{"id":"https://openalex.org/W7204779590","doi":"https://doi.org/10.48550/arxiv.2608.28239","title":"QUBO-Compatible Active Learning for Inverse Design of High-Entropy Alloys","display_name":"QUBO-Compatible Active Learning for Inverse Design of High-Entropy Alloys","publication_year":2026,"publication_date":"2026-08-28","ids":{"openalex":"https://openalex.org/W7204779590","doi":"https://doi.org/10.48550/arxiv.2608.28239"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2608.28239","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2608.28239","pdf_url":"https://arxiv.org/pdf/2608.28239","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-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","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/2608.28239","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5069570302","display_name":"Giorgio Silvi","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Silvi, Giorgio","raw_affiliation_strings":["HQS Quantum Simulations GmbH , 76131 Karlsruhe , Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"HQS Quantum Simulations GmbH , 76131 Karlsruhe , Germany","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010563140","display_name":"Kirsten Bark","orcid":"https://orcid.org/0000-0001-8788-4483","observed_orcids":["https://orcid.org/0000-0001-8788-4483"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bark, Kirsten","raw_affiliation_strings":["HQS Quantum Simulations GmbH , 76131 Karlsruhe , Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"HQS Quantum Simulations GmbH , 76131 Karlsruhe , Germany","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5097372937","display_name":"Rolando Reiner","orcid":"https://orcid.org/0009-0008-6692-7470","observed_orcids":["https://orcid.org/0009-0008-6692-7470"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Reiner, Rolando","raw_affiliation_strings":["HQS Quantum Simulations GmbH , 76131 Karlsruhe , Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"HQS Quantum Simulations GmbH , 76131 Karlsruhe , Germany","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052532888","display_name":"Nicolas Vogt","orcid":"https://orcid.org/0000-0002-3657-7042","observed_orcids":["https://orcid.org/0000-0002-3657-7042"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Vogt, Nicolas","raw_affiliation_strings":["HQS Quantum Simulations GmbH , 76131 Karlsruhe , Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"HQS Quantum Simulations GmbH , 76131 Karlsruhe , Germany","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070404383","display_name":"Thomas Plehn","orcid":"https://orcid.org/0000-0002-4949-6655","observed_orcids":["https://orcid.org/0000-0002-4949-6655"]},"institutions":[{"id":"https://openalex.org/I2898391981","display_name":"Deutsches Zentrum f\u00fcr Luft- und Raumfahrt e. V. (DLR)","ror":"https://ror.org/04bwf3e34","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2898391981"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Plehn, Thomas","raw_affiliation_strings":["Institute for Frontier Materials on Earth and in Space , German Aerospace Center (DLR) , Linder Hoehe , Cologne , 51147 , Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Frontier Materials on Earth and in Space , German Aerospace Center (DLR) , Linder Hoehe , Cologne , 51147 , Germany","institution_ids":["https://openalex.org/I2898391981"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024610575","display_name":"Daniel Barrag\u00e1n-Yani","orcid":"https://orcid.org/0000-0001-9447-3674","observed_orcids":["https://orcid.org/0000-0001-9447-3674"]},"institutions":[{"id":"https://openalex.org/I2898391981","display_name":"Deutsches Zentrum f\u00fcr Luft- und Raumfahrt e. V. (DLR)","ror":"https://ror.org/04bwf3e34","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2898391981"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Barragan-Yani, Daniel","raw_affiliation_strings":["Institute for Frontier Materials on Earth and in Space , German Aerospace Center (DLR) , Linder Hoehe , Cologne , 51147 , Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Frontier Materials on Earth and in Space , German Aerospace Center (DLR) , Linder Hoehe , Cologne , 51147 , Germany","institution_ids":["https://openalex.org/I2898391981"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045887239","display_name":"M. Landmann","orcid":"https://orcid.org/0000-0003-3348-0656","observed_orcids":["https://orcid.org/0000-0003-3348-0656"]},"institutions":[{"id":"https://openalex.org/I2898391981","display_name":"Deutsches Zentrum f\u00fcr Luft- und Raumfahrt e. V. (DLR)","ror":"https://ror.org/04bwf3e34","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2898391981"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Landmann, Marc","raw_affiliation_strings":["Institute for Frontier Materials on Earth and in Space , German Aerospace Center (DLR) , Linder Hoehe , Cologne , 51147 , Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Frontier Materials on Earth and in Space , German Aerospace Center (DLR) , Linder Hoehe , Cologne , 51147 , Germany","institution_ids":["https://openalex.org/I2898391981"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058091006","display_name":"David Melching","orcid":"https://orcid.org/0000-0001-5111-6511","observed_orcids":["https://orcid.org/0000-0001-5111-6511"]},"institutions":[{"id":"https://openalex.org/I2898391981","display_name":"Deutsches Zentrum f\u00fcr Luft- und Raumfahrt e. V. (DLR)","ror":"https://ror.org/04bwf3e34","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2898391981"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Melching, David","raw_affiliation_strings":["Institute for Frontier Materials on Earth and in Space , German Aerospace Center (DLR) , Linder Hoehe , Cologne , 51147 , Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Frontier Materials on Earth and in Space , German Aerospace Center (DLR) , Linder Hoehe , Cologne , 51147 , Germany","institution_ids":["https://openalex.org/I2898391981"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"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":1.0,"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":1.0,"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/T11143","display_name":"High Entropy Alloys Studies","score":0.0,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.0,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/high-entropy-alloys","display_name":"high-entropy alloys","score":0.902999997138977},{"id":"https://openalex.org/keywords/inverse-design","display_name":"inverse design","score":0.8679999709129333},{"id":"https://openalex.org/keywords/qubo","display_name":"QUBO","score":0.8679999709129333},{"id":"https://openalex.org/keywords/active-learning-machine-learning","display_name":"active learning (machine learning)","score":0.8190000057220459},{"id":"https://openalex.org/keywords/graph-neural-networks","display_name":"graph neural networks","score":0.5820000171661377},{"id":"https://openalex.org/keywords/latent-space","display_name":"latent space","score":0.41499999165534973},{"id":"https://openalex.org/keywords/materials-design","display_name":"materials design","score":0.3779999911785126},{"id":"https://openalex.org/keywords/quantum-annealing","display_name":"quantum annealing","score":0.5139999985694885}],"concepts":[{"id":"https://openalex.org/C177179195","wikidata":"https://www.wikidata.org/wiki/Q7268372","display_name":"Quadratic unconstrained binary optimization","level":4,"score":0.7067000269889832},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.6395999789237976},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.625},{"id":"https://openalex.org/C129844170","wikidata":"https://www.wikidata.org/wiki/Q41299","display_name":"Quadratic equation","level":2,"score":0.571399986743927},{"id":"https://openalex.org/C2778049539","wikidata":"https://www.wikidata.org/wiki/Q17002908","display_name":"Bayesian optimization","level":2,"score":0.5527999997138977},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5264000296592712},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5156000256538391},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4740999937057495},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.3986999988555908},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.3880000114440918},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.367000013589859},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.3626999855041504},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.35830000042915344},{"id":"https://openalex.org/C34559072","wikidata":"https://www.wikidata.org/wiki/Q2334061","display_name":"Design of experiments","level":2,"score":0.34880000352859497},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3472000062465668},{"id":"https://openalex.org/C135252773","wikidata":"https://www.wikidata.org/wiki/Q1567213","display_name":"Inverse problem","level":2,"score":0.34549999237060547},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.3440999984741211},{"id":"https://openalex.org/C81845259","wikidata":"https://www.wikidata.org/wiki/Q290117","display_name":"Quadratic programming","level":2,"score":0.34200000762939453},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.3237999975681305},{"id":"https://openalex.org/C198927703","wikidata":"https://www.wikidata.org/wiki/Q4373881","display_name":"Sequential quadratic programming","level":3,"score":0.30649998784065247},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.296999990940094},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29190000891685486},{"id":"https://openalex.org/C2778648169","wikidata":"https://www.wikidata.org/wiki/Q967768","display_name":"Compatibility (geochemistry)","level":2,"score":0.26579999923706055},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.26429998874664307},{"id":"https://openalex.org/C1893757","wikidata":"https://www.wikidata.org/wiki/Q3653001","display_name":"Inversion (geology)","level":3,"score":0.25949999690055847},{"id":"https://openalex.org/C68781425","wikidata":"https://www.wikidata.org/wiki/Q2052203","display_name":"Multi-objective