{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:QOEHX3Z5G2VJRWZLELRADHED7V","short_pith_number":"pith:QOEHX3Z5","schema_version":"1.0","canonical_sha256":"83887bef3d36aa98db2b22e2019c83fd59964050c293612593a9db86f68c6723","source":{"kind":"arxiv","id":"2209.12788","version":2},"attestation_state":"computed","paper":{"title":"Application of Quantum Machine Learning in a Higgs Physics Study at the CEPC","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["quant-ph"],"primary_cat":"hep-ex","authors_text":"Abdualazem Fadol, Chen Zhou, Qiyu Sha, Sitian Qian, Yaquan Fang, Yuyang Xiao, Yu Zhang, Zhan Li","submitted_at":"2022-09-26T15:46:30Z","abstract_excerpt":"Machine learning has blossomed in recent decades and has become essential in many fields. It significantly solved some problems in particle physics -- particle reconstruction, event classification, etc. However, it is now time to break the limitation of conventional machine learning with quantum computing. A support-vector machine algorithm with a quantum kernel estimator (QSVM-Kernel) leverages high-dimensional quantum state space to identify a signal from backgrounds. In this study, we have pioneered employing this quantum machine learning algorithm to study the $e^{+}e^{-} \\rightarrow ZH$ p"},"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":"2209.12788","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"hep-ex","submitted_at":"2022-09-26T15:46:30Z","cross_cats_sorted":["quant-ph"],"title_canon_sha256":"de336d07dbbec9337ad4c2f08a0562eb5ea81bda1d4ad3e3a092ced836c9cb39","abstract_canon_sha256":"a0fba3e8a8b3b9ff2b5086835b6d3b0d65cbf435fd8a9ae55d80076786a4c1ce"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:54:47.417916Z","signature_b64":"ewF9vo18CA8YnsX3q9jatjd/vXCVxHLPgTpSifPuRF1y8J0EehYUSXceHc8mt6wVR3TMEXOHI8OLHKJCFBi+CQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"83887bef3d36aa98db2b22e2019c83fd59964050c293612593a9db86f68c6723","last_reissued_at":"2026-07-05T07:54:47.417377Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:54:47.417377Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Application of Quantum Machine Learning in a Higgs Physics Study at the CEPC","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["quant-ph"],"primary_cat":"hep-ex","authors_text":"Abdualazem Fadol, Chen Zhou, Qiyu Sha, Sitian Qian, Yaquan Fang, Yuyang Xiao, Yu Zhang, Zhan Li","submitted_at":"2022-09-26T15:46:30Z","abstract_excerpt":"Machine learning has blossomed in recent decades and has become essential in many fields. It significantly solved some problems in particle physics -- particle reconstruction, event classification, etc. However, it is now time to break the limitation of conventional machine learning with quantum computing. A support-vector machine algorithm with a quantum kernel estimator (QSVM-Kernel) leverages high-dimensional quantum state space to identify a signal from backgrounds. In this study, we have pioneered employing this quantum machine learning algorithm to study the $e^{+}e^{-} \\rightarrow ZH$ p"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2209.12788","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/2209.12788/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":"2209.12788","created_at":"2026-07-05T07:54:47.417435+00:00"},{"alias_kind":"arxiv_version","alias_value":"2209.12788v2","created_at":"2026-07-05T07:54:47.417435+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2209.12788","created_at":"2026-07-05T07:54:47.417435+00:00"},{"alias_kind":"pith_short_12","alias_value":"QOEHX3Z5G2VJ","created_at":"2026-07-05T07:54:47.417435+00:00"},{"alias_kind":"pith_short_16","alias_value":"QOEHX3Z5G2VJRWZL","created_at":"2026-07-05T07:54:47.417435+00:00"},{"alias_kind":"pith_short_8","alias_value":"QOEHX3Z5","created_at":"2026-07-05T07:54:47.417435+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/QOEHX3Z5G2VJRWZLELRADHED7V","json":"https://pith.science/pith/QOEHX3Z5G2VJRWZLELRADHED7V.json","graph_json":"https://pith.science/api/pith-number/QOEHX3Z5G2VJRWZLELRADHED7V/graph.json","events_json":"https://pith.science/api/pith-number/QOEHX3Z5G2VJRWZLELRADHED7V/events.json","paper":"https://pith.science/paper/QOEHX3Z5"},"agent_actions":{"view_html":"https://pith.science/pith/QOEHX3Z5G2VJRWZLELRADHED7V","download_json":"https://pith.science/pith/QOEHX3Z5G2VJRWZLELRADHED7V.json","view_paper":"https://pith.science/paper/QOEHX3Z5","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2209.12788&json=true","fetch_graph":"https://pith.science/api/pith-number/QOEHX3Z5G2VJRWZLELRADHED7V/graph.json","fetch_events":"https://pith.science/api/pith-number/QOEHX3Z5G2VJRWZLELRADHED7V/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/QOEHX3Z5G2VJRWZLELRADHED7V/action/timestamp_anchor","attest_storage":"https://pith.science/pith/QOEHX3Z5G2VJRWZLELRADHED7V/action/storage_attestation","attest_author":"https://pith.science/pith/QOEHX3Z5G2VJRWZLELRADHED7V/action/author_attestation","sign_citation":"https://pith.science/pith/QOEHX3Z5G2VJRWZLELRADHED7V/action/citation_signature","submit_replication":"https://pith.science/pith/QOEHX3Z5G2VJRWZLELRADHED7V/action/replication_record"}},"created_at":"2026-07-05T07:54:47.417435+00:00","updated_at":"2026-07-05T07:54:47.417435+00:00"}