{"id":"https://openalex.org/W7220737109","doi":"https://doi.org/10.48550/arxiv.2610.06816","title":"Reconfigurable On-Chip AI for Particle Physics Detectors with Logic Neural Networks","display_name":"Reconfigurable On-Chip AI for Particle Physics Detectors with Logic Neural Networks","publication_year":2026,"publication_date":"2026-10-05","ids":{"openalex":"https://openalex.org/W7220737109","doi":"https://doi.org/10.48550/arxiv.2610.06816"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2610.06816","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.06816","pdf_url":"https://arxiv.org/pdf/2610.06816","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/2610.06816","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5105962913","display_name":"Mila Bileska","orcid":"https://orcid.org/0009-0000-4820-5900","observed_orcids":["https://orcid.org/0009-0000-4820-5900"]},"institutions":[{"id":"https://openalex.org/I20089843","display_name":"Princeton University","ror":"https://ror.org/00hx57361","country_code":"US","type":"education","lineage":["https://openalex.org/I20089843"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bileska, Mila","raw_affiliation_strings":["Princeton University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Princeton University","institution_ids":["https://openalex.org/I20089843"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107944521","display_name":"Lino Oscar Gerlach","orcid":"https://orcid.org/0000-0002-4153-5541","observed_orcids":["https://orcid.org/0000-0002-4153-5541"]},"institutions":[{"id":"https://openalex.org/I20089843","display_name":"Princeton University","ror":"https://ror.org/00hx57361","country_code":"US","type":"education","lineage":["https://openalex.org/I20089843"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gerlach, Lino","raw_affiliation_strings":["Princeton University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Princeton University","institution_ids":["https://openalex.org/I20089843"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5143120169","display_name":"Jennet Dickinson","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dickinson, Jennet","raw_affiliation_strings":["Cornell University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cornell University","institution_ids":["https://openalex.org/I205783295"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5157772242","display_name":"Lindsey Gray","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I1314696892","display_name":"Fermi National Accelerator Laboratory","ror":"https://ror.org/020hgte69","country_code":"US","type":"facility","lineage":["https://openalex.org/I1314696892","https://openalex.org/I1330989302","https://openalex.org/I39565521","https://openalex.org/I4210114836"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gray, Lindsey","raw_affiliation_strings":["Fermilab"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fermilab","institution_ids":["https://openalex.org/I1314696892"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079644832","display_name":"Giuseppe Di Guglielmo","orcid":"https://orcid.org/0000-0002-5749-1432","observed_orcids":["https://orcid.org/0000-0002-5749-1432"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Di Guglielmo, Giuseppe","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031846245","display_name":"P. Elmer","orcid":"https://orcid.org/0000-0001-6830-3356","observed_orcids":["https://orcid.org/0000-0001-6830-3356"]},"institutions":[{"id":"https://openalex.org/I20089843","display_name":"Princeton University","ror":"https://ror.org/00hx57361","country_code":"US","type":"education","lineage":["https://openalex.org/I20089843"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Elmer, Peter","raw_affiliation_strings":["Princeton University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Princeton University","institution_ids":["https://openalex.org/I20089843"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5157786555","display_name":"Isobel Ojalvo","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I20089843","display_name":"Princeton University","ror":"https://ror.org/00hx57361","country_code":"US","type":"education","lineage":["https://openalex.org/I20089843"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ojalvo, Isobel","raw_affiliation_strings":["Princeton University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Princeton University","institution_ids":["https://openalex.org/I20089843"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.27730000019073486,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.27730000019073486,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10036","display_name":"Advanced Neural Network Applications","score":0.17520000040531158,"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/T11044","display_name":"Particle Detector Development and Performance","score":0.15109999477863312,"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/particle-detectors","display_name":"particle detectors","score":0.8560000061988831},{"id":"https://openalex.org/keywords/pixel-detector","display_name":"pixel detector","score":0.9580000042915344},{"id":"https://openalex.org/keywords/reconfigurable-neural-networks","display_name":"reconfigurable neural networks","score":0.8289999961853027},{"id":"https://openalex.org/keywords/radiation-damage","display_name":"radiation damage","score":0.7910000085830688},{"id":"https://openalex.org/keywords/on-device-learning","display_name":"on-device learning","score":0.7289999723434448},{"id":"https://openalex.org/keywords/resource-efficient-inference","display_name":"resource-efficient