{"id":"https://openalex.org/W7163876244","doi":"https://doi.org/10.48550/arxiv.2606.07146","title":"Decision-Aware Evaluation of Physics-Informed Surrogates","display_name":"Decision-Aware Evaluation of Physics-Informed Surrogates","publication_year":2026,"publication_date":"2026-06-05","ids":{"openalex":"https://openalex.org/W7163876244","doi":"https://doi.org/10.48550/arxiv.2606.07146"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.07146","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.07146","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,"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"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.07146","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5138125359","display_name":"Daniel Cie\u015blak","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cie\u015blak, Daniel","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5079397804","display_name":"Andrzej Czy\u017cewski","orcid":"https://orcid.org/0000-0001-9159-8658"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Czy\u017cewski, Andrzej","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":0.8805000185966492,"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":0.8805000185966492,"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/T11206","display_name":"Model Reduction and Neural Networks","score":0.09059999883174896,"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"}},{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.002300000051036477,"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/testbed","display_name":"Testbed","score":0.7368000149726868},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.576200008392334},{"id":"https://openalex.org/keywords/oracle","display_name":"Oracle","score":0.5620999932289124},{"id":"https://openalex.org/keywords/limiting","display_name":"Limiting","score":0.43389999866485596},{"id":"https://openalex.org/keywords/comparability","display_name":"Comparability","score":0.4262999892234802},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.4178999960422516},{"id":"https://openalex.org/keywords/dimensionless-quantity","display_name":"Dimensionless quantity","score":0.4009000062942505},{"id":"https://openalex.org/keywords/learning-curve","display_name":"Learning curve","score":0.3806999921798706},{"id":"https://openalex.org/keywords/repeatability","display_name":"Repeatability","score":0.3050000071525574}],"concepts":[{"id":"https://openalex.org/C31395832","wikidata":"https://www.wikidata.org/wiki/Q1318674","display_name":"Testbed","level":2,"score":0.7368000149726868},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.576200008392334},{"id":"https://openalex.org/C55166926","wikidata":"https://www.wikidata.org/wiki/Q2892946","display_name":"Oracle","level":2,"score":0.5620999932289124},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5012999773025513},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.43389999866485596},{"id":"https://openalex.org/C197947376","wikidata":"https://www.wikidata.org/wiki/Q5155608","display_name":"Comparability","level":2,"score":0.4262999892234802},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.4178999960422516},{"id":"https://openalex.org/C24872484","wikidata":"https://www.wikidata.org/wiki/Q126818","display_name":"Dimensionless quantity","level":2,"score":0.4009000062942505},{"id":"https://openalex.org/C34585555","wikidata":"https://www.wikidata.org/wiki/Q1368723","display_name":"Learning curve","level":2,"score":0.3806999921798706},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3343999981880188},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33070001006126404},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3156000077724457},{"id":"https://openalex.org/C154020017","wikidata":"https://www.wikidata.org/wiki/Q520171","display_name":"Repeatability","level":2,"score":0.3050000071525574},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.3046000003814697},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.3012999892234802},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.30079999566078186},{"id":"https://openalex.org/C184389593","wikidata":"https://www.wikidata.org/wiki/Q603159","display_name":"Curve fitting","level":2,"score":0.29980000853538513},{"id":"https://openalex.org/C2780385302","wikidata":"https://www.wikidata.org/wiki/Q367158","display_name":"Protocol (science)","level":3,"score":0.2946999967098236},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.29420000314712524},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.2872999906539917},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.28630000352859497},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.2854999899864197},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.27379998564720154},{"id":"https://openalex.org/C34559072","wikidata":"https://www.wikidata.org/wiki/Q2334061","display_name":"Design of experiments","level":2,"score":0.2680000066757202},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2669999897480011},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.259799987077713},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.257099986076355},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.25279998779296875},{"id":"https://openalex.org/C2781204021","wikidata":"https://www.wikidata.org/wiki/Q6497091","display_name":"Lattice (music)","level":2,"score":0.2522999942302704}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.07146","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.07146","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,"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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.07146","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.07146","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,"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"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.7368650436401367,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Physics-informed":[0,78],"machine":[1],"learning":[2],"is":[3,70,99],"often":[4],"assessed":[5],"by":[6],"curve":[7,53,128],"error,":[8],"although":[9],"engineering":[10],"use":[11],"depends":[12],"on":[13],"downstream":[14],"decisions:":[15],"ranking":[16],"candidates,":[17],"avoiding":[18],"infeasible":[19],"designs":[20],"and":[21,49,59,65,88,111],"limiting":[22],"regret.":[23,61],"We":[24],"introduce":[25],"pinn-gym,":[26],"an":[27],"open":[28],"benchmark":[29,98],"for":[30,119],"material-conditioned":[31],"lattice":[32],"design":[33,76],"that":[34],"couples":[35],"a":[36,50,101,116],"transparent":[37],"reduced-order":[38],"crush-and-impact":[39],"oracle":[40],"with":[41],"five":[42],"printable":[43],"polymer":[44],"cards,":[45,113],"dimensionless":[46,89],"force-response":[47],"targets":[48],"protocol":[51],"spanning":[52],"fidelity,":[54],"physical":[55],"admissibility,":[56],"top-k":[57],"retrieval":[58],"mass":[60],"Across":[62],"per-material,":[63],"pooled":[64],"cross-material":[66],"settings,":[67],"low":[68],"nRMSE":[69],"frequently":[71],"insufficient":[72],"to":[73],"identify":[74],"useful":[75],"selections.":[77],"losses":[79],"alter":[80],"trade-offs":[81],"rather":[82,126],"than":[83,127],"monotonically":[84],"improving":[85],"all":[86],"metrics,":[87],"conditioning":[90],"improves":[91],"comparability":[92],"without":[93],"making":[94],"transfer":[95],"symmetric.":[96],"The":[97],"not":[100],"certified":[102],"material":[103,112],"model;":[104],"within":[105],"the":[106],"released":[107],"oracle,":[108],"candidate":[109],"generator":[110],"pinn-gym":[114],"provides":[115],"reproducible":[117],"testbed":[118],"evaluating":[120],"PIML":[121],"surrogates":[122],"as":[123],"decision":[124],"systems":[125],"predictors":[129],"alone.":[130]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-09T00:00:00"}
