{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:R2ZRWHYPBMDCPARJBEKSJ2RJUZ","short_pith_number":"pith:R2ZRWHYP","schema_version":"1.0","canonical_sha256":"8eb31b1f0f0b06278229091524ea29a662fa71995875e8e466d9f2c315d13fe1","source":{"kind":"arxiv","id":"2512.16175","version":1},"attestation_state":"computed","paper":{"title":"Physics-Informed Neural Networks for Modeling the Martian Induced Magnetosphere","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG","physics.space-ph"],"primary_cat":"astro-ph.EP","authors_text":"Abigail Tadlock, Chi Zhang, Chuanfei Dong, Hongyang Zhou, Jiawei Gao, Liang Wang, Simin Shekarpaz, Xinmin Li, Yilan Qin","submitted_at":"2025-12-18T04:49:20Z","abstract_excerpt":"Understanding the magnetic field environment around Mars and its response to upstream solar wind conditions provide key insights into the processes driving atmospheric ion escape. To date, global models of Martian induced magnetosphere have been exclusively physics-based, relying on computationally intensive simulations. For the first time, we develop a data-driven model of the Martian induced magnetospheric magnetic field using Physics-Informed Neural Network (PINN) combined with MAVEN observations and physical laws. Trained under varying solar wind conditions, including B_IMF, P_SW, and {\\th"},"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":"2512.16175","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"astro-ph.EP","submitted_at":"2025-12-18T04:49:20Z","cross_cats_sorted":["cs.LG","physics.space-ph"],"title_canon_sha256":"c7dd38874d81936a6594af24828207968a5060e9f18042fec4cbffa5e8daed60","abstract_canon_sha256":"efd6ac11ebe457989d30ae4acec97890cfceb14c3547966e8928c4d16163393c"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-08-04T01:52:05.479136Z","signature_b64":"mjIkEJoQKQ7FOVx6vpdpvqjj8sE4JaR8hBev8pB3itidtOOblsVqPkEQ/+c1IPbawn0UwNYX2pq/ZWDENXpjCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8eb31b1f0f0b06278229091524ea29a662fa71995875e8e466d9f2c315d13fe1","last_reissued_at":"2026-08-04T01:52:05.477493Z","signature_status":"signed_v1","first_computed_at":"2026-08-04T01:52:05.477493Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Physics-Informed Neural Networks for Modeling the Martian Induced Magnetosphere","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG","physics.space-ph"],"primary_cat":"astro-ph.EP","authors_text":"Abigail Tadlock, Chi Zhang, Chuanfei Dong, Hongyang Zhou, Jiawei Gao, Liang Wang, Simin Shekarpaz, Xinmin Li, Yilan Qin","submitted_at":"2025-12-18T04:49:20Z","abstract_excerpt":"Understanding the magnetic field environment around Mars and its response to upstream solar wind conditions provide key insights into the processes driving atmospheric ion escape. To date, global models of Martian induced magnetosphere have been exclusively physics-based, relying on computationally intensive simulations. For the first time, we develop a data-driven model of the Martian induced magnetospheric magnetic field using Physics-Informed Neural Network (PINN) combined with MAVEN observations and physical laws. Trained under varying solar wind conditions, including B_IMF, P_SW, and {\\th"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2512.16175","kind":"arxiv","version":1},"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/2512.16175/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":"2512.16175","created_at":"2026-08-04T01:52:05.478744+00:00"},{"alias_kind":"arxiv_version","alias_value":"2512.16175v1","created_at":"2026-08-04T01:52:05.478744+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2512.16175","created_at":"2026-08-04T01:52:05.478744+00:00"},{"alias_kind":"pith_short_12","alias_value":"R2ZRWHYPBMDC","created_at":"2026-08-04T01:52:05.478744+00:00"},{"alias_kind":"pith_short_16","alias_value":"R2ZRWHYPBMDCPARJ","created_at":"2026-08-04T01:52:05.478744+00:00"},{"alias_kind":"pith_short_8","alias_value":"R2ZRWHYP","created_at":"2026-08-04T01:52:05.478744+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/R2ZRWHYPBMDCPARJBEKSJ2RJUZ","json":"https://pith.science/pith/R2ZRWHYPBMDCPARJBEKSJ2RJUZ.json","graph_json":"https://pith.science/api/pith-number/R2ZRWHYPBMDCPARJBEKSJ2RJUZ/graph.json","events_json":"https://pith.science/api/pith-number/R2ZRWHYPBMDCPARJBEKSJ2RJUZ/events.json","paper":"https://pith.science/paper/R2ZRWHYP"},"agent_actions":{"view_html":"https://pith.science/pith/R2ZRWHYPBMDCPARJBEKSJ2RJUZ","download_json":"https://pith.science/pith/R2ZRWHYPBMDCPARJBEKSJ2RJUZ.json","view_paper":"https://pith.science/paper/R2ZRWHYP","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2512.16175&json=true","fetch_graph":"https://pith.science/api/pith-number/R2ZRWHYPBMDCPARJBEKSJ2RJUZ/graph.json","fetch_events":"https://pith.science/api/pith-number/R2ZRWHYPBMDCPARJBEKSJ2RJUZ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/R2ZRWHYPBMDCPARJBEKSJ2RJUZ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/R2ZRWHYPBMDCPARJBEKSJ2RJUZ/action/storage_attestation","attest_author":"https://pith.science/pith/R2ZRWHYPBMDCPARJBEKSJ2RJUZ/action/author_attestation","sign_citation":"https://pith.science/pith/R2ZRWHYPBMDCPARJBEKSJ2RJUZ/action/citation_signature","submit_replication":"https://pith.science/pith/R2ZRWHYPBMDCPARJBEKSJ2RJUZ/action/replication_record"}},"created_at":"2026-08-04T01:52:05.478744+00:00","updated_at":"2026-08-04T01:52:05.478744+00:00"}