{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:IALRLQQ7DNGAXTBFIFUEQ3KYGA","short_pith_number":"pith:IALRLQQ7","schema_version":"1.0","canonical_sha256":"401715c21f1b4c0bcc254168486d5830320687f33d3052a4593a6095417ec8cb","source":{"kind":"arxiv","id":"1612.00337","version":2},"attestation_state":"computed","paper":{"title":"The AAA algorithm for rational approximation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.NA"],"primary_cat":"math.NA","authors_text":"Lloyd N. Trefethen, Olivier S\\`ete, Yuji Nakatsukasa","submitted_at":"2016-12-01T16:27:19Z","abstract_excerpt":"We introduce a new algorithm for approximation by rational functions on a real or complex set of points, implementable in 40 lines of Matlab and requiring no user input parameters. Even on a disk or interval the algorithm may outperform existing methods, and on more complicated domains it is especially competitive. The core ideas are (1) representation of the rational approximant in barycentric form with interpolation at certain support points and (2) greedy selection of the support points to avoid exponential instabilities. The name AAA stands for \"adaptive Antoulas--Anderson\" in honor of the"},"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":"1612.00337","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.NA","submitted_at":"2016-12-01T16:27:19Z","cross_cats_sorted":["cs.NA"],"title_canon_sha256":"0c57c5c605e44d5b556dfff568128aa32a1e1141dd4b9340e6d8e4710133778a","abstract_canon_sha256":"d408193ae701cc82d9fbab435edbd62d2416a3c91b36f7223479a7f69b09be6a"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-04T18:10:18.602780Z","signature_b64":"u6SWy+7ZfhoaE/CAb/AoyzfA1TY8W6xPw47+M1q42JQY3UkJ2S+GXabG/XgHClLnVezJikpip9U6Q5LjxO4OCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"401715c21f1b4c0bcc254168486d5830320687f33d3052a4593a6095417ec8cb","last_reissued_at":"2026-06-04T18:10:18.602282Z","signature_status":"signed_v1","first_computed_at":"2026-06-04T18:10:18.602282Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"The AAA algorithm for rational approximation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.NA"],"primary_cat":"math.NA","authors_text":"Lloyd N. Trefethen, Olivier S\\`ete, Yuji Nakatsukasa","submitted_at":"2016-12-01T16:27:19Z","abstract_excerpt":"We introduce a new algorithm for approximation by rational functions on a real or complex set of points, implementable in 40 lines of Matlab and requiring no user input parameters. Even on a disk or interval the algorithm may outperform existing methods, and on more complicated domains it is especially competitive. The core ideas are (1) representation of the rational approximant in barycentric form with interpolation at certain support points and (2) greedy selection of the support points to avoid exponential instabilities. The name AAA stands for \"adaptive Antoulas--Anderson\" in honor of the"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1612.00337","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/1612.00337/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":"1612.00337","created_at":"2026-06-04T18:10:18.602353+00:00"},{"alias_kind":"arxiv_version","alias_value":"1612.00337v2","created_at":"2026-06-04T18:10:18.602353+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1612.00337","created_at":"2026-06-04T18:10:18.602353+00:00"},{"alias_kind":"pith_short_12","alias_value":"IALRLQQ7DNGA","created_at":"2026-06-04T18:10:18.602353+00:00"},{"alias_kind":"pith_short_16","alias_value":"IALRLQQ7DNGAXTBF","created_at":"2026-06-04T18:10:18.602353+00:00"},{"alias_kind":"pith_short_8","alias_value":"IALRLQQ7","created_at":"2026-06-04T18:10:18.602353+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/IALRLQQ7DNGAXTBFIFUEQ3KYGA","json":"https://pith.science/pith/IALRLQQ7DNGAXTBFIFUEQ3KYGA.json","graph_json":"https://pith.science/api/pith-number/IALRLQQ7DNGAXTBFIFUEQ3KYGA/graph.json","events_json":"https://pith.science/api/pith-number/IALRLQQ7DNGAXTBFIFUEQ3KYGA/events.json","paper":"https://pith.science/paper/IALRLQQ7"},"agent_actions":{"view_html":"https://pith.science/pith/IALRLQQ7DNGAXTBFIFUEQ3KYGA","download_json":"https://pith.science/pith/IALRLQQ7DNGAXTBFIFUEQ3KYGA.json","view_paper":"https://pith.science/paper/IALRLQQ7","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1612.00337&json=true","fetch_graph":"https://pith.science/api/pith-number/IALRLQQ7DNGAXTBFIFUEQ3KYGA/graph.json","fetch_events":"https://pith.science/api/pith-number/IALRLQQ7DNGAXTBFIFUEQ3KYGA/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/IALRLQQ7DNGAXTBFIFUEQ3KYGA/action/timestamp_anchor","attest_storage":"https://pith.science/pith/IALRLQQ7DNGAXTBFIFUEQ3KYGA/action/storage_attestation","attest_author":"https://pith.science/pith/IALRLQQ7DNGAXTBFIFUEQ3KYGA/action/author_attestation","sign_citation":"https://pith.science/pith/IALRLQQ7DNGAXTBFIFUEQ3KYGA/action/citation_signature","submit_replication":"https://pith.science/pith/IALRLQQ7DNGAXTBFIFUEQ3KYGA/action/replication_record"}},"created_at":"2026-06-04T18:10:18.602353+00:00","updated_at":"2026-06-04T18:10:18.602353+00:00"}