{"id":"https://openalex.org/W4406459268","doi":"https://doi.org/10.1109/bigdata62323.2024.10825452","title":"Global-local Fourier Neural Operator for Accelerating Coronal Magnetic Field Model","display_name":"Global-local Fourier Neural Operator for Accelerating Coronal Magnetic Field Model","publication_year":2024,"publication_date":"2024-12-15","ids":{"openalex":"https://openalex.org/W4406459268","doi":"https://doi.org/10.1109/bigdata62323.2024.10825452"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata62323.2024.10825452","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825452","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100315349","display_name":"Yutao Du","orcid":null},"institutions":[{"id":"https://openalex.org/I118118575","display_name":"New Jersey Institute of Technology","ror":"https://ror.org/05e74xb87","country_code":"US","type":"education","lineage":["https://openalex.org/I118118575"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yutao Du","raw_affiliation_strings":["NJIT,Mechanical and Industrial Engineering,Newark,USA"],"affiliations":[{"raw_affiliation_string":"NJIT,Mechanical and Industrial Engineering,Newark,USA","institution_ids":["https://openalex.org/I118118575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016611516","display_name":"Qin Li","orcid":"https://orcid.org/0000-0001-7364-6900"},"institutions":[{"id":"https://openalex.org/I118118575","display_name":"New Jersey Institute of Technology","ror":"https://ror.org/05e74xb87","country_code":"US","type":"education","lineage":["https://openalex.org/I118118575"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qin Li","raw_affiliation_strings":["NJIT,Department of Physics,Newark,USA"],"affiliations":[{"raw_affiliation_string":"NJIT,Department of Physics,Newark,USA","institution_ids":["https://openalex.org/I118118575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070695030","display_name":"Raghav Gnanasambandam","orcid":"https://orcid.org/0009-0004-2159-4837"},"institutions":[{"id":"https://openalex.org/I1323276237","display_name":"Florida A&M University - Florida State University College of Engineering","ror":"https://ror.org/01v4tq883","country_code":"US","type":"education","lineage":["https://openalex.org/I103163165","https://openalex.org/I1323276237","https://openalex.org/I8248082"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Raghav Gnanasambandam","raw_affiliation_strings":["FAMU-FSU,Industrial and Manufacturing Engineering,Tallahassee,FL"],"affiliations":[{"raw_affiliation_string":"FAMU-FSU,Industrial and Manufacturing Engineering,Tallahassee,FL","institution_ids":["https://openalex.org/I1323276237"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072191151","display_name":"Mengnan Du","orcid":"https://orcid.org/0000-0002-1614-6069"},"institutions":[{"id":"https://openalex.org/I118118575","display_name":"New Jersey Institute of Technology","ror":"https://ror.org/05e74xb87","country_code":"US","type":"education","lineage":["https://openalex.org/I118118575"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mengnan Du","raw_affiliation_strings":["NJIT,Department of Data Science,Newark,USA"],"affiliations":[{"raw_affiliation_string":"NJIT,Department of Data Science,Newark,USA","institution_ids":["https://openalex.org/I118118575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061307319","display_name":"Haimin Wang","orcid":"https://orcid.org/0000-0002-5233-565X"},"institutions":[{"id":"https://openalex.org/I118118575","display_name":"New Jersey Institute of Technology","ror":"https://ror.org/05e74xb87","country_code":"US","type":"education","lineage":["https://openalex.org/I118118575"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Haimin Wang","raw_affiliation_strings":["NJIT,Department of Physics,Newark,USA"],"affiliations":[{"raw_affiliation_string":"NJIT,Department of Physics,Newark,USA","institution_ids":["https://openalex.org/I118118575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101364672","display_name":"Bo Shen","orcid":null},"institutions":[{"id":"https://openalex.org/I118118575","display_name":"New Jersey Institute of Technology","ror":"https://ror.org/05e74xb87","country_code":"US","type":"education","lineage":["https://openalex.org/I118118575"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bo