{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:OO6JW23TINCIQR36V2VH35VIP3","short_pith_number":"pith:OO6JW23T","schema_version":"1.0","canonical_sha256":"73bc9b6b73434488477eaeaa7df6a87efb2dfec9f5c9052047b0e1e13e493d80","source":{"kind":"arxiv","id":"2310.07752","version":3},"attestation_state":"computed","paper":{"title":"Precision-Machine Learning for the Matrix Element Method","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"hep-ph","authors_text":"Anja Butter, Nathan Huetsch, Ramon Winterhalder, Theo Heimel, Tilman Plehn","submitted_at":"2023-10-11T18:00:00Z","abstract_excerpt":"The matrix element method is the LHC inference method of choice for limited statistics. We present a dedicated machine learning framework, based on efficient phase-space integration, a learned acceptance and transfer function. It is based on a choice of INN and diffusion networks, and a transformer to solve jet combinatorics. We showcase this setup for the CP-phase of the top Yukawa coupling in associated Higgs and single-top production."},"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":"2310.07752","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"hep-ph","submitted_at":"2023-10-11T18:00:00Z","cross_cats_sorted":[],"title_canon_sha256":"4a05ae68f1ee800bc6b45ed2dcb716c21618670aaed280e53794307f67261522","abstract_canon_sha256":"6856bcd9e35adaac9be092bb84b74b44a75bbf042228ffb4ebaf5cec81ecfc2b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:34:10.073438Z","signature_b64":"2TACdVz7I20ggvCvPRhl7eAwTV5EEYzApICB/CFUrqSP86m4xWO4bVxUMgBOgRfFdyejlfKAUw9QMql0bskMAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"73bc9b6b73434488477eaeaa7df6a87efb2dfec9f5c9052047b0e1e13e493d80","last_reissued_at":"2026-07-05T09:34:10.072500Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:34:10.072500Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Precision-Machine Learning for the Matrix Element Method","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"hep-ph","authors_text":"Anja Butter, Nathan Huetsch, Ramon Winterhalder, Theo Heimel, Tilman Plehn","submitted_at":"2023-10-11T18:00:00Z","abstract_excerpt":"The matrix element method is the LHC inference method of choice for limited statistics. We present a dedicated machine learning framework, based on efficient phase-space integration, a learned acceptance and transfer function. It is based on a choice of INN and diffusion networks, and a transformer to solve jet combinatorics. We showcase this setup for the CP-phase of the top Yukawa coupling in associated Higgs and single-top production."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.07752","kind":"arxiv","version":3},"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/2310.07752/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":"2310.07752","created_at":"2026-07-05T09:34:10.072939+00:00"},{"alias_kind":"arxiv_version","alias_value":"2310.07752v3","created_at":"2026-07-05T09:34:10.072939+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.07752","created_at":"2026-07-05T09:34:10.072939+00:00"},{"alias_kind":"pith_short_12","alias_value":"OO6JW23TINCI","created_at":"2026-07-05T09:34:10.072939+00:00"},{"alias_kind":"pith_short_16","alias_value":"OO6JW23TINCIQR36","created_at":"2026-07-05T09:34:10.072939+00:00"},{"alias_kind":"pith_short_8","alias_value":"OO6JW23T","created_at":"2026-07-05T09:34:10.072939+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2606.11083","citing_title":"Matrix element method at NLO: A fine proof of concept in POWHEG","ref_index":53,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/OO6JW23TINCIQR36V2VH35VIP3","json":"https://pith.science/pith/OO6JW23TINCIQR36V2VH35VIP3.json","graph_json":"https://pith.science/api/pith-number/OO6JW23TINCIQR36V2VH35VIP3/graph.json","events_json":"https://pith.science/api/pith-number/OO6JW23TINCIQR36V2VH35VIP3/events.json","paper":"https://pith.science/paper/OO6JW23T"},"agent_actions":{"view_html":"https://pith.science/pith/OO6JW23TINCIQR36V2VH35VIP3","download_json":"https://pith.science/pith/OO6JW23TINCIQR36V2VH35VIP3.json","view_paper":"https://pith.science/paper/OO6JW23T","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2310.07752&json=true","fetch_graph":"https://pith.science/api/pith-number/OO6JW23TINCIQR36V2VH35VIP3/graph.json","fetch_events":"https://pith.science/api/pith-number/OO6JW23TINCIQR36V2VH35VIP3/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/OO6JW23TINCIQR36V2VH35VIP3/action/timestamp_anchor","attest_storage":"https://pith.science/pith/OO6JW23TINCIQR36V2VH35VIP3/action/storage_attestation","attest_author":"https://pith.science/pith/OO6JW23TINCIQR36V2VH35VIP3/action/author_attestation","sign_citation":"https://pith.science/pith/OO6JW23TINCIQR36V2VH35VIP3/action/citation_signature","submit_replication":"https://pith.science/pith/OO6JW23TINCIQR36V2VH35VIP3/action/replication_record"}},"created_at":"2026-07-05T09:34:10.072939+00:00","updated_at":"2026-07-05T09:34:10.072939+00:00"}