{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:2CWJ5BU4G6PHC3GU3SG46LAK26","short_pith_number":"pith:2CWJ5BU4","schema_version":"1.0","canonical_sha256":"d0ac9e869c379e716cd4dc8dcf2c0ad7ae02858fd034a59b44ab53b02750e088","source":{"kind":"arxiv","id":"1703.00998","version":1},"attestation_state":"computed","paper":{"title":"randUTV: A blocked randomized algorithm for computing a rank-revealing UTV factorization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.NA","authors_text":"Gregorio Quintana-Orti, Nathan Heavner, Per-Gunnar Martinsson","submitted_at":"2017-03-03T00:20:37Z","abstract_excerpt":"This manuscript describes the randomized algorithm randUTV for computing a so called UTV factorization efficiently. Given a matrix $A$, the algorithm computes a factorization $A = UTV^{*}$, where $U$ and $V$ have orthonormal columns, and $T$ is triangular (either upper or lower, whichever is preferred). The algorithm randUTV is developed primarily to be a fast and easily parallelized alternative to algorithms for computing the Singular Value Decomposition (SVD). randUTV provides accuracy very close to that of the SVD for problems such as low-rank approximation, solving ill-conditioned linear s"},"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":"1703.00998","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.NA","submitted_at":"2017-03-03T00:20:37Z","cross_cats_sorted":[],"title_canon_sha256":"bd7e242e5ef57f2cf70e11cff03e9eaebc456505a6f07e736270969fc11f87f0","abstract_canon_sha256":"0f6189b2e05bfff9ec317887f88f7b59117aa000eb03941db178a3118a6f8bc3"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:49:37.284100Z","signature_b64":"n/futhYaJOXZG58TNjKN4u2kTmOtkZ5g8mCGXeRVGMrR7WT45Cc/t8MBRZoCvkDmmcHVKFzFgzqIXo+sCOMMBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d0ac9e869c379e716cd4dc8dcf2c0ad7ae02858fd034a59b44ab53b02750e088","last_reissued_at":"2026-05-18T00:49:37.283407Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:49:37.283407Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"randUTV: A blocked randomized algorithm for computing a rank-revealing UTV factorization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.NA","authors_text":"Gregorio Quintana-Orti, Nathan Heavner, Per-Gunnar Martinsson","submitted_at":"2017-03-03T00:20:37Z","abstract_excerpt":"This manuscript describes the randomized algorithm randUTV for computing a so called UTV factorization efficiently. Given a matrix $A$, the algorithm computes a factorization $A = UTV^{*}$, where $U$ and $V$ have orthonormal columns, and $T$ is triangular (either upper or lower, whichever is preferred). The algorithm randUTV is developed primarily to be a fast and easily parallelized alternative to algorithms for computing the Singular Value Decomposition (SVD). randUTV provides accuracy very close to that of the SVD for problems such as low-rank approximation, solving ill-conditioned linear s"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1703.00998","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":"1703.00998","created_at":"2026-05-18T00:49:37.283513+00:00"},{"alias_kind":"arxiv_version","alias_value":"1703.00998v1","created_at":"2026-05-18T00:49:37.283513+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1703.00998","created_at":"2026-05-18T00:49:37.283513+00:00"},{"alias_kind":"pith_short_12","alias_value":"2CWJ5BU4G6PH","created_at":"2026-05-18T12:30:55.937587+00:00"},{"alias_kind":"pith_short_16","alias_value":"2CWJ5BU4G6PHC3GU","created_at":"2026-05-18T12:30:55.937587+00:00"},{"alias_kind":"pith_short_8","alias_value":"2CWJ5BU4","created_at":"2026-05-18T12:30:55.937587+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/2CWJ5BU4G6PHC3GU3SG46LAK26","json":"https://pith.science/pith/2CWJ5BU4G6PHC3GU3SG46LAK26.json","graph_json":"https://pith.science/api/pith-number/2CWJ5BU4G6PHC3GU3SG46LAK26/graph.json","events_json":"https://pith.science/api/pith-number/2CWJ5BU4G6PHC3GU3SG46LAK26/events.json","paper":"https://pith.science/paper/2CWJ5BU4"},"agent_actions":{"view_html":"https://pith.science/pith/2CWJ5BU4G6PHC3GU3SG46LAK26","download_json":"https://pith.science/pith/2CWJ5BU4G6PHC3GU3SG46LAK26.json","view_paper":"https://pith.science/paper/2CWJ5BU4","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1703.00998&json=true","fetch_graph":"https://pith.science/api/pith-number/2CWJ5BU4G6PHC3GU3SG46LAK26/graph.json","fetch_events":"https://pith.science/api/pith-number/2CWJ5BU4G6PHC3GU3SG46LAK26/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/2CWJ5BU4G6PHC3GU3SG46LAK26/action/timestamp_anchor","attest_storage":"https://pith.science/pith/2CWJ5BU4G6PHC3GU3SG46LAK26/action/storage_attestation","attest_author":"https://pith.science/pith/2CWJ5BU4G6PHC3GU3SG46LAK26/action/author_attestation","sign_citation":"https://pith.science/pith/2CWJ5BU4G6PHC3GU3SG46LAK26/action/citation_signature","submit_replication":"https://pith.science/pith/2CWJ5BU4G6PHC3GU3SG46LAK26/action/replication_record"}},"created_at":"2026-05-18T00:49:37.283513+00:00","updated_at":"2026-05-18T00:49:37.283513+00:00"}