{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:EFBOL6DCCWHJWLLIKS2AKUDLDY","short_pith_number":"pith:EFBOL6DC","schema_version":"1.0","canonical_sha256":"2142e5f862158e9b2d6854b405506b1e38483d145d6964192e5a6387ee186a21","source":{"kind":"arxiv","id":"1608.00677","version":4},"attestation_state":"computed","paper":{"title":"Hybrid Quantum-Classical Approach to Quantum Optimal Control","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"quant-ph","authors_text":"Chang-Pu Sun, Jun Li, Xiaodong Yang, Xinhua Peng","submitted_at":"2016-08-02T02:20:04Z","abstract_excerpt":"A central challenge in quantum computing is to identify more computational problems for which utilization of quantum resources can offer significant speedup. Here, we propose a hybrid quantum-classical scheme to tackle the quantum optimal control problem. We show that the most computationally demanding part of gradient-based algorithms, namely computing the fitness function and its gradient for a control input, can be accomplished by the process of evolution and measurement on a quantum simulator. By posing queries to and receiving messages from the quantum simulator, classical computing devic"},"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":"1608.00677","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"quant-ph","submitted_at":"2016-08-02T02:20:04Z","cross_cats_sorted":[],"title_canon_sha256":"723d8a11ffa1a62bccd2b050b5356ab35243de91b59fe573fa71b81942d77c6f","abstract_canon_sha256":"0760d8f40377bc86c4405d66b9894f552fa46a99353fb9635c01feacebd1e486"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:46:09.048751Z","signature_b64":"2UROdH+SkGhDx5PQ0hFmwGulmLZRl42l8ULLPvH91zDgboLclviMh1evQSsoX2N2oyjTGudWSMrtJwktgF08Dw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2142e5f862158e9b2d6854b405506b1e38483d145d6964192e5a6387ee186a21","last_reissued_at":"2026-05-18T00:46:09.048194Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:46:09.048194Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Hybrid Quantum-Classical Approach to Quantum Optimal Control","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"quant-ph","authors_text":"Chang-Pu Sun, Jun Li, Xiaodong Yang, Xinhua Peng","submitted_at":"2016-08-02T02:20:04Z","abstract_excerpt":"A central challenge in quantum computing is to identify more computational problems for which utilization of quantum resources can offer significant speedup. Here, we propose a hybrid quantum-classical scheme to tackle the quantum optimal control problem. We show that the most computationally demanding part of gradient-based algorithms, namely computing the fitness function and its gradient for a control input, can be accomplished by the process of evolution and measurement on a quantum simulator. By posing queries to and receiving messages from the quantum simulator, classical computing devic"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1608.00677","kind":"arxiv","version":4},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"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":"1608.00677","created_at":"2026-05-18T00:46:09.048272+00:00"},{"alias_kind":"arxiv_version","alias_value":"1608.00677v4","created_at":"2026-05-18T00:46:09.048272+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1608.00677","created_at":"2026-05-18T00:46:09.048272+00:00"},{"alias_kind":"pith_short_12","alias_value":"EFBOL6DCCWHJ","created_at":"2026-05-18T12:30:12.583610+00:00"},{"alias_kind":"pith_short_16","alias_value":"EFBOL6DCCWHJWLLI","created_at":"2026-05-18T12:30:12.583610+00:00"},{"alias_kind":"pith_short_8","alias_value":"EFBOL6DC","created_at":"2026-05-18T12:30:12.583610+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/EFBOL6DCCWHJWLLIKS2AKUDLDY","json":"https://pith.science/pith/EFBOL6DCCWHJWLLIKS2AKUDLDY.json","graph_json":"https://pith.science/api/pith-number/EFBOL6DCCWHJWLLIKS2AKUDLDY/graph.json","events_json":"https://pith.science/api/pith-number/EFBOL6DCCWHJWLLIKS2AKUDLDY/events.json","paper":"https://pith.science/paper/EFBOL6DC"},"agent_actions":{"view_html":"https://pith.science/pith/EFBOL6DCCWHJWLLIKS2AKUDLDY","download_json":"https://pith.science/pith/EFBOL6DCCWHJWLLIKS2AKUDLDY.json","view_paper":"https://pith.science/paper/EFBOL6DC","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1608.00677&json=true","fetch_graph":"https://pith.science/api/pith-number/EFBOL6DCCWHJWLLIKS2AKUDLDY/graph.json","fetch_events":"https://pith.science/api/pith-number/EFBOL6DCCWHJWLLIKS2AKUDLDY/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/EFBOL6DCCWHJWLLIKS2AKUDLDY/action/timestamp_anchor","attest_storage":"https://pith.science/pith/EFBOL6DCCWHJWLLIKS2AKUDLDY/action/storage_attestation","attest_author":"https://pith.science/pith/EFBOL6DCCWHJWLLIKS2AKUDLDY/action/author_attestation","sign_citation":"https://pith.science/pith/EFBOL6DCCWHJWLLIKS2AKUDLDY/action/citation_signature","submit_replication":"https://pith.science/pith/EFBOL6DCCWHJWLLIKS2AKUDLDY/action/replication_record"}},"created_at":"2026-05-18T00:46:09.048272+00:00","updated_at":"2026-05-18T00:46:09.048272+00:00"}