{"id":"https://openalex.org/W7154309731","doi":"https://doi.org/10.48550/arxiv.2604.10171","title":"PoreDiT: A Scalable Generative Model for Large-Scale Digital Rock Reconstruction","display_name":"PoreDiT: A Scalable Generative Model for Large-Scale Digital Rock Reconstruction","publication_year":2026,"publication_date":"2026-04-11","ids":{"openalex":"https://openalex.org/W7154309731","doi":"https://doi.org/10.48550/arxiv.2604.10171"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.10171","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.10171","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.10171","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Huang, Yizhuo","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Huang, Yizhuo","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132589259","display_name":"Baoquan Sun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Baoquan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5133578574","display_name":"Haibo Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Haibo","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"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/T10491","display_name":"Enhanced Oil Recovery Techniques","score":0.7263000011444092,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10491","display_name":"Enhanced Oil Recovery Techniques","score":0.7263000011444092,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/T11751","display_name":"Lattice Boltzmann Simulation Studies","score":0.10119999945163727,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10591","display_name":"Theoretical and Computational Physics","score":0.018400000408291817,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6794000267982483},{"id":"https://openalex.org/keywords/high-fidelity","display_name":"High fidelity","score":0.5968999862670898},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.5026999711990356},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.4767000079154968},{"id":"https://openalex.org/keywords/grayscale","display_name":"Grayscale","score":0.47110000252723694},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.44780001044273376},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.42730000615119934},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4106999933719635}],"concepts":[{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6794000267982483},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6552000045776367},{"id":"https://openalex.org/C113364801","wikidata":"https://www.wikidata.org/wiki/Q26674","display_name":"High fidelity","level":2,"score":0.5968999862670898},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.5026999711990356},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.4767000079154968},{"id":"https://openalex.org/C78201319","wikidata":"https://www.wikidata.org/wiki/Q685727","display_name":"Grayscale","level":3,"score":0.47110000252723694},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4700999855995178},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.44780001044273376},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.42730000615119934},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4106999933719635},{"id":"https://openalex.org/C125112378","wikidata":"https://www.wikidata.org/wiki/Q176640","display_name":"Randomness","level":2,"score":0.37540000677108765},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.37070000171661377},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.3310999870300293},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.323199987411499},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.32280001044273376},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3075000047683716},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.30309998989105225},{"id":"https://openalex.org/C90278072","wikidata":"https://www.wikidata.org/wiki/Q216320","display_name":"Fluid dynamics","level":2,"score":0.2962000072002411},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.2816999852657318},{"id":"https://openalex.org/C459310","wikidata":"https://www.wikidata.org/wiki/Q117801","display_name":"Computational science","level":1,"score":0.27970001101493835},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.2777000069618225},{"id":"https://openalex.org/C3020199158","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"High resolution","level":2,"score":0.26969999074935913},{"id":"https://openalex.org/C194583477","wikidata":"https://www.wikidata.org/wiki/Q408891","display_name":"Physical law","level":2,"score":0.26600000262260437},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.26499998569488525},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2646999955177307},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.2606000006198883},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.2605000138282776},{"id":"https://openalex.org/C181843262","wikidata":"https://www.wikidata.org/wiki/Q640492","display_name":"Digital elevation model","level":2,"score":0.26030001044273376}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.10171","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.10171","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.10171","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.10171","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0,84],"manuscript":[1],"presents":[2],"PoreDiT,":[3],"a":[4,46],"novel":[5],"generative":[6],"model":[7,71],"designed":[8],"for":[9,77,129,137],"high-efficiency":[10],"digital":[11,22,96],"rock":[12,23,97],"reconstruction":[13],"at":[14],"gigavoxel":[15],"scales.":[16],"Addressing":[17],"the":[18,27,35,59,70,90],"significant":[19],"challenges":[20],"in":[21,139],"physics":[24],"(DRP),":[25],"particularly":[26],"trade-off":[28],"between":[29],"resolution":[30],"and":[31,34,81,117,133,145],"field-of-view":[32],"(FOV),":[33],"computational":[36,87],"bottlenecks":[37],"associated":[38],"with":[39],"traditional":[40],"deep":[41],"learning":[42],"architectures,":[43],"PoreDiT":[44,103],"leverages":[45],"three-dimensional":[47],"(3D)":[48],"Swin":[49],"Transformer":[50],"to":[51,108,123],"break":[52],"through":[53],"these":[54],"limitations.":[55],"By":[56],"directly":[57],"predicting":[58],"binary":[60],"probability":[61],"field":[62],"of":[63,67,92],"pore":[64],"spaces":[65],"instead":[66],"grayscale":[68],"intensities,":[69],"preserves":[72],"key":[73],"topological":[74],"features":[75],"critical":[76],"pore-scale":[78,115,140],"fluid":[79,141],"flow":[80],"transport":[82],"simulations.":[83],"approach":[85],"enhances":[86],"efficiency,":[88],"enabling":[89],"generation":[91],"ultra-large-scale":[93],"($1024^3$":[94],"voxels)":[95],"samples":[98],"on":[99],"consumer-grade":[100],"hardware.":[101],"Furthermore,":[102],"achieves":[104],"physical":[105],"fidelity":[106],"comparable":[107],"previous":[109],"state-of-the-art":[110],"methods,":[111],"including":[112],"accurate":[113],"porosity,":[114],"permeability,":[116],"Euler":[118],"characteristics.":[119],"The":[120],"model's":[121],"ability":[122],"scale":[124],"efficiently":[125],"opens":[126],"new":[127],"avenues":[128],"large-domain":[130],"hydrodynamic":[131],"simulations":[132],"provides":[134],"practical":[135],"solutions":[136],"researchers":[138],"mechanics,":[142],"reservoir":[143],"characterization,":[144],"carbon":[146],"sequestration.":[147]},"counts_by_year":[],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2026-04-15T00:00:00"}
