{"id":"https://openalex.org/W7150727764","doi":"https://doi.org/10.48550/arxiv.2604.03187","title":"Biologically Realistic Dynamics for Nonlinear Classification in CMOS+X Neurons","display_name":"Biologically Realistic Dynamics for Nonlinear Classification in CMOS+X Neurons","publication_year":2026,"publication_date":"2026-04-03","ids":{"openalex":"https://openalex.org/W7150727764","doi":"https://doi.org/10.48550/arxiv.2604.03187"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.03187","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.03187","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,"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.2604.03187","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5126175560","display_name":"Steven Louis","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Louis, Steven","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133052694","display_name":"Hannah Bradley","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bradley, Hannah","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079846878","display_name":"Artem Litvinenko","orcid":"https://orcid.org/0000-0002-3880-5184"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Litvinenko, Artem","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133023027","display_name":"Cody Trevillian","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Trevillian, Cody","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068579855","display_name":"Darrin M. Hanna","orcid":"https://orcid.org/0000-0001-5580-8451"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hanna, Darrin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5107825823","display_name":"Vasyl Tyberkevych","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tyberkevych, Vasyl","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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.692300021648407,"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":0.692300021648407,"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/T10049","display_name":"Magnetic properties of thin films","score":0.14239999651908875,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"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/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.06629999727010727,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/neuromorphic-engineering","display_name":"Neuromorphic engineering","score":0.8331999778747559},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.7584999799728394},{"id":"https://openalex.org/keywords/spike","display_name":"Spike (software development)","score":0.6572999954223633},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.6437000036239624},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.5866000056266785},{"id":"https://openalex.org/keywords/spiking-neural-network","display_name":"Spiking neural network","score":0.5800999999046326},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5418000221252441},{"id":"https://openalex.org/keywords/nmos-logic","display_name":"NMOS logic","score":0.5335000157356262},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.40529999136924744}],"concepts":[{"id":"https://openalex.org/C151927369","wikidata":"https://www.wikidata.org/wiki/Q1981312","display_name":"Neuromorphic engineering","level":3,"score":0.8331999778747559},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.7584999799728394},{"id":"https://openalex.org/C2781390188","wikidata":"https://www.wikidata.org/wiki/Q25203449","display_name":"Spike (software development)","level":2,"score":0.6572999954223633},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.6437000036239624},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5958999991416931},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.5866000056266785},{"id":"https://openalex.org/C11731999","wikidata":"https://www.wikidata.org/wiki/Q9067355","display_name":"Spiking neural network","level":3,"score":0.5800999999046326},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5418000221252441},{"id":"https://openalex.org/C197162436","wikidata":"https://www.wikidata.org/wiki/Q83908","display_name":"NMOS logic","level":4,"score":0.5335000157356262},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.40529999136924744},{"id":"https://openalex.org/C2778381111","wikidata":"https://www.wikidata.org/wiki/Q6731632","display_name":"Magnetization dynamics","level":4,"score":0.40450000762939453},{"id":"https://openalex.org/C145912823","wikidata":"https://www.wikidata.org/wiki/Q113558","display_name":"Dynamics (music)","level":2,"score":0.3982999920845032},{"id":"https://openalex.org/C6899612","wikidata":"https://www.wikidata.org/wiki/Q852911","display_name":"Resistive touchscreen","level":2,"score":0.38429999351501465},{"id":"https://openalex.org/C3832189","wikidata":"https://www.wikidata.org/wiki/Q8588916","display_name":"Models of neural computation","level":3,"score":0.3709999918937683},{"id":"https://openalex.org/C186060115","wikidata":"https://www.wikidata.org/wiki/Q30336093","display_name":"Biological system","level":1,"score":0.3646000027656555},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3513999879360199},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34880000352859497},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.3203999996185303},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.3158999979496002},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.3041999936103821},{"id":"https://openalex.org/C131017901","wikidata":"https://www.wikidata.org/wiki/Q170451","display_name":"Logic gate","level":2,"score":0.2955000102519989},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2847999930381775},{"id":"https://openalex.org/C812465","wikidata":"https://www.wikidata.org/wiki/Q5058375","display_name":"Cellular neural network","level":3,"score":0.28369998931884766},{"id":"https://openalex.org/C180205008","wikidata":"https://www.wikidata.org/wiki/Q159190","display_name":"Amplitude","level":2,"score":0.27149999141693115},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.2606000006198883},{"id":"https://openalex.org/C118403218","wikidata":"https://www.wikidata.org/wiki/Q43283","display_name":"Biological neural network","level":2,"score":0.2581999897956848},{"id":"https://openalex.org/C126701199","wikidata":"https://www.wikidata.org/wiki/Q264224","display_name":"Complex dynamics","level":2,"score":0.25769999623298645},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.25049999356269836}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.03187","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.03187","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,"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.2604.03187","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.03187","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,"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":[{"id":"https://metadata.un.org/sdg/7","score":0.9057664275169373,"display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Spiking":[0],"neural":[1,23],"networks":[2,24],"encode":[3],"information":[4],"in":[5,21,31,48,60,99,125],"spike":[6,104],"timing":[7],"and":[8,28,90,106],"offer":[9],"a":[10,18,49,55,69],"pathway":[11],"toward":[12],"energy":[13],"efficient":[14],"artificial":[15],"intelligence.":[16],"However,":[17],"key":[19],"challenge":[20],"spiking":[22,51],"is":[25],"realizing":[26],"nonlinear":[27,46,84,123],"expressive":[29],"computation":[30,47,124],"compact,":[32],"energy-efficient":[33],"hardware":[34],"without":[35],"relying":[36],"on":[37],"additional":[38],"circuit":[39],"complexity.":[40],"In":[41],"this":[42],"work,":[43],"we":[44],"examine":[45],"CMOS+X":[50],"neuron":[52],"implemented":[53],"with":[54,62],"magnetic":[56],"tunnel":[57],"junction":[58],"connected":[59],"series":[61],"an":[63],"NMOS":[64],"transistor.":[65],"Circuit":[66],"simulations":[67],"of":[68,118],"multilayer":[70],"network":[71],"solving":[72],"the":[73],"XOR":[74],"classification":[75],"problem":[76],"show":[77,114],"that":[78,115],"three":[79],"intrinsic":[80],"neuronal":[81],"properties":[82],"enable":[83],"behavior:":[85],"threshold":[86],"activation,":[87],"response":[88,101],"latency,":[89],"absolute":[91,107],"refraction.":[92],"Threshold":[93],"activation":[94],"determines":[95],"which":[96],"neurons":[97],"participate":[98],"computation,":[100],"latency":[102],"shifts":[103],"timing,":[105],"refraction":[108],"suppresses":[109],"subsequent":[110],"spikes.":[111],"These":[112],"results":[113],"magnetization":[116],"dynamics":[117],"MTJ":[119],"devices":[120],"can":[121],"support":[122],"compact":[126],"neuromorphic":[127],"hardware.":[128]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-04-07T00:00:00"}