Shen","raw_affiliation_strings":["NJIT,Mechanical and Industrial Engineering,Newark,USA"],"affiliations":[{"raw_affiliation_string":"NJIT,Mechanical and Industrial Engineering,Newark,USA","institution_ids":["https://openalex.org/I118118575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100315349"],"corresponding_institution_ids":["https://openalex.org/I118118575"],"apc_list":null,"apc_paid":null,"fwci":1.4565,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.82460116,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1964","last_page":"1971"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.9948999881744385,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear 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/T11206","display_name":"Model Reduction and Neural Networks","score":0.9948999881744385,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear 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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9876999855041504,"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/T13650","display_name":"Computational Physics and Python Applications","score":0.9872000217437744,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/fourier-transform","display_name":"Fourier transform","score":0.6112872362136841},{"id":"https://openalex.org/keywords/operator","display_name":"Operator (biology)","score":0.5460633039474487},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5319042205810547},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4408401846885681},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.43096572160720825},{"id":"https://openalex.org/keywords/magnetic-field","display_name":"Magnetic field","score":0.412457138299942},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.324770987033844},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.22475159168243408},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16186881065368652}],"concepts":[{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.6112872362136841},{"id":"https://openalex.org/C17020691","wikidata":"https://www.wikidata.org/wiki/Q139677","display_name":"Operator (biology)","level":5,"score":0.5460633039474487},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5319042205810547},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4408401846885681},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.43096572160720825},{"id":"https://openalex.org/C115260700","wikidata":"https://www.wikidata.org/wiki/Q11408","display_name":"Magnetic field","level":2,"score":0.412457138299942},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.324770987033844},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.22475159168243408},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16186881065368652},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C158448853","wikidata":"https://www.wikidata.org/wiki/Q425218","display_name":"Repressor","level":4,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C86339819","wikidata":"https://www.wikidata.org/wiki/Q407384","display_name":"Transcription factor","level":3,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata62323.2024.10825452","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825452","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":57,"referenced_works":["https://openalex.org/W1520318636","https://openalex.org/W1673348683","https://openalex.org/W1936694085","https://openalex.org/W1990523545","https://openalex.org/W2015545843","https://openalex.org/W2024165284","https://openalex.org/W2034039186","https://openalex.org/W2041818639","https://openalex.org/W2047104238","https://openalex.org/W2078311749","https://openalex.org/W2132473313","https://openalex.org/W2606909011","https://openalex.org/W2770250658","https://openalex.org/W2793413110","https://openalex.org/W2803629276","https://openalex.org/W2891053588","https://openalex.org/W2899283552","https://openalex.org/W2899557151","https://openalex.org/W2962934715","https://openalex.org/W2963745697","https://openalex.org/W3020102814","https://openalex.org/W3098703131","https://openalex.org/W3101301500","https://openalex.org/W3145761758","https://openalex.org/W3163993681","https://openalex.org/W3197308578","https://openalex.org/W4200281533","https://openalex.org/W4206042015","https://openalex.org