{"id":"https://openalex.org/W7220912320","doi":"https://doi.org/10.48550/arxiv.2610.08116","title":"Soft Contrastive Learning for Unsupervised Discovery of Phases of Matter","display_name":"Soft Contrastive Learning for Unsupervised Discovery of Phases of Matter","publication_year":2026,"publication_date":"2026-10-06","ids":{"openalex":"https://openalex.org/W7220912320","doi":"https://doi.org/10.48550/arxiv.2610.08116"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2610.08116","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.08116","pdf_url":"https://arxiv.org/pdf/2610.08116","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/2610.08116","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5157779836","display_name":"V\u00edt Bene\u0161","orcid":"https://orcid.org/0000-0003-2289-7480","observed_orcids":["https://orcid.org/0000-0003-2289-7480"]},"institutions":[{"id":"https://openalex.org/I4210122644","display_name":"FZU - Institute of Physics of the Czech Academy of Sciences","ror":"https://ror.org/02yhj4v17","country_code":"CZ","type":"facility","lineage":["https://openalex.org/I202391551","https://openalex.org/I4210122644"]},{"id":"https://openalex.org/I44504214","display_name":"Czech Technical University in Prague","ror":"https://ror.org/03kqpb082","country_code":"CZ","type":"education","lineage":["https://openalex.org/I44504214"]}],"countries":["CZ"],"is_corresponding":false,"raw_author_name":"Bene\u0161, V\u00edt","raw_affiliation_strings":["Department of Materials , Faculty of Nuclear Sciences and Physical Engineering , Czech Technical University in Prague , Trojanova 13 , Prague 120 00 , Czech Republic","FZU -Institute of Physics of the Czech Academy of Sciences , Na Slovance 1999/2 , 182 00 Prague , Czech Republic"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Materials , Faculty of Nuclear Sciences and Physical Engineering , Czech Technical University in Prague , Trojanova 13 , Prague 120 00 , Czech Republic","institution_ids":["https://openalex.org/I44504214"]},{"raw_affiliation_string":"FZU -Institute of Physics of the Czech Academy of Sciences , Na Slovance 1999/2 , 182 00 Prague , Czech Republic","institution_ids":["https://openalex.org/I4210122644"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022364790","display_name":"Pavel Bal\u00e1\u017e","orcid":"https://orcid.org/0000-0003-0016-9271","observed_orcids":["https://orcid.org/0000-0003-0016-9271"]},"institutions":[{"id":"https://openalex.org/I4210122644","display_name":"FZU - Institute of Physics of the Czech Academy of Sciences","ror":"https://ror.org/02yhj4v17","country_code":"CZ","type":"facility","lineage":["https://openalex.org/I202391551","https://openalex.org/I4210122644"]}],"countries":["CZ"],"is_corresponding":false,"raw_author_name":"Bal\u00e1\u017e, Pavel","raw_affiliation_strings":["FZU -Institute of Physics of the Czech Academy of Sciences , Na Slovance 1999/2 , 182 00 Prague , Czech Republic"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"FZU -Institute of Physics of the Czech Academy of Sciences , Na Slovance 1999/2 , 182 00 Prague , Czech Republic","institution_ids":["https://openalex.org/I4210122644"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005512014","display_name":"Dmytro Bohdanov","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210122644","display_name":"FZU - Institute of Physics of the Czech Academy of Sciences","ror":"https://ror.org/02yhj4v17","country_code":"CZ","type":"facility","lineage":["https://openalex.org/I202391551","https://openalex.org/I4210122644"]},{"id":"https://openalex.org/I44504214","display_name":"Czech Technical University in Prague","ror":"https://ror.org/03kqpb082","country_code":"CZ","type":"education","lineage":["https://openalex.org/I44504214"]}],"countries":["CZ"],"is_corresponding":false,"raw_author_name":"Bohdanov, Dmytro","raw_affiliation_strings":["Department of Solid State Physics , Faculty of Nuclear Sciences and Physical Engineering , Czech Technical University in Prague , Trojanova 13 , Prague 120 00 , Czech Republic","FZU -Institute of Physics of the Czech Academy of Sciences , Na Slovance 1999/2 , 182 00 Prague , Czech Republic"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Solid