{"id":"https://openalex.org/W4378800988","doi":"https://doi.org/10.1145/3583781.3590300","title":"Graph Neural Network Assisted Quantum Compilation for Qubit Allocation","display_name":"Graph Neural Network Assisted Quantum Compilation for Qubit Allocation","publication_year":2023,"publication_date":"2023-05-31","ids":{"openalex":"https://openalex.org/W4378800988","doi":"https://doi.org/10.1145/3583781.3590300"},"language":"en","primary_location":{"id":"doi:10.1145/3583781.3590300","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3583781.3590300","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3583781.3590300","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Great Lakes Symposium on VLSI 2023","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3583781.3590300","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5053566005","display_name":"Travis LeCompte","orcid":"https://orcid.org/0000-0002-6915-3545"},"institutions":[{"id":"https://openalex.org/I121820613","display_name":"Louisiana State University","ror":"https://ror.org/05ect4e57","country_code":"US","type":"education","lineage":["https://openalex.org/I121820613"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Travis LeCompte","raw_affiliation_strings":["Louisiana State University, Baton Rouge, LA, USA"],"raw_orcid":"https://orcid.org/0000-0002-6915-3545","affiliations":[{"raw_affiliation_string":"Louisiana State University, Baton Rouge, LA, USA","institution_ids":["https://openalex.org/I121820613"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003880951","display_name":"Fang Qi","orcid":"https://orcid.org/0000-0003-1447-0428"},"institutions":[{"id":"https://openalex.org/I114832834","display_name":"Tulane University","ror":"https://ror.org/04vmvtb21","country_code":"US","type":"education","lineage":["https://openalex.org/I114832834"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fang Qi","raw_affiliation_strings":["Tulane University, New Orleans, LA, USA"],"raw_orcid":"https://orcid.org/0000-0003-1447-0428","affiliations":[{"raw_affiliation_string":"Tulane University, New Orleans, LA, USA","institution_ids":["https://openalex.org/I114832834"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061718239","display_name":"Xu Yuan","orcid":"https://orcid.org/0000-0003-3775-3033"},"institutions":[{"id":"https://openalex.org/I79516672","display_name":"University of Louisiana at Lafayette","ror":"https://ror.org/01x8rc503","country_code":"US","type":"education","lineage":["https://openalex.org/I2799628689","https://openalex.org/I79516672"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xu Yuan","raw_affiliation_strings":["University of Louisiana at Lafayette, Lafayette , LA, USA"],"raw_orcid":"https://orcid.org/0000-0003-3775-3033","affiliations":[{"raw_affiliation_string":"University of Louisiana at Lafayette, Lafayette , LA, USA","institution_ids":["https://openalex.org/I79516672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032851065","display_name":"Nian-Feng Tzeng","orcid":"https://orcid.org/0000-0002-8357-6632"},"institutions":[{"id":"https://openalex.org/I79516672","display_name":"University of Louisiana at Lafayette","ror":"https://ror.org/01x8rc503","country_code":"US","type":"education","lineage":["https://openalex.org/I2799628689","https://openalex.org/I79516672"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nian-Feng Tzeng","raw_affiliation_strings":["University of Louisiana at Lafayette, Lafayette , LA, USA"],"raw_orcid":"https://orcid.org/0000-0002-8357-6632","affiliations":[{"raw_affiliation_string":"University of Louisiana at Lafayette, Lafayette , LA, USA","institution_ids":["https://openalex.org/I79516672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012903661","display_name":"M. Hassan Najafi","orcid":"https://orcid.org/0000-0002-4655-6229"},"institutions":[{"id":"https://openalex.org/I79516672","display_name":"University of Louisiana at Lafayette","ror":"https://ror.org/01x8rc503","country_code":"US","type":"education","lineage":["https://openalex.org/I2799628689","https://openalex.org/I79516672"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"M. Hassan Najafi","raw_affiliation_strings":["University of Louisiana at Lafayette, Lafayette , LA, USA"],"raw_orcid":"https://orcid.org/0000-0002-4655-6229","affiliations":[{"raw_affiliation_string":"University of Louisiana at Lafayette, Lafayette , LA, USA","institution_ids":["https://openalex.org/I79516672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101893942","display_name":"Lu Peng","orcid":"https://orcid.org/0000-0003-3545-286X"},"institutions":[{"id":"https://openalex.org/I114832834","display_name":"Tulane University","ror":"https://ror.org/04vmvtb21","country_code":"US","type":"education","lineage":["https://openalex.org/I114832834"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lu Peng","raw_affiliation_strings":["Tulane University, New Orleans, LA, USA"],"raw_orcid":"https://orcid.org/0000-0003-3545-286X","affiliations":[{"raw_affiliation_string":"Tulane University, New Orleans, LA, USA","institution_ids":["https://openalex.org/I114832834"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.3037,"has_fulltext":true,"cited_by_count":7,"citation_normalized_percentile":{"value":0.8181512,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"415","last_page":"419"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10682","display_name":"Quantum Computing Algorithms and Architecture","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T10682","display_name":"Quantum Computing Algorithms and Architecture","score":0.9998000264167786,"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"}},{"id":"https://openalex.org/T10020","display_name":"Quantum Information and