{"id":"https://openalex.org/W7220914864","doi":"https://doi.org/10.48550/arxiv.2610.10298","title":"Physics-Aligned Electronic Ground-State Learning Improves Generalization","display_name":"Physics-Aligned Electronic Ground-State Learning Improves Generalization","publication_year":2026,"publication_date":"2026-10-07","ids":{"openalex":"https://openalex.org/W7220914864","doi":"https://doi.org/10.48550/arxiv.2610.10298"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2610.10298","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.10298","pdf_url":"https://arxiv.org/pdf/2610.10298","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2610.10298","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5111396940","display_name":"Eike Eberhard","orcid":null,"observed_orcids":[]},"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/A5157949877","display_name":"Xaver Kainz","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Kainz, Xaver","raw_affiliation_strings":["Munich Data Science Institute (MDSI)","Technical University of Munich (TUM)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Munich Data Science Institute (MDSI)","institution_ids":[]},{"raw_affiliation_string":"Technical University of Munich (TUM)","institution_ids":["https://openalex.org/I62916508"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108342175","display_name":"Viktor Kotsev","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Kotsev, Viktor","raw_affiliation_strings":["Technical University of Munich (TUM)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technical University of Munich (TUM)","institution_ids":["https://openalex.org/I62916508"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087778280","display_name":"Abdulrahman Aldossary","orcid":"https://orcid.org/0000-0003-0700-7996","observed_orcids":["https://orcid.org/0000-0003-0700-7996"]},"institutions":[{"id":"https://openalex.org/I1304085615","display_name":"Nvidia (United Kingdom)","ror":"https://ror.org/02kr42612","country_code":"GB","type":"company","lineage":["https://openalex.org/I1304085615","https://openalex.org/I4210127875"]},{"id":"https://openalex.org/I4210127875","display_name":"Nvidia (United States)","ror":"https://ror.org/03jdj4y14","country_code":"US","type":"company","lineage":["https://openalex.org/I4210127875"]}],"countries":["GB","US"],"is_corresponding":false,"raw_author_name":"Aldossary, Abdulrahman","raw_affiliation_strings":["NVIDIA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NVIDIA","institution_ids":["https://openalex.org/I1304085615","https://openalex.org/I4210127875"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074504351","display_name":"Stephan G\u00fcnnemann","orcid":"https://orcid.org/0000-0001-7772-5059","observed_orcids":["https://orcid.org/0000-0001-7772-5059"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"G\u00fcnnemann, Stephan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"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":0.9937000274658203,"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":0.9937000274658203,"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":0.006000000052154064,"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/T10211","display_name":"Computational Drug Discovery Methods","score":9.999999747378752e-05,"subfield":{"id":"https://openalex.org/subfields/3002","display_name":"Drug Discovery"},"field":{"id":"https://openalex.org/fields/30","display_name":"Pharmacology, Toxicology and Pharmaceutics"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/machine-learning-interatomic-potentials","display_name":"machine learning interatomic potentials","score":0.9350000023841858},{"id":"https://openalex.org/keywords/kohn-sham-density-functional-theory","display_name":"Kohn-Sham density functional theory","score":0.8970000147819519},{"id":"https://openalex.org/keywords/out-of-distribution-generalization","display_name":"out-of-distribution generalization","score":0.871999979019165},{"id":"https://openalex.org/keywords/energy-and-force-prediction","display_name":"energy and force