{"id":"https://openalex.org/W7165621461","doi":"https://doi.org/10.48550/arxiv.2606.22393","title":"HFORD: Hybrid Forward Optimization and Reverse Design Method and Its Applications to On-Chip Millimeter-Wave Inductive Elements","display_name":"HFORD: Hybrid Forward Optimization and Reverse Design Method and Its Applications to On-Chip Millimeter-Wave Inductive Elements","publication_year":2026,"publication_date":"2026-06-21","ids":{"openalex":"https://openalex.org/W7165621461","doi":"https://doi.org/10.48550/arxiv.2606.22393"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.22393","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.22393","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":"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.2606.22393","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134947889","display_name":"Y Song","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Song, Yuzhen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139153135","display_name":"Yifan Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yifan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083621372","display_name":"Guqiao Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Guqiao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139215437","display_name":"Hanyu Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Hanyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019206078","display_name":"Qile Wu","orcid":"https://orcid.org/0009-0003-1096-1892"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Qi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139195222","display_name":"Guangyi Lu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lu, Guangyi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139142819","display_name":"Haiming Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Haiming","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139192577","display_name":"Wei Hong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hong, Wei","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/T10187","display_name":"Radio Frequency Integrated Circuit Design","score":0.29840001463890076,"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/T10187","display_name":"Radio Frequency Integrated Circuit Design","score":0.29840001463890076,"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/T11522","display_name":"VLSI and FPGA Design Techniques","score":0.1981000006198883,"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/T10936","display_name":"Millimeter-Wave Propagation and Modeling","score":0.1956000030040741,"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/particle-swarm-optimization","display_name":"Particle swarm optimization","score":0.5059000253677368},{"id":"https://openalex.org/keywords/inverse","display_name":"Inverse","score":0.41909998655319214},{"id":"https://openalex.org/keywords/reverse-engineering","display_name":"Reverse engineering","score":0.3659999966621399},{"id":"https://openalex.org/keywords/topology-optimization","display_name":"Topology optimization","score":0.3628999888896942},{"id":"https://openalex.org/keywords/optimal-design","display_name":"Optimal design","score":0.3517000079154968},{"id":"https://openalex.org/keywords/footprint","display_name":"Footprint","score":0.33889999985694885},{"id":"https://openalex.org/keywords/topology","display_name":"Topology (electrical circuits)","score":0.3310999870300293},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.32910001277923584},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.3172000050544739}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5464000105857849},{"id":"https://openalex.org/C85617194","wikidata":"https://www.wikidata.org/wiki/Q2072794","display_name":"Particle swarm optimization","level":2,"score":0.5059000253677368},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.41909998655319214},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.39629998803138733},{"id":"https://openalex.org/C207850805","wikidata":"https://www.wikidata.org/wiki/Q269608","display_name":"Reverse engineering","level":2,"score":0.3659999966621399},{"id":"https://openalex.org/C189216461","wikidata":"https://www.wikidata.org/wiki/Q2443456","display_name":"Topology optimization","level":3,"score":0.3628999888896942},{"id":"https://openalex.org/C186394612","wikidata":"https://www.wikidata.org/wiki/Q7098942","display_name":"Optimal design","level":2,"score":0.3517000079154968},{"id":"https://openalex.org/C132943942","wikidata":"https://www.wikidata.org/wiki/Q2562511","display_name":"Footprint","level":2,"score":0.33889999985694885},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33880001306533813},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.3310999870300293},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.32910001277923584},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.3172000050544739},{"id":"https://openalex.org/C2780077345","wikidata":"https://www.wikidata.org/wiki/Q16891888","display_name":"Spice","level":2,"score":0.3165000081062317},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.3111000061035156},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.3066999912261963},{"id":"https://openalex.org/C199845137","wikidata":"https://www.wikidata.org/wiki/Q145490","display_name":"Network