inference","score":0.5170000195503235}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6675000190734863},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.6503000259399414},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6204000115394592},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5539000034332275},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.492900013923645},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4927000105381012},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.43130001425743103},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.35269999504089355},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3310999870300293},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.33079999685287476},{"id":"https://openalex.org/C131017901","wikidata":"https://www.wikidata.org/wiki/Q170451","display_name":"Logic gate","level":2,"score":0.31630000472068787},{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.31119999289512634},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.30300000309944153},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.3019999861717224},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.30160000920295715},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.2985999882221222},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.295199990272522},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28540000319480896},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.2797999978065491},{"id":"https://openalex.org/C206274596","wikidata":"https://www.wikidata.org/wiki/Q1063837","display_name":"Programmable logic device","level":2,"score":0.274399995803833},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2727000117301941},{"id":"https://openalex.org/C157922185","wikidata":"https://www.wikidata.org/wiki/Q173198","display_name":"Logic synthesis","level":3,"score":0.2535000145435333}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2610.06816","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.06816","pdf_url":"https://arxiv.org/pdf/2610.06816","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.2610.06816","doi":"https://doi.org/10.48550/arxiv.2610.06816","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2610.06816","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":"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"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2610.06816","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.06816","pdf_url":"https://arxiv.org/pdf/2610.06816","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":[{"id":"https://openalex.org/G5178502699","display_name":"S2I2: Institute for Research and Innovation in Software for High Energy Physics (IRIS-HEP)","funder_award_id":"1836650","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5447875206","display_name":"Institute for Research and Innovation in Software for High Energy Physics (IRIS-HEP)","funder_award_id":"2323298","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7220737109.pdf","grobid_xml":"https://content.openalex.org/works/W7220737109.grobid-xml"},"referenced_works_count":11,"referenced_works":["https://openalex.org/W2427495647","https://openalex.org/W3174684282","https://openalex.org/W3175548485","https://openalex.org/W4319654320","https://openalex.org/W4386227311","https://openalex.org/W4393795350","https://openalex.org/W4401236133","https://openalex.org/W4415882883","https://openalex.org/W4416296600","https://openalex.org/W4416964958","https://openalex.org/W7083803815"],"related_works":["https://openalex.org/W3158512465","https://openalex.org/W7130582600","https://openalex.org/W4416440556","https://openalex.org/W7087691452","https://openalex.org/W3194386147","https://openalex.org/W4403885723","https://openalex.org/W2798084934","https://openalex.org/W4404366693","https://openalex.org/W4225135667","https://openalex.org/W2916565138"],"abstract_inverted_index":{"On-device":[0],"machine":[1],"learning":[2],"is":[3],"increasingly":[4],"important":[5],"in":[6,50,76,136,151],"applications":[7],"where":[8],"extreme":[9],"data":[10,71,92],"rates":[11,93],"or":[12],"resource":[13,144],"constraints":[14,104],"make":[15],"centralized":[16],"processing":[17],"infeasible.":[18],"Logic":[19],"neural":[20],"networks":[21],"(LNNs),":[22],"which":[23],"directly":[24],"learn":[25],"Boolean":[26],"logic":[27],"instead":[28],"of":[29],"conventional":[30],"arithmetic":[31],"operations,":[32],"have":[33],"recently":[34],"emerged":[35],"as":[36],"a":[37,80,148],"state-of-the-art":[38],"approach":[39],"for":[40,48,59,133],"efficient":[41,107],"inference":[42,135],"and":[43,63,88,102,123],"are":[44,56],"particularly":[45,81],"well":[46],"suited":[47],"deployment":[49],"custom":[51],"silicon.":[52],"However,":[53],"hard-wired":[54],"solutions":[55],"typically":[57],"optimized":[58],"narrowly":[60],"defined":[61],"tasks":[62],"lack":[64],"the":[65,160],"ability":[66],"to":[67,69,184,186],"adapt":[68,185],"changing":[70,187],"distributions.":[72],"Next-generation":[73],"pixel":[74,137],"detectors":[75],"particle":[77],"physics":[78],"present":[79,176],"challenging":[82],"use":[83],"case:":[84],"their":[85,142],"high":[86],"granularity":[87],"readout":[89],"frequency":[90],"generate":[91],"that":[94,119,141],"cannot":[95],"be":[96,121],"centrally":[97],"processed,":[98],"while":[99],"stringent":[100],"space":[101],"power":[103],"necessitate":[105],"highly":[106],"on-chip":[108,134],"inference.":[109],"Moreover,":[110],"radiation":[111],"damage":[112],"progressively":[113],"alters":[114],"detector":[115],"response,":[116],"requiring":[117],"models":[118,183],"can":[120],"re-trained":[122],"reconfigured":[124],"after":[125,190],"deployment.":[126,191],"In":[127],"this":[128],"work,":[129],"we":[130,175],"evaluate":[131],"LNNs":[132,164],"detectors.":[138],"We":[139],"show":[140],"superior":[143],"efficiency":[145],"may":[146],"enable":[147],"step":[149],"change":[150],"model":[152],"capability,":[153],"making":[154],"more":[155],"complex":[156],"architectures":[157],"feasible":[158],"within":[159],"available":[161],"hardware":[162],"budget.":[163],"also":[165],"provide":[166],"increased":[167],"robustness":[168],"against":[169],"radiation-induced":[170],"random":[171],"bit":[172],"flips.":[173],"Finally,":[174],"novel":[177],"work":[178],"on":[179],"reconfigurable":[180],"LNNs,":[181],"enabling":[182],"operating":[188],"conditions":[189]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2026-10-07T00:00:00"}