{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:PXSLDW5FDVMTW65QXZ4UOHO2NZ","short_pith_number":"pith:PXSLDW5F","schema_version":"1.0","canonical_sha256":"7de4b1dba51d593b7bb0be79471dda6e45923422d8cfc8fea4b88b8c5e26e35c","source":{"kind":"arxiv","id":"2211.01094","version":2},"attestation_state":"computed","paper":{"title":"Simultaneous CTEQ-TEA extraction of PDFs and SMEFT parameters from jet and $t{\\bar t}$ data","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["hep-ex"],"primary_cat":"hep-ph","authors_text":"Dianyu Liu, Jun Gao, Meisen Gao, T. J. Hobbs, Xiaomin Shen","submitted_at":"2022-11-02T13:10:29Z","abstract_excerpt":"Recasting phenomenological Lagrangians in terms of SM effective field theory (SMEFT) provides a valuable means of connecting potential BSM physics at momenta well above the electroweak scale to experimental signatures at lower energies. In this work we jointly fit the Wilson coefficients of SMEFT operators as well as the PDFs in an extension of the CT18 global analysis framework, obtaining self-consistent constraints to possible BSM physics effects. Global fits are boosted with machine-learning techniques in the form of neural networks to ensure efficient scans of the full PDF+SMEFT parameter "},"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":"2211.01094","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"hep-ph","submitted_at":"2022-11-02T13:10:29Z","cross_cats_sorted":["hep-ex"],"title_canon_sha256":"3b384b891d98d3fc3a7d708f88e81da27ae155ff84ed9d37e7625d95d4e7e546","abstract_canon_sha256":"1c4a722402453a3b31b73eb46df12d271ace3e6bfac14230d450ea0599c994d5"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:12:38.510358Z","signature_b64":"O+YZ9GZr/BJDiHk6ijXlcqPRpLrSrBY3oPooqv9eqlzlm4PAWJqLnpc9fgYB1/a3EykHhg5Z7V8PFdP6SkOhCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7de4b1dba51d593b7bb0be79471dda6e45923422d8cfc8fea4b88b8c5e26e35c","last_reissued_at":"2026-07-05T06:12:38.509985Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:12:38.509985Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Simultaneous CTEQ-TEA extraction of PDFs and SMEFT parameters from jet and $t{\\bar t}$ data","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["hep-ex"],"primary_cat":"hep-ph","authors_text":"Dianyu Liu, Jun Gao, Meisen Gao, T. J. Hobbs, Xiaomin Shen","submitted_at":"2022-11-02T13:10:29Z","abstract_excerpt":"Recasting phenomenological Lagrangians in terms of SM effective field theory (SMEFT) provides a valuable means of connecting potential BSM physics at momenta well above the electroweak scale to experimental signatures at lower energies. In this work we jointly fit the Wilson coefficients of SMEFT operators as well as the PDFs in an extension of the CT18 global analysis framework, obtaining self-consistent constraints to possible BSM physics effects. Global fits are boosted with machine-learning techniques in the form of neural networks to ensure efficient scans of the full PDF+SMEFT parameter "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.01094","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/2211.01094/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":"2211.01094","created_at":"2026-07-05T06:12:38.510043+00:00"},{"alias_kind":"arxiv_version","alias_value":"2211.01094v2","created_at":"2026-07-05T06:12:38.510043+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.01094","created_at":"2026-07-05T06:12:38.510043+00:00"},{"alias_kind":"pith_short_12","alias_value":"PXSLDW5FDVMT","created_at":"2026-07-05T06:12:38.510043+00:00"},{"alias_kind":"pith_short_16","alias_value":"PXSLDW5FDVMTW65Q","created_at":"2026-07-05T06:12:38.510043+00:00"},{"alias_kind":"pith_short_8","alias_value":"PXSLDW5F","created_at":"2026-07-05T06:12:38.510043+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":2,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2607.07791","citing_title":"PDF effects in high-mass Drell-Yan SMEFT analyses across flavour space","ref_index":13,"is_internal_anchor":true},{"citing_arxiv_id":"2412.07651","citing_title":"An EWPD SMEFT likelihood for the LHC -- and how to improve it with measurements of W and Z boson properties","ref_index":78,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/PXSLDW5FDVMTW65QXZ4UOHO2NZ","json":"https://pith.science/pith/PXSLDW5FDVMTW65QXZ4UOHO2NZ.json","graph_json":"https://pith.science/api/pith-number/PXSLDW5FDVMTW65QXZ4UOHO2NZ/graph.json","events_json":"https://pith.science/api/pith-number/PXSLDW5FDVMTW65QXZ4UOHO2NZ/events.json","paper":"https://pith.science/paper/PXSLDW5F"},"agent_actions":{"view_html":"https://pith.science/pith/PXSLDW5FDVMTW65QXZ4UOHO2NZ","download_json":"https://pith.science/pith/PXSLDW5FDVMTW65QXZ4UOHO2NZ.json","view_paper":"https://pith.science/paper/PXSLDW5F","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2211.01094&json=true","fetch_graph":"https://pith.science/api/pith-number/PXSLDW5FDVMTW65QXZ4UOHO2NZ/graph.json","fetch_events":"https://pith.science/api/pith-number/PXSLDW5FDVMTW65QXZ4UOHO2NZ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/PXSLDW5FDVMTW65QXZ4UOHO2NZ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/PXSLDW5FDVMTW65QXZ4UOHO2NZ/action/storage_attestation","attest_author":"https://pith.science/pith/PXSLDW5FDVMTW65QXZ4UOHO2NZ/action/author_attestation","sign_citation":"https://pith.science/pith/PXSLDW5FDVMTW65QXZ4UOHO2NZ/action/citation_signature","submit_replication":"https://pith.science/pith/PXSLDW5FDVMTW65QXZ4UOHO2NZ/action/replication_record"}},"created_at":"2026-07-05T06:12:38.510043+00:00","updated_at":"2026-07-05T06:12:38.510043+00:00"}