topology","level":2,"score":0.30640000104904175},{"id":"https://openalex.org/C530198007","wikidata":"https://www.wikidata.org/wiki/Q80831","display_name":"Integrated circuit","level":2,"score":0.3003999888896942},{"id":"https://openalex.org/C138852830","wikidata":"https://www.wikidata.org/wiki/Q2292993","display_name":"Design methods","level":2,"score":0.29919999837875366},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.29649999737739563},{"id":"https://openalex.org/C115527620","wikidata":"https://www.wikidata.org/wiki/Q769909","display_name":"Nonlinear programming","level":3,"score":0.296099990606308},{"id":"https://openalex.org/C74524168","wikidata":"https://www.wikidata.org/wiki/Q1074539","display_name":"Integrated circuit design","level":2,"score":0.29269999265670776},{"id":"https://openalex.org/C2776221188","wikidata":"https://www.wikidata.org/wiki/Q21072556","display_name":"Design space exploration","level":2,"score":0.2872999906539917},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2752000093460083},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.26980000734329224},{"id":"https://openalex.org/C124216869","wikidata":"https://www.wikidata.org/wiki/Q7621833","display_name":"Design strategy","level":2,"score":0.26809999346733093},{"id":"https://openalex.org/C62469222","wikidata":"https://www.wikidata.org/wiki/Q17092103","display_name":"Hybrid algorithm (constraint satisfaction)","level":5,"score":0.2646999955177307}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.22393","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.22393","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":"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.2606.22393","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.22393","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":"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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"On-chip":[0],"inductive":[1,70],"elements":[2],"are":[3],"pivotal":[4],"in":[5],"determining":[6],"both":[7],"the":[8,19,43,65,153,156,171,175],"silicon":[9],"footprint":[10],"and":[11,42,59,88,142],"performance":[12,107],"of":[13,22,46,68,155],"millimeter-wave":[14],"(mmWave)":[15],"integrated":[16],"circuits.":[17],"However,":[18],"layout-level":[20,81],"synthesis":[21,67,95],"these":[23,51],"passive":[24],"devices":[25],"is":[26,100],"severely":[27],"challenged":[28],"by":[29],"highly":[30],"nonlinear":[31],"geometry-to-performance":[32],"mappings,":[33],"computationally":[34],"expensive":[35],"full-wave":[36],"electromagnetic":[37],"simulations,":[38],"topology-dependent":[39],"design":[40,61,161,167,176],"spaces,":[41],"inherent":[44],"non-uniqueness":[45],"inverse":[47,140],"design.":[48],"To":[49],"overcome":[50],"bottlenecks,":[52],"we":[53],"propose":[54],"a":[55,73,93,121,127,134],"hybrid":[56],"forward":[57],"optimization":[58,145,185],"reverse":[60],"(HFORD)":[62],"method":[63,173],"for":[64,124,130,138,146],"target-to-layout":[66],"mmWave":[69],"elements.":[71],"Utilizing":[72],"unified":[74],"core":[75,119],"to":[76,80,102,180,183],"map":[77],"device-level":[78],"requirements":[79],"seeds,":[82],"HFORD":[83,118],"structures":[84],"direct":[85],"device":[86],"targets":[87],"translates":[89],"circuit":[90],"specifications":[91],"into":[92],"hierarchical":[94],"flow.":[96],"Specifically,":[97],"sparse-fitting":[98],"sampling":[99],"introduced":[101],"improve":[103],"coverage":[104],"across":[105],"critical":[106],"regions,":[108],"while":[109],"compact":[110],"response-fitting":[111],"coefficients":[112],"significantly":[113],"reduce":[114],"training":[115],"dimensionality.":[116],"The":[117],"integrates":[120],"random":[122],"forest":[123],"topology":[125],"selection,":[126],"variational":[128],"autoencoder":[129],"spectral":[131],"feature":[132],"generation,":[133],"mixture":[135],"density":[136],"network":[137],"probabilistic":[139],"mapping,":[141],"particle":[143],"swarm":[144],"latent":[147],"space":[148],"exploration.":[149],"This":[150],"integration":[151],"improves":[152],"feasibility":[154],"generated":[157],"layout":[158],"seeds":[159],"under":[160],"rule":[162],"check":[163],"(DRC)":[164],"constraints.":[165],"Two":[166],"examples":[168],"demonstrate":[169],"that":[170],"proposed":[172],"accelerates":[174],"cycle":[177],"from":[178],"hours":[179],"minutes":[181],"compared":[182],"conventional":[184],"methods.":[186]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-24T00:00:00"}
