"facilities":[2],"like":[3],"ITER":[4],"face":[5],"a":[6,21,39,46,73],"\"data":[7],"deluge,\"":[8],"generating":[9],"petabytes":[10],"of":[11,29,41,108],"multi-diagnostic":[12],"signals":[13],"daily":[14],"that":[15],"challenge":[16],"manual":[17],"analysis.":[18],"We":[19,43],"present":[20],"\"signals-first\"":[22],"self-supervised":[23],"framework":[24,112],"for":[25,51,58,122],"the":[26],"automated":[27,119],"extraction":[28],"coherent":[30],"and":[31,49,55,86,101,117],"transient":[32,56],"modes":[33,57],"from":[34,91,98],"high-noise":[35],"time-frequency":[36],"data":[37,97],"across":[38],"variety":[40],"sensors.":[42],"also":[44],"develop":[45],"general-purpose":[47],"method":[48],"tool":[50],"extracting":[52],"coherent,":[53],"quasi-coherent,":[54],"fluctuation":[59],"measurements":[60,90],"in":[61,68,128],"tokamaks":[62],"by":[63],"employing":[64],"non-linear":[65],"optimal":[66],"techniques":[67],"multichannel":[69],"signal":[70],"processing":[71],"with":[72],"fast":[74,79],"neural":[75],"network":[76],"surrogate":[77],"on":[78,96],"magnetics,":[80],"electron":[81],"cyclotron":[82],"emission,":[83],"CO2":[84],"interferometers,":[85],"beam":[87],"emission":[88],"spectroscopy":[89],"DIII-D.":[92],"Results":[93],"are":[94],"tested":[95],"DIII-D,":[99],"TJ-II,":[100],"non-fusion":[102],"spectrograms.":[103],"With":[104],"an":[105],"inference":[106],"latency":[107],"0.5":[109],"seconds,":[110],"this":[111],"enables":[113],"real-time":[114],"mode":[115],"identification":[116],"large-scale":[118],"database":[120],"generation":[121],"advanced":[123],"plasma":[124],"control.":[125],"Repository":[126],"is":[127],"https://github.com/PlasmaControl/TokEye.":[129]},"counts_by_year":[],"updated_date":"2026-02-28T06:14:18.631764","created_date":"2026-02-26T00:00:00"}