optimization","level":2,"score":0.25920000672340393},{"id":"https://openalex.org/C2780695315","wikidata":"https://www.wikidata.org/wiki/Q3799040","display_name":"Unobservable","level":2,"score":0.2578999996185303},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.2567000091075897},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.2563000023365021},{"id":"https://openalex.org/C34972735","wikidata":"https://www.wikidata.org/wiki/Q2920267","display_name":"Engineering design process","level":2,"score":0.2535000145435333}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2608.28239","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2608.28239","pdf_url":"https://arxiv.org/pdf/2608.28239","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-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2608.28239","doi":"https://doi.org/10.48550/arxiv.2608.28239","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2608.28239","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2608.28239","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2608.28239","pdf_url":"https://arxiv.org/pdf/2608.28239","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-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7204779590.pdf","grobid_xml":"https://content.openalex.org/works/W7204779590.grobid-xml"},"referenced_works_count":26,"referenced_works":["https://openalex.org/W1568345435","https://openalex.org/W1983624953","https://openalex.org/W2024060531","https://openalex.org/W2039122980","https://openalex.org/W2295739661","https://openalex.org/W2883583109","https://openalex.org/W2884430236","https://openalex.org/W2887230019","https://openalex.org/W2916338083","https://openalex.org/W2921873493","https://openalex.org/W2951539866","https://openalex.org/W4200630323","https://openalex.org/W4224291578","https://openalex.org/W4288048022","https://openalex.org/W4296126761","https://openalex.org/W4306956168","https://openalex.org/W4380997161","https://openalex.org/W4381996662","https://openalex.org/W4397010572","https://openalex.org/W4406120297","https://openalex.org/W4407369004","https://openalex.org/W4415232694","https://openalex.org/W4417267582","https://openalex.org/W7134056750","https://openalex.org/W7162877891","https://openalex.org/W7167638685"],"related_works":["https://openalex.org/W4412188808","https://openalex.org/W7105110502","https://openalex.org/W7212082430","https://openalex.org/W4403471049","https://openalex.org/W7117236149","https://openalex.org/W4412433707","https://openalex.org/W4417209235","https://openalex.org/W4310886834","https://openalex.org/W7077512121","https://openalex.org/W7115564227"],"abstract_inverted_index":{"Machine-learned":[0],"forward":[1],"models":[2],"can":[3,149,163],"rapidly":[4],"predict":[5],"alloy":[6],"properties,":[7],"but":[8],"their":[9],"use":[10],"for":[11,36,176],"inverse":[12,37,180],"design":[13,38],"remains":[14,127],"challenging":[15],"when":[16],"the":[17,75,108,119,140,145,167],"search":[18,98,121],"should":[19],"also":[20],"retain":[21],"compatibility":[22],"with":[23,83,129],"quadratic":[24,66,147],"unconstrained":[25],"binary":[26,54,59],"optimization":[27,132,170],"(QUBO).":[28],"Here,":[29],"we":[30],"develop":[31],"a":[32,43,48,58,94,135,154,173],"QUBO-compatible":[33,125,177],"active-learning":[34],"framework":[35,76],"of":[39,65,97],"high-entropy":[40],"alloys":[41],"using":[42],"pretrained":[44],"graph-neural-network":[45],"predictor":[46],"as":[47,153],"fixed":[49],"property":[50],"oracle.":[51],"A":[52],"property-guided":[53],"variational":[55],"autoencoder":[56],"provides":[57],"latent":[60,105],"representation,":[61],"while":[62,112],"an":[63],"ensemble":[64],"factorization":[67],"machines":[68],"guides":[69],"candidate":[70,91],"selection.":[71],"We":[72],"systematically":[73],"benchmark":[74],"through":[77],"controlled":[78],"latent-space":[79],"ablations":[80],"and":[81],"comparison":[82],"direct":[84],"composition-space":[85,136],"optimization.":[86],"The":[87,123],"results":[88,157],"show":[89,158],"that":[90,159],"generation":[92],"is":[93],"major":[95],"determinant":[96],"performance:":[99],"local":[100],"perturbations":[101],"around":[102],"previously":[103],"high-performing":[104],"codes":[106],"provide":[107],"largest":[109],"workflow-specific":[110],"improvement,":[111],"surrogate-based":[113],"selection":[114],"further":[115],"prioritizes":[116],"candidates":[117],"within":[118],"enriched":[120],"pool.":[122],"resulting":[124],"workflow":[126],"competitive":[128],"strong":[130],"classical":[131],"strategies,":[133],"although":[134],"genetic":[137],"algorithm":[138],"achieves":[139],"highest":[141],"mean":[142],"score.":[143],"Finally,":[144],"learned":[146],"surrogate":[148],"be":[150,164],"exported":[151],"directly":[152],"QUBO.":[155],"These":[156],"effective":[160],"data":[161],"acquisition":[162],"separated":[165],"from":[166],"final":[168],"QUBO":[169],"endpoint,":[171],"providing":[172],"benchmarked":[174],"route":[175],"data-driven":[178],"materials":[179],"design.":[181]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2026-09-01T00:00:00"}