Cryptography","score":0.9887999892234802,"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"}},{"id":"https://openalex.org/T10558","display_name":"Advancements in Semiconductor Devices and Circuit Design","score":0.9868000149726868,"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/computer-science","display_name":"Computer science","score":0.827114462852478},{"id":"https://openalex.org/keywords/qubit","display_name":"Qubit","score":0.7811480760574341},{"id":"https://openalex.org/keywords/quantum-computer","display_name":"Quantum computer","score":0.641497790813446},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5220115780830383},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4837956130504608},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.44392481446266174},{"id":"https://openalex.org/keywords/quantum","display_name":"Quantum","score":0.43185022473335266},{"id":"https://openalex.org/keywords/quantum-circuit","display_name":"Quantum circuit","score":0.4234997034072876},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2317705750465393},{"id":"https://openalex.org/keywords/quantum-error-correction","display_name":"Quantum error correction","score":0.19702497124671936}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.827114462852478},{"id":"https://openalex.org/C203087015","wikidata":"https://www.wikidata.org/wiki/Q378201","display_name":"Qubit","level":3,"score":0.7811480760574341},{"id":"https://openalex.org/C58053490","wikidata":"https://www.wikidata.org/wiki/Q176555","display_name":"Quantum computer","level":3,"score":0.641497790813446},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5220115780830383},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4837956130504608},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.44392481446266174},{"id":"https://openalex.org/C84114770","wikidata":"https://www.wikidata.org/wiki/Q46344","display_name":"Quantum","level":2,"score":0.43185022473335266},{"id":"https://openalex.org/C124148022","wikidata":"https://www.wikidata.org/wiki/Q2122210","display_name":"Quantum circuit","level":5,"score":0.4234997034072876},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2317705750465393},{"id":"https://openalex.org/C51003876","wikidata":"https://www.wikidata.org/wiki/Q1536431","display_name":"Quantum error correction","level":4,"score":0.19702497124671936},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3583781.3590300","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3583781.3590300","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3583781.3590300","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Great Lakes Symposium on VLSI 2023","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3583781.3590300","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3583781.3590300","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3583781.3590300","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Great Lakes Symposium on VLSI 2023","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4378800988.pdf","grobid_xml":"https://content.openalex.org/works/W4378800988.grobid-xml"},"referenced_works_count":3,"referenced_works":["https://openalex.org/W2889938786","https://openalex.org/W2913992572","https://openalex.org/W2950697450"],"related_works":["https://openalex.org/W2134613344","https://openalex.org/W4200149527","https://openalex.org/W2045473016","https://openalex.org/W4284882292","https://openalex.org/W2997740458","https://openalex.org/W4379115997","https://openalex.org/W2792100442","https://openalex.org/W3092615945","https://openalex.org/W4214847524","https://openalex.org/W3133505863"],"abstract_inverted_index":{"Quantum":[0,140],"computers":[1],"in":[2,97],"the":[3,31,58,69,76,87,119,123,128,146],"current":[4,32],"noisy":[5],"intermediate-scale":[6],"quantum":[7,20,124],"(NISQ)":[8],"era":[9],"face":[10],"two":[11,70],"major":[12],"limitations":[13],"-":[14],"size":[15,33],"and":[16,79,91,130,154,157],"error":[17,21],"vulnerability.":[18],"Although":[19],"correction":[22],"(QEC)":[23],"methods":[24],"exist,":[25],"they":[26],"are":[27,75],"not":[28],"applicable":[29],"at":[30,47],"of":[34,38,100,122,151],"computers,":[35],"requiring":[36],"thousands":[37],"qubits,":[39],"while":[40],"NISQ":[41],"systems":[42],"have":[43],"nearly":[44],"one":[45],"hundred":[46],"most.":[48],"One":[49],"common":[50],"approach":[51],"to":[52,56,61,117],"improve":[53],"reliability":[54],"is":[55],"adjust":[57],"compilation":[59,73],"process":[60,118],"create":[62],"a":[63,98,111,135,149],"more":[64],"reliable":[65],"final":[66],"circuit,":[67],"where":[68],"most":[71],"critical":[72],"decisions":[74],"qubit":[77,80,88],"allocation":[78,89,169],"routing":[81],"problems.":[82],"We":[83,144],"focus":[84],"on":[85],"solving":[86],"problem":[90],"identifying":[92],"initial":[93],"layouts":[94],"that":[95,159],"result":[96],"reduction":[99],"error.":[101],"To":[102],"identify":[103],"these":[104],"layouts,":[105],"we":[106],"combine":[107],"reinforcement":[108],"learning":[109],"with":[110],"graph":[112],"neural":[113],"network":[114],"(GNN)-based":[115],"Q-network":[116],"mesh":[120],"topology":[121],"computer,":[125],"known":[126],"as":[127],"backend,":[129],"make":[131],"mapping":[132],"decisions,":[133],"creating":[134],"Graph":[136],"Neural":[137],"Network":[138],"Assisted":[139],"Compilation":[141],"(GNAQC)":[142],"strategy.":[143],"train":[145],"architecture":[147],"using":[148],"set":[150],"four":[152],"backends":[153],"six":[155],"circuits":[156],"find":[158],"GNAQC":[160],"improves":[161],"output":[162],"fidelity":[163],"by":[164],"roughly":[165],"12.7%":[166],"over":[167],"pre-existing":[168],"methods.":[170]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-31T08:31:51.225901","created_date":"2025-10-10T00:00:00"}