{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2008:DY7ZAVUFY4ASGTEUKAZPAXJDAR","short_pith_number":"pith:DY7ZAVUF","schema_version":"1.0","canonical_sha256":"1e3f905685c701234c945032f05d23047878b253ae81ef6a73b7e7c51c8f3c49","source":{"kind":"arxiv","id":"0812.4854","version":1},"attestation_state":"computed","paper":{"title":"Monte Carlo Determination of Multiple Extremal Eigenpairs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cond-mat.stat-mech"],"primary_cat":"physics.comp-ph","authors_text":"J. E. Gubernatis, T. E. Booth","submitted_at":"2008-12-28T21:42:36Z","abstract_excerpt":"We present a Monte Carlo algorithm that allows the simultaneous determination of a few extremal eigenpairs of a very large matrix without the need to compute the inner product of two vectors or store all the components of any one vector. The new algorithm, a Monte Carlo implementation of a deterministic one we recently benchmarked, is an extension of the power method. In the implementation presented, we used a basic Monte Carlo splitting and termination method called the comb, incorporated the weight cancellation method of Arnow {\\it et al.}, and exploited a new sampling method, the sewing met"},"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":"0812.4854","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"physics.comp-ph","submitted_at":"2008-12-28T21:42:36Z","cross_cats_sorted":["cond-mat.stat-mech"],"title_canon_sha256":"bf88c76ad48431ea3ddc94c29aa1869eb2902d6616afd96c4ca61560addc6bd7","abstract_canon_sha256":"d1b892f58daf8e16381c07dd861e97fa8e17a4e3274125c30755cdfa7ec74996"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:15:03.749093Z","signature_b64":"vLtLhF2jEfwXE+K6+N+S9dLOQPnztPO9+bOg2xX3hFJTizPryqLMYhbNHSpyJgqGcmKJbp8gh86lNwvxEcTZCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1e3f905685c701234c945032f05d23047878b253ae81ef6a73b7e7c51c8f3c49","last_reissued_at":"2026-05-18T02:15:03.748742Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:15:03.748742Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Monte Carlo Determination of Multiple Extremal Eigenpairs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cond-mat.stat-mech"],"primary_cat":"physics.comp-ph","authors_text":"J. E. Gubernatis, T. E. Booth","submitted_at":"2008-12-28T21:42:36Z","abstract_excerpt":"We present a Monte Carlo algorithm that allows the simultaneous determination of a few extremal eigenpairs of a very large matrix without the need to compute the inner product of two vectors or store all the components of any one vector. The new algorithm, a Monte Carlo implementation of a deterministic one we recently benchmarked, is an extension of the power method. In the implementation presented, we used a basic Monte Carlo splitting and termination method called the comb, incorporated the weight cancellation method of Arnow {\\it et al.}, and exploited a new sampling method, the sewing met"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"0812.4854","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":""},"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":"0812.4854","created_at":"2026-05-18T02:15:03.748791+00:00"},{"alias_kind":"arxiv_version","alias_value":"0812.4854v1","created_at":"2026-05-18T02:15:03.748791+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.0812.4854","created_at":"2026-05-18T02:15:03.748791+00:00"},{"alias_kind":"pith_short_12","alias_value":"DY7ZAVUFY4AS","created_at":"2026-05-18T12:25:57.157939+00:00"},{"alias_kind":"pith_short_16","alias_value":"DY7ZAVUFY4ASGTEU","created_at":"2026-05-18T12:25:57.157939+00:00"},{"alias_kind":"pith_short_8","alias_value":"DY7ZAVUF","created_at":"2026-05-18T12:25:57.157939+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/DY7ZAVUFY4ASGTEUKAZPAXJDAR","json":"https://pith.science/pith/DY7ZAVUFY4ASGTEUKAZPAXJDAR.json","graph_json":"https://pith.science/api/pith-number/DY7ZAVUFY4ASGTEUKAZPAXJDAR/graph.json","events_json":"https://pith.science/api/pith-number/DY7ZAVUFY4ASGTEUKAZPAXJDAR/events.json","paper":"https://pith.science/paper/DY7ZAVUF"},"agent_actions":{"view_html":"https://pith.science/pith/DY7ZAVUFY4ASGTEUKAZPAXJDAR","download_json":"https://pith.science/pith/DY7ZAVUFY4ASGTEUKAZPAXJDAR.json","view_paper":"https://pith.science/paper/DY7ZAVUF","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=0812.4854&json=true","fetch_graph":"https://pith.science/api/pith-number/DY7ZAVUFY4ASGTEUKAZPAXJDAR/graph.json","fetch_events":"https://pith.science/api/pith-number/DY7ZAVUFY4ASGTEUKAZPAXJDAR/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/DY7ZAVUFY4ASGTEUKAZPAXJDAR/action/timestamp_anchor","attest_storage":"https://pith.science/pith/DY7ZAVUFY4ASGTEUKAZPAXJDAR/action/storage_attestation","attest_author":"https://pith.science/pith/DY7ZAVUFY4ASGTEUKAZPAXJDAR/action/author_attestation","sign_citation":"https://pith.science/pith/DY7ZAVUFY4ASGTEUKAZPAXJDAR/action/citation_signature","submit_replication":"https://pith.science/pith/DY7ZAVUFY4ASGTEUKAZPAXJDAR/action/replication_record"}},"created_at":"2026-05-18T02:15:03.748791+00:00","updated_at":"2026-05-18T02:15:03.748791+00:00"}