{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:CZPTSUPGWHCWIZ2DTQ5GNHO3Q4","short_pith_number":"pith:CZPTSUPG","schema_version":"1.0","canonical_sha256":"165f3951e6b1c56467439c3a669ddb8721b0fc87497be100c2dc635c7aaa3208","source":{"kind":"arxiv","id":"2608.05314","version":1},"attestation_state":"computed","paper":{"title":"Machine learning for sample-based quantum diagonalization: generative configuration recovery and the classical-simulability frontier","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["physics.chem-ph"],"primary_cat":"quant-ph","authors_text":"Daita AI), Nicol\\'as Bonilla Vargas (Universidad Nacional de Colombia, SRH University M\\\"unchen","submitted_at":"2026-08-05T18:15:19Z","abstract_excerpt":"Sample-based quantum diagonalization (SQD), equivalently quantum-selected configuration interaction (QSCI), has in two years become a pragmatic centre of gravity of pre-fault-tolerant quantum chemistry: a quantum processor samples electronic configurations, and the many-electron Hamiltonian is diagonalized classically in the resulting determinant subspace. Its accuracy is set entirely by which configurations enter that subspace, a selection problem for machine learning made acute by a coupon-collector bottleneck. We critically review the ecosystem of generative and learned selectors, organizin"},"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":"2608.05314","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"quant-ph","submitted_at":"2026-08-05T18:15:19Z","cross_cats_sorted":["physics.chem-ph"],"title_canon_sha256":"bedbd884e6305dd58881712d2993ea5108085ba8269b67a82c80cca440846df5","abstract_canon_sha256":"1c841e5b7700cc9cb28f2564e2c8880109933c9eb59ffd2902cd2dc0e74e5419"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-08-07T00:46:59.418503Z","signature_b64":"4f9gZMB8ZnHEpT7x7Lo/s3Iv4p/CakbsED2VCv+/y/eoFz6ykzWIvMIHwUtTDOXXZ5bPK49XQwfA4uKKvFjnDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"165f3951e6b1c56467439c3a669ddb8721b0fc87497be100c2dc635c7aaa3208","last_reissued_at":"2026-08-07T00:46:59.417031Z","signature_status":"signed_v1","first_computed_at":"2026-08-07T00:46:59.417031Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Machine learning for sample-based quantum diagonalization: generative configuration recovery and the classical-simulability frontier","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["physics.chem-ph"],"primary_cat":"quant-ph","authors_text":"Daita AI), Nicol\\'as Bonilla Vargas (Universidad Nacional de Colombia, SRH University M\\\"unchen","submitted_at":"2026-08-05T18:15:19Z","abstract_excerpt":"Sample-based quantum diagonalization (SQD), equivalently quantum-selected configuration interaction (QSCI), has in two years become a pragmatic centre of gravity of pre-fault-tolerant quantum chemistry: a quantum processor samples electronic configurations, and the many-electron Hamiltonian is diagonalized classically in the resulting determinant subspace. Its accuracy is set entirely by which configurations enter that subspace, a selection problem for machine learning made acute by a coupon-collector bottleneck. We critically review the ecosystem of generative and learned selectors, organizin"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.05314","kind":"arxiv","version":1},"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/2608.05314/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":"2608.05314","created_at":"2026-08-07T00:46:59.418357+00:00"},{"alias_kind":"arxiv_version","alias_value":"2608.05314v1","created_at":"2026-08-07T00:46:59.418357+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.05314","created_at":"2026-08-07T00:46:59.418357+00:00"},{"alias_kind":"pith_short_12","alias_value":"CZPTSUPGWHCW","created_at":"2026-08-07T00:46:59.418357+00:00"},{"alias_kind":"pith_short_16","alias_value":"CZPTSUPGWHCWIZ2D","created_at":"2026-08-07T00:46:59.418357+00:00"},{"alias_kind":"pith_short_8","alias_value":"CZPTSUPG","created_at":"2026-08-07T00:46:59.418357+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/CZPTSUPGWHCWIZ2DTQ5GNHO3Q4","json":"https://pith.science/pith/CZPTSUPGWHCWIZ2DTQ5GNHO3Q4.json","graph_json":"https://pith.science/api/pith-number/CZPTSUPGWHCWIZ2DTQ5GNHO3Q4/graph.json","events_json":"https://pith.science/api/pith-number/CZPTSUPGWHCWIZ2DTQ5GNHO3Q4/events.json","paper":"https://pith.science/paper/CZPTSUPG"},"agent_actions":{"view_html":"https://pith.science/pith/CZPTSUPGWHCWIZ2DTQ5GNHO3Q4","download_json":"https://pith.science/pith/CZPTSUPGWHCWIZ2DTQ5GNHO3Q4.json","view_paper":"https://pith.science/paper/CZPTSUPG","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2608.05314&json=true","fetch_graph":"https://pith.science/api/pith-number/CZPTSUPGWHCWIZ2DTQ5GNHO3Q4/graph.json","fetch_events":"https://pith.science/api/pith-number/CZPTSUPGWHCWIZ2DTQ5GNHO3Q4/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/CZPTSUPGWHCWIZ2DTQ5GNHO3Q4/action/timestamp_anchor","attest_storage":"https://pith.science/pith/CZPTSUPGWHCWIZ2DTQ5GNHO3Q4/action/storage_attestation","attest_author":"https://pith.science/pith/CZPTSUPGWHCWIZ2DTQ5GNHO3Q4/action/author_attestation","sign_citation":"https://pith.science/pith/CZPTSUPGWHCWIZ2DTQ5GNHO3Q4/action/citation_signature","submit_replication":"https://pith.science/pith/CZPTSUPGWHCWIZ2DTQ5GNHO3Q4/action/replication_record"}},"created_at":"2026-08-07T00:46:59.418357+00:00","updated_at":"2026-08-07T00:46:59.418357+00:00"}