{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:6G246MKGXWW7RNLOZWSFDAFNHD","short_pith_number":"pith:6G246MKG","schema_version":"1.0","canonical_sha256":"f1b5cf3146bdadf8b56ecda45180ad38c24018633b5b67e1ecd6e65e6b3aaad0","source":{"kind":"arxiv","id":"2602.11208","version":2},"attestation_state":"computed","paper":{"title":"Adaptive Physics Transformer with Fused Global-Local Attention for Subsurface Energy Systems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Carl Jacquemyn, Gege Wen, Matthew Jackson, Nok Hei (Hadrian) Fung, Randolph Settgast, Sally M. Benson, Xin Ju, Yuyan Zhang","submitted_at":"2026-02-10T22:48:58Z","abstract_excerpt":"The Earth's subsurface is a cornerstone of modern society, providing essential energy resources like hydrocarbons, geothermal, and minerals while serving as the primary reservoir for $CO_2$ sequestration. However, full physics numerical simulations of these systems are notoriously computationally expensive due to geological heterogeneity, high resolution requirements, and the tight coupling of physical processes with distinct propagation time scales. Here we propose the $\\textbf{Adaptive Physics Transformer}$ (APT), a geometry-, mesh-, and physics-agnostic neural operator that explicitly addre"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2602.11208","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-02-10T22:48:58Z","cross_cats_sorted":[],"title_canon_sha256":"5dad9bbf6d71d7e7052dab07967aa10c5f3539a1f384f06f049ed94e08ddc1d7","abstract_canon_sha256":"dcdd1dd5796d96c9cf5243c77f9911dda73f966d2fe61b03b7976a42d803231f"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-01T01:02:34.001095Z","signature_b64":"Zl1Z/TH9svQWiJImr/0GZDgulz+YAGHeI2VsoH73cBBmA68TVz8MGdqNVsavTfv0ycySGX7AB9OaV7HegSZlDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f1b5cf3146bdadf8b56ecda45180ad38c24018633b5b67e1ecd6e65e6b3aaad0","last_reissued_at":"2026-06-01T01:02:34.000195Z","signature_status":"signed_v1","first_computed_at":"2026-06-01T01:02:34.000195Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Adaptive Physics Transformer with Fused Global-Local Attention for Subsurface Energy Systems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Carl Jacquemyn, Gege Wen, Matthew Jackson, Nok Hei (Hadrian) Fung, Randolph Settgast, Sally M. Benson, Xin Ju, Yuyan Zhang","submitted_at":"2026-02-10T22:48:58Z","abstract_excerpt":"The Earth's subsurface is a cornerstone of modern society, providing essential energy resources like hydrocarbons, geothermal, and minerals while serving as the primary reservoir for $CO_2$ sequestration. However, full physics numerical simulations of these systems are notoriously computationally expensive due to geological heterogeneity, high resolution requirements, and the tight coupling of physical processes with distinct propagation time scales. Here we propose the $\\textbf{Adaptive Physics Transformer}$ (APT), a geometry-, mesh-, and physics-agnostic neural operator that explicitly addre"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2602.11208","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2602.11208/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2602.11208","created_at":"2026-06-01T01:02:34.000323+00:00"},{"alias_kind":"arxiv_version","alias_value":"2602.11208v2","created_at":"2026-06-01T01:02:34.000323+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2602.11208","created_at":"2026-06-01T01:02:34.000323+00:00"},{"alias_kind":"pith_short_12","alias_value":"6G246MKGXWW7","created_at":"2026-06-01T01:02:34.000323+00:00"},{"alias_kind":"pith_short_16","alias_value":"6G246MKGXWW7RNLO","created_at":"2026-06-01T01:02:34.000323+00:00"},{"alias_kind":"pith_short_8","alias_value":"6G246MKG","created_at":"2026-06-01T01:02:34.000323+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/6G246MKGXWW7RNLOZWSFDAFNHD","json":"https://pith.science/pith/6G246MKGXWW7RNLOZWSFDAFNHD.json","graph_json":"https://pith.science/api/pith-number/6G246MKGXWW7RNLOZWSFDAFNHD/graph.json","events_json":"https://pith.science/api/pith-number/6G246MKGXWW7RNLOZWSFDAFNHD/events.json","paper":"https://pith.science/paper/6G246MKG"},"agent_actions":{"view_html":"https://pith.science/pith/6G246MKGXWW7RNLOZWSFDAFNHD","download_json":"https://pith.science/pith/6G246MKGXWW7RNLOZWSFDAFNHD.json","view_paper":"https://pith.science/paper/6G246MKG","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2602.11208&json=true","fetch_graph":"https://pith.science/api/pith-number/6G246MKGXWW7RNLOZWSFDAFNHD/graph.json","fetch_events":"https://pith.science/api/pith-number/6G246MKGXWW7RNLOZWSFDAFNHD/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/6G246MKGXWW7RNLOZWSFDAFNHD/action/timestamp_anchor","attest_storage":"https://pith.science/pith/6G246MKGXWW7RNLOZWSFDAFNHD/action/storage_attestation","attest_author":"https://pith.science/pith/6G246MKGXWW7RNLOZWSFDAFNHD/action/author_attestation","sign_citation":"https://pith.science/pith/6G246MKGXWW7RNLOZWSFDAFNHD/action/citation_signature","submit_replication":"https://pith.science/pith/6G246MKGXWW7RNLOZWSFDAFNHD/action/replication_record"}},"created_at":"2026-06-01T01:02:34.000323+00:00","updated_at":"2026-06-01T01:02:34.000323+00:00"}