prediction","score":0.6669999957084656},{"id":"https://openalex.org/keywords/qm9","display_name":"QM9","score":0.5989999771118164}],"concepts":[{"id":"https://openalex.org/C132459708","wikidata":"https://www.wikidata.org/wiki/Q744069","display_name":"Extrapolation","level":2,"score":0.738099992275238},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.5533999800682068},{"id":"https://openalex.org/C152365726","wikidata":"https://www.wikidata.org/wiki/Q1048589","display_name":"Density functional theory","level":2,"score":0.5271000266075134},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4893999993801117},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.43389999866485596},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.42969998717308044},{"id":"https://openalex.org/C137635306","wikidata":"https://www.wikidata.org/wiki/Q182667","display_name":"Pareto principle","level":2,"score":0.397599995136261},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.38940000534057617},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.3788999915122986},{"id":"https://openalex.org/C130787639","wikidata":"https://www.wikidata.org/wiki/Q5645293","display_name":"Hamiltonian (control theory)","level":2,"score":0.36399999260902405},{"id":"https://openalex.org/C153914771","wikidata":"https://www.wikidata.org/wiki/Q5227343","display_name":"Data reduction","level":2,"score":0.35040000081062317},{"id":"https://openalex.org/C14961307","wikidata":"https://www.wikidata.org/wiki/Q5377176","display_name":"Energy minimization","level":2,"score":0.3407999873161316},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.3248000144958496},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3138999938964844},{"id":"https://openalex.org/C21080849","wikidata":"https://www.wikidata.org/wiki/Q13611879","display_name":"Data point","level":2,"score":0.3086000084877014},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3050000071525574},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.298799991607666},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29840001463890076},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.27970001101493835},{"id":"https://openalex.org/C122383733","wikidata":"https://www.wikidata.org/wiki/Q865920","display_name":"Approximation error","level":2,"score":0.2628999948501587},{"id":"https://openalex.org/C99726746","wikidata":"https://www.wikidata.org/wiki/Q906396","display_name":"Chemical space","level":3,"score":0.26019999384880066},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.2574000060558319},{"id":"https://openalex.org/C135889238","wikidata":"https://www.wikidata.org/wiki/Q46276","display_name":"Kinetic energy","level":2,"score":0.25369998812675476},{"id":"https://openalex.org/C154507838","wikidata":"https://www.wikidata.org/wiki/Q7625053","display_name":"Structural risk minimization","level":3,"score":0.25270000100135803}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2610.10298","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.10298","pdf_url":"https://arxiv.org/pdf/2610.10298","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2610.10298","doi":"https://doi.org/10.48550/arxiv.2610.10298","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2610.10298","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2610.10298","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.10298","pdf_url":"https://arxiv.org/pdf/2610.10298","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7220914864.pdf","grobid_xml":"https://content.openalex.org/works/W7220914864.grobid-xml"},"referenced_works_count":59,"referenced_works":["https://openalex.org/W1708984004","https://openalex.org/W1804110266","https://openalex.org/W1985583109","https://openalex.org/W1986751761","https://openalex.org/W1988091937","https://openalex.org/W1992028354","https://openalex.org/W2011079470","https://openalex.org/W2013183108","https://openalex.org/W2023271753","https://openalex.org/W2037210960","https://openalex.org/W2038305447","https://openalex.org/W2038533471","https://openalex.org/W2042490355","https://openalex.org/W2051891162","https://openalex.org/W2086458318","https://openalex.org/W2105564187","https://openalex.org/W2109665034","https://openalex.org/W2132354558","https://openalex.org/W2143981217","https://openalex.org/W2148284063","https://openalex.org/W2230728100","https://openalex.org/W2508041733","https://openalex.org/W2778051