{"id":"https://openalex.org/W7163531530","doi":"https://doi.org/10.48550/arxiv.2606.04279","title":"Derivative Informed Learning of Exchange-Correlation Functionals","display_name":"Derivative Informed Learning of Exchange-Correlation Functionals","publication_year":2026,"publication_date":"2026-06-02","ids":{"openalex":"https://openalex.org/W7163531530","doi":"https://doi.org/10.48550/arxiv.2606.04279"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.04279","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.04279","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.2606.04279","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137848229","display_name":"Eike S. Eberhard","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Eberhard, Eike S.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137817046","display_name":"Luca A. Thiede","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Thiede, Luca A.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137869300","display_name":"Abdul Aldossary","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Aldossary, Abdul","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137824454","display_name":"Andreas Burger","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Burger, Andreas","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017074868","display_name":"Nicholas Gao","orcid":"https://orcid.org/0000-0002-1487-2657"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gao, Nicholas","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121527716","display_name":"Vignesh Bhethanabotla","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bhethanabotla, Vignesh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137862489","display_name":"Al\u00e1n Aspuru-Guzik","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Aspuru-Guzik, Al\u00e1n","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5074504351","display_name":"Stephan G\u00fcnnemann","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"G\u00fcnnemann, Stephan","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/T11948","display_name":"Machine Learning in Materials Science","score":0.9708999991416931,"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":0.9708999991416931,"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/T10002","display_name":"Advanced Chemical Physics Studies","score":0.005900000222027302,"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":0.003599999938160181,"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/hessian-matrix","display_name":"Hessian matrix","score":0.7114999890327454},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.630299985408783},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5627999901771545},{"id":"https://openalex.org/keywords/hybrid-functional","display_name":"Hybrid functional","score":0.5239999890327454},{"id":"https://openalex.org/keywords/time-dependent-density-functional-theory","display_name":"Time-dependent density functional theory","score":0.510200023651123},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.5024999976158142},{"id":"https://openalex.org/keywords/derivative","display_name":"Derivative (finance)","score":0.4749999940395355},{"id":"https://openalex.org/keywords/density-functional-theory","display_name":"Density functional theory","score":0.4000999927520752}],"concepts":[{"id":"https://openalex.org/C203616005","wikidata":"https://www.wikidata.org/wiki/Q620495","display_name":"Hessian matrix","level":2,"score":0.7114999890327454},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.630299985408783},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5627999901771545},{"id":"https://openalex.org/C22693506","wikidata":"https://www.wikidata.org/wiki/Q3075290","display_name":"Hybrid functional","level":3,"score":0.5239999890327454},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5105000138282776},{"id":"https://openalex.org/C20853536","wikidata":"https://www.wikidata.org/wiki/Q4120992","display_name":"Time-dependent density functional theory","level":3,"score":0.510200023651123},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.5024999976158142},{"id":"https://openalex.org/C111771559","wikidata":"https://www.wikidata.org/wiki/Q66295","display_name":"Derivative (finance)","level":2,"score":0.4749999940395355},{"id":"https://openalex.org/C152365726","wikidata":"https://www.wikidata.org/wiki/Q1048589","display_name":"Density functional theory","level":2,"score":0.4000999927520752},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.37959998846054077},{"id":"https://openalex.org/C191640071","wikidata":"https://www.wikidata.org/wiki/Q5377056","display_name":"Energy