State Physics , Faculty of Nuclear Sciences and Physical Engineering , Czech Technical University in Prague , Trojanova 13 , Prague 120 00 , Czech Republic","institution_ids":["https://openalex.org/I44504214"]},{"raw_affiliation_string":"FZU -Institute of Physics of the Czech Academy of Sciences , Na Slovance 1999/2 , 182 00 Prague , Czech Republic","institution_ids":["https://openalex.org/I4210122644"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060309049","display_name":"J. Hlinka","orcid":"https://orcid.org/0000-0002-9293-4462","observed_orcids":["https://orcid.org/0000-0002-9293-4462"]},"institutions":[{"id":"https://openalex.org/I4210122644","display_name":"FZU - Institute of Physics of the Czech Academy of Sciences","ror":"https://ror.org/02yhj4v17","country_code":"CZ","type":"facility","lineage":["https://openalex.org/I202391551","https://openalex.org/I4210122644"]}],"countries":["CZ"],"is_corresponding":false,"raw_author_name":"Hlinka, Ji\u0159\u00ed","raw_affiliation_strings":["FZU -Institute of Physics of the Czech Academy of Sciences , Na Slovance 1999/2 , 182 00 Prague , Czech Republic"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"FZU -Institute of Physics of the Czech Academy of Sciences , Na Slovance 1999/2 , 182 00 Prague , Czech Republic","institution_ids":["https://openalex.org/I4210122644"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"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":0.9824000000953674,"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":0.9824000000953674,"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/T10591","display_name":"Theoretical and Computational Physics","score":0.005100000184029341,"subfield":{"id":"https://openalex.org/subfields/3104","display_name":"Condensed Matter 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/T11206","display_name":"Model Reduction and Neural Networks","score":0.0044999998062849045,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/phase-diagram-construction","display_name":"phase diagram construction","score":0.8299999833106995},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"unsupervised learning","score":0.8050000071525574},{"id":"https://openalex.org/keywords/contrastive-learning","display_name":"contrastive learning","score":0.8029999732971191},{"id":"https://openalex.org/keywords/soft-labels","display_name":"soft labels","score":0.7210000157356262},{"id":"https://openalex.org/keywords/representation-learning","display_name":"representation learning","score":0.6050000190734863},{"id":"https://openalex.org/keywords/monte-carlo-simulated-annealing","display_name":"Monte Carlo simulated annealing","score":0.8859999775886536},{"id":"https://openalex.org/keywords/data-generation","display_name":"data generation","score":0.6060000061988831},{"id":"https://openalex.org/keywords/coupled-order-parameters","display_name":"coupled order parameters","score":0.765999972820282},{"id":"https://openalex.org/keywords/phase-behavior","display_name":"phase behavior","score":0.41499999165534973},{"id":"https://openalex.org/keywords/condensed-matter","display_name":"condensed matter","score":0.4779999852180481}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7196000218391418},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6880000233650208},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5331000089645386},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4945000112056732},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4916999936103821},{"id":"https://openalex.org/C31395832","wikidata":"https://www.wikidata.org/wiki/Q1318674","display_name":"Testbed","level":2,"score":0.490200012922287},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4602000117301941},{"id":"https://openalex.org/C126980161","wikidata":"https://www.wikidata.org/wiki/Q863783","display_name":"Simulated annealing","level":2,"score":0.4390000104904175},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3668999969959259},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.3481000065803528},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3474000096321106},{"id":"https://openalex.org/C44280652","wikidata":"https://www.wikidata.org/wiki/Q104837","display_name":"Phase (matter)","level":2,"score":0.296099990606308},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.2928999960422516},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.28040000796318054},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2736000120639801},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.26260000467300415},{"id":"https://openalex.org/C2778334786","wikidata":"https://www.wikidata.org/wiki/Q1586270","display_name":"Variation (astronomy)","level":2,"score":0.2565000057220459},{"id":"https://openalex.org/C47822265","wikidata":"https://www.wikidata.org/wiki/Q854457","display_name":"Complex system","level":2,"score":0.25459998846054077}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2610.08116","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.08116","pdf_url":"https://arxiv.org/pdf/2610.08116","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.2610.08116","doi":"https://doi.org/10.48550/arxiv.2610.08116","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2610.08116","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:2610.08116","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.08116","pdf_url":"https://arxiv.org/pdf/2610.08116","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":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7220912320.pdf","grobid_xml":"https://content.openalex.org/works/W7220912320.grobid-xml"},"referenced_works_count":11,"referenced_works":["https://openalex.org/W2279221249","https://openalex.org/W2531147647","https://openalex.org/W3005680577","https://openalex.org/W3035524453","https://openalex.org/W3036601975","https://openalex.org/W3135367836","https://openalex.org/W3148912309","https://openalex.org/W3156636935","https://openalex.org/W4297808394","https://openalex.org/W4313528212","https://openalex.org/W7220705663"],"related_works":["https://openalex.org/W4313528212","https://openalex.org/W4414284360","https://openalex.org/W2951618391","https://openalex.org/W7220218447","https://openalex.org/W4296502121","https://openalex.org/W4409413097","https://openalex.org/W7205886057","https://openalex.org/W2727796268","https://openalex.org/W4406205136","https://openalex.org/W3195056591"],"abstract_inverted_index":{"A":[0],"machine":[1],"learning":[2,27],"(ML)":[3],"framework":[4,115],"for":[5,68,82,137],"phase-diagram":[6,84,154],"construction":[7,155],"in":[8,46,97,106,124],"condensed":[9],"matter":[10],"systems":[11],"with":[12,24,160],"unknown":[13],"phase":[14,61,142],"structure":[15],"is":[16,39,110,116],"presented.":[17],"The":[18,114,144],"method":[19],"combines":[20],"physically":[21,134,149],"motivated":[22,135],"descriptors":[23,100],"contrastive":[25,51,108],"representation":[26],"and":[28,130,141],"a":[29,34,50,56,72,92,119,133,148],"two-stage":[30],"data-generation":[31],"workflow.":[32],"First,":[33],"sparse":[35],"set":[36],"of":[37,79,94,126],"configurations":[38,62],"generated":[40],"by":[41],"Monte":[42],"Carlo":[43],"simulated":[44],"annealing":[45],"order":[47,87],"to":[48,88,152],"train":[49],"neural":[52],"network":[53],"that":[54,156],"produces":[55],"low-dimensional":[57],"embedding.":[58],"Consequently,":[59],"representative":[60],"are":[63,101],"used":[64,102,131],"as":[65,103,112,132],"initial":[66],"conditions":[67],"gradient-based":[69],"optimization":[70],"on":[71,118],"dense":[73],"parameter":[74],"grid,":[75],"enabling":[76],"efficient":[77],"generation":[78],"refined":[80],"datasets":[81],"high-resolution":[83],"construction.":[85],"In":[86],"optimize":[89],"the":[90,95,107],"workflow,":[91],"variant":[93],"method,":[96],"which":[98],"derived":[99],"soft":[104],"labels":[105],"objective,":[109],"examined":[111],"well.":[113],"demonstrated":[117],"PbZrO3-inspired":[120],"model":[121],"potential":[122],"formulated":[123],"terms":[125],"coupled":[127],"order-parameter":[128],"fields":[129],"testbed":[136],"exploring":[138],"configuration":[139],"diversity":[140],"behavior.":[143],"proposed":[145],"approach":[146],"provides":[147],"informed":[150],"route":[151],"ML-assisted":[153],"integrates":[157],"data":[158],"analysis":[159],"adaptive":[161],"dataset":[162],"refinement.":[163]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2026-10-09T00:00:00"}