/W4223598461","https://openalex.org/W4224952693","https://openalex.org/W4229443067","https://openalex.org/W4310289730","https://openalex.org/W4312222006","https://openalex.org/W4321455646","https://openalex.org/W4367860144","https://openalex.org/W4384132443","https://openalex.org/W4386090509","https://openalex.org/W4388409634","https://openalex.org/W4388701359","https://openalex.org/W4390598975","https://openalex.org/W4392099970","https://openalex.org/W4392347580","https://openalex.org/W4394578532","https://openalex.org/W4395081327","https://openalex.org/W4398235521","https://openalex.org/W6631190155","https://openalex.org/W6632344786","https://openalex.org/W6636997655","https://openalex.org/W6637078869","https://openalex.org/W6746017139","https://openalex.org/W6774402226","https://openalex.org/W6784227514","https://openalex.org/W6784333009","https://openalex.org/W6809929161","https://openalex.org/W6810506684","https://openalex.org/W6853720899","https://openalex.org/W6858091098"],"related_works":["https://openalex.org/W2391251536","https://openalex.org/W2362198218","https://openalex.org/W2019521278","https://openalex.org/W1984922432","https://openalex.org/W2375008505","https://openalex.org/W1982750869","https://openalex.org/W2085756966","https://openalex.org/W2350679292","https://openalex.org/W2086348228","https://openalex.org/W4390653028"],"abstract_inverted_index":{"Exploring":[0],"the":[1,5,15,32,36,42,73,93,112,124,139,176,188,211],"outer":[2],"atmosphere":[3],"of":[4,59,110,138,178,213],"sun":[6],"has":[7,79],"remained":[8],"a":[9,100],"significant":[10],"bottleneck":[11],"in":[12,92],"astrophysics,":[13],"given":[14],"intricate":[16],"magnetic":[17,39,66],"formations":[18],"that":[19,106,183],"significantly":[20],"influence":[21],"diverse":[22],"solar":[23],"events.":[24],"Magnetohydrodynamics":[25],"(MHD)":[26],"simulations":[27],"allow":[28],"us":[29],"to":[30,63,82,119,132,157,174,210],"model":[31],"complex":[33],"interactions":[34],"between":[35],"sun\u2019s":[37],"plasma,":[38],"fields,":[40],"and":[41,90,155,163],"surrounding":[43],"environment.":[44],"However,":[45],"MHD":[46,189],"simulation":[47,68,190],"is":[48,62,141,171,220],"extremely":[49],"time-consuming,":[50],"taking":[51],"days":[52],"or":[53],"weeks":[54],"for":[55,87,194],"simulation.":[56],"The":[57,136,180],"goal":[58],"this":[60,96],"study":[61],"accelerate":[64],"coronal":[65],"field":[67],"using":[69],"deep":[70,145],"learning,":[71],"specifically,":[72],"Fourier":[74,102],"Neural":[75,103],"Operator":[76,104],"(FNO).":[77],"FNO":[78,114,126],"been":[80],"proven":[81],"be":[83],"an":[84],"ideal":[85],"tool":[86],"scientific":[88],"computing":[89],"discovery":[91],"literature.":[94],"In":[95],"paper,":[97],"we":[98],"proposed":[99],"global-local":[101],"(GL-FNO)":[105],"contains":[107],"two":[108],"branches":[109],"FNOs:":[111],"global":[113,121],"branch":[115,127],"takes":[116,128],"downsampled":[117],"input":[118,131],"reconstruct":[120],"features":[122],"while":[123],"local":[125],"original":[129],"resolution":[130],"capture":[133],"fine":[134],"details.":[135],"performance":[137],"GL-FNO":[140,184],"compared":[142],"with":[143],"state-of-the-art":[144],"learning":[146],"methods,":[147],"including":[148],"FNO,":[149],"U-NO,":[150],"U-FNO,":[151],"Vision":[152],"Transformer,":[153],"CNN-RNN,":[154],"CNN-LSTM,":[156],"demonstrate":[158,175],"its":[159],"accuracy,":[160],"computational":[161],"efficiency,":[162],"scalability.":[164],"Furthermore,":[165],"physics-based":[166],"analysis":[167],"from":[168],"domain":[169],"experts":[170],"also":[172,202],"performed":[173],"reliability":[177],"GL-FNO.":[179],"results":[181],"show":[182],"not":[185],"only":[186],"accelerates":[187],"(a":[191],"few":[192],"seconds":[193],"prediction,":[195],"more":[196],"than":[197],"\u00d720,000":[198],"speed":[199],"up)":[200],"but":[201],"provides":[203],"reliable":[204],"prediction":[205],"capabilities,":[206],"thus":[207],"greatly":[208],"contributing":[209],"understanding":[212],"space":[214],"weather":[215],"dynamics.":[216],"Our":[217],"code":[218],"implementation":[219],"available":[221],"at":[222],"https://github.com/Yutao-0718/GL-FNO.":[223]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1}],"updated_date":"2026-03-12T08:34:05.389933","created_date":"2025-10-10T00:00:00"}