functional","level":2,"score":0.37610000371932983},{"id":"https://openalex.org/C17137986","wikidata":"https://www.wikidata.org/wiki/Q215067","display_name":"Orthogonality","level":2,"score":0.37459999322891235},{"id":"https://openalex.org/C173523689","wikidata":"https://www.wikidata.org/wiki/Q215589","display_name":"Dipole","level":2,"score":0.34290000796318054},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.3407999873161316},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.33889999985694885},{"id":"https://openalex.org/C33257320","wikidata":"https://www.wikidata.org/wiki/Q1932744","display_name":"Second derivative","level":2,"score":0.32499998807907104},{"id":"https://openalex.org/C2983502797","wikidata":"https://www.wikidata.org/wiki/Q828402","display_name":"Energy density","level":2,"score":0.32429999113082886},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3057999908924103},{"id":"https://openalex.org/C104970782","wikidata":"https://www.wikidata.org/wiki/Q7100054","display_name":"Orbital-free density functional theory","level":4,"score":0.30140000581741333},{"id":"https://openalex.org/C2780522230","wikidata":"https://www.wikidata.org/wiki/Q1140419","display_name":"Ambiguity","level":2,"score":0.28200000524520874},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.26579999923706055},{"id":"https://openalex.org/C171752962","wikidata":"https://www.wikidata.org/wiki/Q255166","display_name":"Kullback\u2013Leibler divergence","level":2,"score":0.25850000977516174},{"id":"https://openalex.org/C189508267","wikidata":"https://www.wikidata.org/wiki/Q17088227","display_name":"Density estimation","level":3,"score":0.2574000060558319}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.04279","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.04279","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.2606.04279","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.04279","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":[{"display_name":"Affordable and clean energy","score":0.8641122579574585,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Machine-learned":[0],"(ML)":[1],"exchange-correlation":[2],"(XC)":[3],"functionals":[4,38,164],"aim":[5],"to":[6,41,126,141,171],"replace":[7],"human-designed":[8],"density":[9,76,129,150],"functional":[10,61,97],"approximations":[11],"by":[12,62,123,169,189],"learning":[13],"directly":[14],"from":[15,57,139,161],"reference":[16,59],"data,":[17],"but":[18],"they":[19],"still":[20],"do":[21,152],"not":[22,153],"consistently":[23,109],"outperform":[24],"traditional":[25],"$\\mathcal{O}(N^4)$-scaling":[26],"hybrid":[27,60],"functionals.":[28],"We":[29,45,156],"study":[30],"a":[31,51],"hybrid-distillation":[32],"setting":[33],"in":[34],"which":[35],"$\\mathcal{O}(N^3)$-scaling":[36],"ML-XC":[37],"are":[39],"trained":[40],"reproduce":[42],"B3LYP/def2-SVP":[43],"targets.":[44],"introduce":[46],"Derivative":[47],"Informed":[48],"XC-Loss":[49],"(DI-Loss),":[50],"loss":[52],"that":[53,99,159],"incorporates":[54],"additional":[55],"information":[56],"the":[58,69,72,82,88,95,101,111,119,162,185],"supervising":[63],"first":[64],"and":[65,91,128,148],"second":[66],"derivatives":[67],"of":[68,74,94,100],"energy":[70,113,127,135],"on":[71,144],"Grassmannian":[73],"admissible":[75],"matrices.":[77],"Rather":[78],"than":[79],"only":[80],"matching":[81],"self-consistent":[83],"fixed":[84],"point,":[85],"DI-Loss":[86,108],"aligns":[87],"local":[89],"first-":[90],"second-order":[92],"response":[93],"learned":[96],"with":[98,182],"target":[102],"functional.":[103],"Across":[104],"four":[105],"evaluated":[106],"architectures,":[107,118],"improves":[110,138,179],"main":[112],"metrics.":[114],"Averaged":[115],"uniformly":[116],"across":[117],"total-energy":[120],"MAE":[121,188],"decreases":[122],"66%":[124],"relative":[125],"supervision":[130,178],"alone.":[131],"The":[132],"density-sensitive":[133],"mean-field":[134],"metric":[136],"$E_\u03c1$":[137],"$1.2$":[140],"$0.8$":[142],"mEh":[143],"average,":[145],"while":[146],"dipole":[147],"$\\mathcal{L}_2$":[149],"errors":[151],"improve":[154],"uniformly.":[155],"further":[157],"show":[158],"densities":[160],"distilled":[163],"reduce":[165],"hybrid-functional":[166],"SCF":[167],"iterations":[168],"up":[170],"50%.":[172],"In":[173],"downstream":[174],"TDDFT":[175],"calculations,":[176],"Hessian":[177],"excited-state":[180],"predictions,":[181],"XCdiff":[183],"reducing":[184],"mean":[186],"excitation-energy":[187],"19":[190],"-":[191],"35%.":[192]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-05T00:00:00"}