509","https://openalex.org/W2909595621","https://openalex.org/W2964121744","https://openalex.org/W2984234582","https://openalex.org/W2990504690","https://openalex.org/W3007178273","https://openalex.org/W3015963962","https://openalex.org/W3021539081","https://openalex.org/W3126679164","https://openalex.org/W3167942196","https://openalex.org/W3203476487","https://openalex.org/W3208707586","https://openalex.org/W4225405705","https://openalex.org/W4282053982","https://openalex.org/W4296459217","https://openalex.org/W4312119492","https://openalex.org/W4319653980","https://openalex.org/W4385406529","https://openalex.org/W4399234288","https://openalex.org/W4399555398","https://openalex.org/W4404580258","https://openalex.org/W4405516564","https://openalex.org/W4406763461","https://openalex.org/W4407131484","https://openalex.org/W4407925765","https://openalex.org/W4414804964","https://openalex.org/W4414846785","https://openalex.org/W4415109457","https://openalex.org/W4415338186","https://openalex.org/W4416044854","https://openalex.org/W4416050544","https://openalex.org/W4416524231","https://openalex.org/W7077504066","https://openalex.org/W7130706643","https://openalex.org/W7133185931","https://openalex.org/W7197052522","https://openalex.org/W7221176537"],"related_works":["https://openalex.org/W7042732966","https://openalex.org/W4402386263","https://openalex.org/W4407759102","https://openalex.org/W6967130730","https://openalex.org/W7221126729","https://openalex.org/W7155402292","https://openalex.org/W7160907534","https://openalex.org/W4415067729","https://openalex.org/W4385738720","https://openalex.org/W4412109372"],"abstract_inverted_index":{"Machine-learned":[0],"interatomic":[1],"potentials":[2],"(MLIPs)":[3],"excel":[4],"at":[5],"in-distribution":[6],"tasks,":[7],"accelerating":[8],"drug":[9],"and":[10,41,52,66,90,100,117,128,137,175],"material":[11],"development,":[12],"yet":[13],"they":[14],"struggle":[15],"to":[16,21,83,178],"generalize":[17],"out-of-distribution.":[18],"We":[19,47],"propose":[20],"push":[22],"the":[23,49,57,126,132,169],"cost-accuracy":[24],"Pareto":[25],"frontier":[26],"by":[27,62,135],"designing":[28],"observable-agnostic":[29],"electronic":[30],"ground-state":[31],"descriptor":[32],"models":[33],"(GSMs)":[34],"with":[35,56],"computational":[36],"costs":[37],"situated":[38],"between":[39],"MLIPs":[40],"Kohn-Sham":[42],"density":[43,111],"functional":[44],"theory":[45],"(KS-DFT).":[46],"align":[48],"learning":[50],"objectives":[51],"architectures":[53],"of":[54,60,75,131,156,163,171],"GSMs":[55,177],"governing":[58],"equations":[59],"KS-DFT":[61],"enforcing":[63],"physical":[64],"constraints":[65],"removing":[67],"optimization":[68],"pressure":[69],"on":[70,150],"unphysical":[71],"or":[72],"irrelevant":[73],"degrees":[74],"freedom.":[76],"In":[77],"our":[78,85],"size-extrapolation":[79],"experiments":[80],"from":[81],"QM9":[82],"QM40,":[84],"combined":[86],"contributions":[87],"OrthoNormal-Loss":[88],"(ON-Loss)":[89],"Grassmann":[91],"Restricted":[92],"Occupied-Orbital":[93],"Training":[94,122],"(GROOT)":[95],"reach":[96],"a":[97,141],"79.1%":[98],"energy":[99,127,161,184],"83.4%":[101],"force":[102,129],"mean":[103],"absolute":[104],"error":[105],"(MAE)":[106],"reduction":[107],"over":[108],"previous":[109],"state-of-the-art":[110],"GSMs.":[112],"For":[113],"Hamiltonian":[114],"GSMs,":[115],"ON-Loss":[116],"Residual":[118],"Optimal-gauge":[119],"Conditioning-aware":[120],"KS-Eq.":[121],"(ROCKET)":[123],"together":[124],"reduce":[125],"MAEs":[130],"strongest":[133],"baseline":[134],"99.8%":[136],"95.9%,":[138],"respectively.":[139],"Using":[140],"self-consistency":[142,173],"rejection":[143],"criterion,":[144],"we":[145,167],"filter":[146],"out":[147],"extrapolation":[148],"errors":[149,185],"QMugs,":[151],"rejecting":[152],"fewer":[153],"than":[154],"0.4%":[155],"predictions":[157],"while":[158],"reaching":[159,183],"an":[160],"MAE":[162],"0.07":[164],"mHa.":[165],"Finally,":[166],"demonstrate":[168],"efficiency":[170],"label-free":[172],"fine-tuning,":[174],"transfer":[176],"reactive":[179],"chemistry":[180],"in":[181],"Transition1x,":[182],"below":[186],"chemical":[187],"accuracy.":[188]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2026-10-09T00:00:00"}