{"id":"https://openalex.org/W7128817514","doi":"https://doi.org/10.48550/arxiv.2602.12242","title":"MagneX: A High-Performance, GPU-Enabled, Data-Driven Micromagnetics Solver for Spintronics","display_name":"MagneX: A High-Performance, GPU-Enabled, Data-Driven Micromagnetics Solver for Spintronics","publication_year":2026,"publication_date":"2026-02-12","ids":{"openalex":"https://openalex.org/W7128817514","doi":"https://doi.org/10.48550/arxiv.2602.12242"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2602.12242","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5116335912","display_name":"Andy Nonaka","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nonaka, Andy","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005835764","display_name":"Yingheng Tang","orcid":"https://orcid.org/0009-0001-5362-2546"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tang, Yingheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125905477","display_name":"Julian C. LePelch","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"LePelch, Julian C.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Kumar, Prabhat","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kumar, Prabhat","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125895195","display_name":"Weiqun Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Weiqun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125964121","display_name":"Jorge A. Munoz","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Munoz, Jorge A.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125914825","display_name":"Christian Fernandez-Soria","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fernandez-Soria, Christian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125909100","display_name":"Cesar Diaz","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Diaz, Cesar","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125995019","display_name":"David J. Gardner","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gardner, David J.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5125971332","display_name":"Zhi Jackie Yao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yao, Zhi Jackie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":10,"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/T11948","display_name":"Machine Learning in Materials Science","score":0.8129000067710876,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.8129000067710876,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10049","display_name":"Magnetic properties of thin films","score":0.03229999914765358,"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/T11804","display_name":"Quantum many-body systems","score":0.023399999365210533,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/micromagnetics","display_name":"Micromagnetics","score":0.7494000196456909},{"id":"https://openalex.org/keywords/spintronics","display_name":"Spintronics","score":0.652999997138977},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6158999800682068},{"id":"https://openalex.org/keywords/multiphysics","display_name":"Multiphysics","score":0.6067000031471252},{"id":"https://openalex.org/keywords/coupling","display_name":"Coupling (piping)","score":0.5105999708175659},{"id":"https://openalex.org/keywords/solver","display_name":"Solver","score":0.44359999895095825},{"id":"https://openalex.org/keywords/terabit","display_name":"Terabit","score":0.4011000096797943}],"concepts":[{"id":"https://openalex.org/C119835096","wikidata":"https://www.wikidata.org/wiki/Q6839648","display_name":"Micromagnetics","level":4,"score":0.7494000196456909},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7290999889373779},{"id":"https://openalex.org/C207999682","wikidata":"https://www.wikidata.org/wiki/Q258659","display_name":"Spintronics","level":3,"score":0.652999997138977},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6158999800682068},{"id":"https://openalex.org/C46435376","wikidata":"https://www.wikidata.org/wiki/Q1829750","display_name":"Multiphysics","level":3,"score":0.6067000031471252},{"id":"https://openalex.org/C131584629","wikidata":"https://www.wikidata.org/wiki/Q4308705","display_name":"Coupling (piping)","level":2,"score":0.5105999708175659},{"id":"https://openalex.org/C459310","wikidata":"https://www.wikidata.org/wiki/Q117801","display_name":"Computational science","level":1,"score":0.48899999260902405},{"id":"https://openalex.org/C2778770139","wikidata":"https://www.wikidata.org/wiki/Q1966904","display_name":"Solver","level":2,"score":0.44359999895095825},{"id":"https://openalex.org/C76808792","wikidata":"https://www.wikidata.org/wiki/Q1152323","display_name":"Terabit","level":4,"score":0.4011000096797943},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.39410001039505005},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.35370001196861267},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.34880000352859497},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.334199994802475},{"id":"https://openalex.org/C60434167","wikidata":"https://www.wikidata.org/wiki/Q5255001","display_name":"Demagnetizing field","level":4,"score":0.32829999923706055},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.3158000111579895},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.3012999892234802},{"id":"https://openalex.org/C31487907","wikidata":"https://www.wikidata.org/wiki/Q1154597","display_name":"Polygon mesh","level":2,"score":0.2919999957084656},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.28049999475479126},{"id":"https://openalex.org/C2778596170","wikidata":"https://www.wikidata.org/wiki/Q4444360","display_name":"Patterned media","level":3,"score":0.27410000562667847},{"id":"https://openalex.org/C167343916","wikidata":"https://www.wikidata.org/wiki/Q6888384","display_name":"Modeling and simulation","level":2,"score":0.25279998779296875}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2602.12242","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2602.12242","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.12242","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2602.12242","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.5562487840652466}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0],"order":[1],"to":[2,14,19,46,57,164,176],"comprehensively":[3],"investigate":[4],"the":[5,21,28,32,64,116,122,130,141,148,162],"multiphysics":[6],"coupling":[7,97],"in":[8,27],"spintronic":[9,183],"devices,":[10],"it":[11],"is":[12],"essential":[13],"parallelize":[15],"and":[16,23,48,77,109,119,124,134,179,184],"utilize":[17],"GPU-acceleration":[18],"address":[20],"spatial":[22],"temporal":[24],"disparities":[25],"inherent":[26],"relevant":[29],"physics.":[30],"Additionally,":[31],"use":[33],"of":[34,121,144],"cutting-edge":[35],"time":[36],"integration":[37],"libraries":[38,76,155],"as":[39,41,71,73],"well":[40,72],"machine":[42],"learning":[43],"(ML)":[44],"approaches":[45],"replace":[47],"potentially":[49],"accelerate":[50],"expensive":[51],"computational":[52],"routines":[53],"are":[54],"attractive":[55],"capabilities":[56,60],"enhance":[58],"modeling":[59,87],"moving":[61],"forward.":[62],"Leveraging":[63],"Exascale":[65],"Computing":[66],"Project":[67],"software":[68],"framework":[69],"AMReX,":[70],"SUNDIALS":[74],"time-integration":[75],"python-based":[78],"ML":[79],"workflows,":[80],"we":[81,139],"have":[82],"developed":[83],"an":[84],"open-source":[85],"micromagnetics":[86],"tool":[88,92],"called":[89],"MagneX.":[90],"This":[91],"incorporates":[93],"various":[94],"crucial":[95],"magnetic":[96],"mechanisms,":[98],"including":[99],"Zeeman":[100],"coupling,":[101,103,108],"demagnetization":[102,150],"crystalline":[104],"anisotropy":[105],"interaction,":[106],"exchange":[107],"Dzyaloshinskii-Moriya":[110],"interaction":[111],"(DMI)":[112],"coupling.":[113],"We":[114],"demonstrate":[115,140],"GPU":[117],"performance":[118],"scalability":[120],"code":[123],"rigorously":[125],"validate":[126],"MagneX's":[127],"functionality":[128],"using":[129],"mumag":[131],"standard":[132],"problems":[133],"widely-accepted":[135],"DMI":[136],"benchmarks.":[137],"Furthermore,":[138],"data-driven":[142],"capability":[143],"MagneX":[145],"by":[146],"replacing":[147],"computationally-expensive":[149],"physics":[151],"with":[152],"neural":[153],"network":[154],"trained":[156],"from":[157],"our":[158],"simulation":[159],"data.":[160],"With":[161],"capacity":[163],"explore":[165],"complete":[166],"physical":[167],"interactions,":[168],"this":[169],"innovative":[170],"approach":[171],"offers":[172],"a":[173],"promising":[174],"pathway":[175],"better":[177],"understand":[178],"develop":[180],"fully":[181],"integrated":[182],"electronic":[185],"systems.":[186]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-02-14T00:00:00"}