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Comput. , 28:2095–2113, 2006","work_id":"26501470-5204-4a61-a052-8495a0ab879f","year":2095}],"snapshot_sha256":"185a66535059ed3b1f08691052dcbe38180efe8fc02b24a75b0c193f1f2672cf"},"source":{"id":"2605.17664","kind":"arxiv","version":1},"verdict":{"created_at":"2026-05-19T22:19:47.101946Z","id":"00ef584e-95c2-4481-b875-e42f2cd427f0","model_set":{"reader":"grok-4.3"},"one_line_summary":"The paper introduces AAg, a nonlinear-residual variant of Anderson acceleration, proves sharp linear convergence rates for arbitrary depth on Picard iterations for Navier-Stokes, and proposes an adaptive depth strategy validated by numerical tests.","pipeline_version":"pith-pipeline@v0.9.0","pith_extraction_headline":"Modified Anderson acceleration using nonlinear residuals gives sharp linear convergence predictions for Navier-Stokes Picard iterations.","strongest_claim":"We establish a convergence analysis for this method with any depth that shows how AAg accelerates convergence through the gain of the optimization problem, and obtain a sharp prediction of its linear convergence rate (a feature that is not part of the known theory for classical Anderson acceleration).","weakest_assumption":"The convergence analysis assumes that the nonlinear residual is used to define the least-squares problem in AAg and that the gain of this optimization problem directly controls the contraction factor; this premise is inherited from the prior work on AAg and is not re-derived from first principles for the Navier-Stokes setting."}},"verdict_id":"00ef584e-95c2-4481-b875-e42f2cd427f0"}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:7b1c2270ad098a184b425ac5ded5e3680657b91f400d4e50f17f303a66553c4c","target":"record","created_at":"2026-05-20T00:04:51Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"53e5ff034f433036672d6ef546db80b4adfb35b7dbdb398d65dec40503f93919","cross_cats_sorted":["cs.NA"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.NA","submitted_at":"2026-05-17T21:49:19Z","title_canon_sha256":"7dffdd3152a98e5faee26ecc7fb3b1485eb76480f44a982fc0966481e074b250"},"schema_version":"1.0","source":{"id":"2605.17664","kind":"arxiv","version":1}},"canonical_sha256":"e256aa08d59acae625084d1ba9e88dd295157d0575795ddb9bfc5821beed4616","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e256aa08d59acae625084d1ba9e88dd295157d0575795ddb9bfc5821beed4616","first_computed_at":"2026-05-20T00:04:51.591997Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-20T00:04:51.591997Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"9bneZlmMRg7tfreEIre0x+1UEocLRnY5jAxy1yHliJrre6OInjE4Yg2T2Bp2WEnqMPPQUX2SoqeJnGG7QcQZDw==","signature_status":"signed_v1","signed_at":"2026-05-20T00:04:51.592893Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.17664","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7b1c2270ad098a184b425ac5ded5e3680657b91f400d4e50f17f303a66553c4c","sha256:925ce4e949d9cabb0ba43ffe529f474fde85739e98f90aeb6242a1ed44a5ebf6"],"state_sha256":"38f759064fcfbe262eb519162b6ba93cb365abde37d0c2a80142b1b2a16603bc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BE8219Kc335yJgVXe14Crwi4EYvSnNULUXh38yaIWO6EzXo6FU3YburmrsXYOH3fOHxC4tw5kLrIKqway0Q8Bg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-22T23:59:30.688437Z","bundle_sha256":"5fa414eea8952e24aa2c773029a1392601a43c36c78fc4ec05d74a29b029c242"}}