{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:QRUDABKUKDEWRDO5XMIK4FQNQ2","short_pith_number":"pith:QRUDABKU","schema_version":"1.0","canonical_sha256":"846830055450c9688dddbb10ae160d86ac038b4cb4638e25d860d6f9c163fcbe","source":{"kind":"arxiv","id":"2311.11751","version":2},"attestation_state":"computed","paper":{"title":"Quantum approximated cloning-assisted density matrix exponentiation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"quant-ph","authors_text":"Javier Gonzalez-Conde, Mikel Sanz, Pablo Rodriguez-Grasa, Patrick Rebentrost, Ruben Ibarrondo, Yue Ban","submitted_at":"2023-11-20T13:27:00Z","abstract_excerpt":"Classical information loading is an essential task for many processing quantum algorithms, constituting a cornerstone in the field of quantum machine learning. In particular, the embedding techniques based on Hamiltonian simulation techniques enable the loading of matrices into quantum computers. A representative example of these methods is the Lloyd-Mohseni-Rebentrost protocol, which efficiently implements matrix exponentiation when multiple copies of a quantum state are available. However, this is a quite ideal set up, and in a realistic scenario, the copies are limited and the non-cloning t"},"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":"2311.11751","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"quant-ph","submitted_at":"2023-11-20T13:27:00Z","cross_cats_sorted":[],"title_canon_sha256":"fddc8e03158f3acbd817b84616ff1ba1b234805e8a087c99213dbc0c526819d8","abstract_canon_sha256":"57dcafe67fcce9c12acdc9dbcafa0247ac1da18632ccc86c1239c1fe6eb4d500"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:39:59.168508Z","signature_b64":"POmoGuwoZAmOI+MC2LJCrApl/mIHnfD3AxFP19G2n9X1OotKhzhOq8JcVkNpGvIIkGZbHsNE39VDtcE3SxGNDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"846830055450c9688dddbb10ae160d86ac038b4cb4638e25d860d6f9c163fcbe","last_reissued_at":"2026-07-05T10:39:59.168018Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:39:59.168018Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Quantum approximated cloning-assisted density matrix exponentiation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"quant-ph","authors_text":"Javier Gonzalez-Conde, Mikel Sanz, Pablo Rodriguez-Grasa, Patrick Rebentrost, Ruben Ibarrondo, Yue Ban","submitted_at":"2023-11-20T13:27:00Z","abstract_excerpt":"Classical information loading is an essential task for many processing quantum algorithms, constituting a cornerstone in the field of quantum machine learning. In particular, the embedding techniques based on Hamiltonian simulation techniques enable the loading of matrices into quantum computers. A representative example of these methods is the Lloyd-Mohseni-Rebentrost protocol, which efficiently implements matrix exponentiation when multiple copies of a quantum state are available. However, this is a quite ideal set up, and in a realistic scenario, the copies are limited and the non-cloning t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.11751","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/2311.11751/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":"2311.11751","created_at":"2026-07-05T10:39:59.168070+00:00"},{"alias_kind":"arxiv_version","alias_value":"2311.11751v2","created_at":"2026-07-05T10:39:59.168070+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.11751","created_at":"2026-07-05T10:39:59.168070+00:00"},{"alias_kind":"pith_short_12","alias_value":"QRUDABKUKDEW","created_at":"2026-07-05T10:39:59.168070+00:00"},{"alias_kind":"pith_short_16","alias_value":"QRUDABKUKDEWRDO5","created_at":"2026-07-05T10:39:59.168070+00:00"},{"alias_kind":"pith_short_8","alias_value":"QRUDABKU","created_at":"2026-07-05T10:39:59.168070+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/QRUDABKUKDEWRDO5XMIK4FQNQ2","json":"https://pith.science/pith/QRUDABKUKDEWRDO5XMIK4FQNQ2.json","graph_json":"https://pith.science/api/pith-number/QRUDABKUKDEWRDO5XMIK4FQNQ2/graph.json","events_json":"https://pith.science/api/pith-number/QRUDABKUKDEWRDO5XMIK4FQNQ2/events.json","paper":"https://pith.science/paper/QRUDABKU"},"agent_actions":{"view_html":"https://pith.science/pith/QRUDABKUKDEWRDO5XMIK4FQNQ2","download_json":"https://pith.science/pith/QRUDABKUKDEWRDO5XMIK4FQNQ2.json","view_paper":"https://pith.science/paper/QRUDABKU","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2311.11751&json=true","fetch_graph":"https://pith.science/api/pith-number/QRUDABKUKDEWRDO5XMIK4FQNQ2/graph.json","fetch_events":"https://pith.science/api/pith-number/QRUDABKUKDEWRDO5XMIK4FQNQ2/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/QRUDABKUKDEWRDO5XMIK4FQNQ2/action/timestamp_anchor","attest_storage":"https://pith.science/pith/QRUDABKUKDEWRDO5XMIK4FQNQ2/action/storage_attestation","attest_author":"https://pith.science/pith/QRUDABKUKDEWRDO5XMIK4FQNQ2/action/author_attestation","sign_citation":"https://pith.science/pith/QRUDABKUKDEWRDO5XMIK4FQNQ2/action/citation_signature","submit_replication":"https://pith.science/pith/QRUDABKUKDEWRDO5XMIK4FQNQ2/action/replication_record"}},"created_at":"2026-07-05T10:39:59.168070+00:00","updated_at":"2026-07-05T10:39:59.168070+00:00"}