{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:6XPPXVXUO4EF3EPBOESWTFPL6O","short_pith_number":"pith:6XPPXVXU","schema_version":"1.0","canonical_sha256":"f5defbd6f477085d91e171256995ebf3aace88edd65539996eec0f8173038dbf","source":{"kind":"arxiv","id":"2608.05522","version":1},"attestation_state":"computed","paper":{"title":"Equation-Free Period-Aware Forecast-Error Contraction for Estimating Negative Largest Lyapunov Exponents from Short Trajectory Ensembles","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","physics.data-an"],"primary_cat":"nlin.CD","authors_text":"Andrei Velichko, N'Gbo N'Gbo, Viet-Thanh Pham","submitted_at":"2026-08-06T01:58:00Z","abstract_excerpt":"Estimating positive largest Lyapunov exponents from data is comparatively natural because neighboring trajectories separate, whereas stable dynamics require resolving contraction before measurement noise or finite precision erases the signal. We introduce a period-aware forecast-error contraction procedure for estimating a dominant negative Lyapunov exponent from ensembles of short scalar trajectories without using governing equations or an analytical Jacobian. A k-nearest-neighbor predictor is trained on trajectory histories, the geometric-mean absolute forecast error is evaluated at phase-co"},"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":"2608.05522","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"nlin.CD","submitted_at":"2026-08-06T01:58:00Z","cross_cats_sorted":["cs.LG","physics.data-an"],"title_canon_sha256":"6f633a311841867864d230749f60dfcf3ed7cce3fb7236911c64372dcc28b74a","abstract_canon_sha256":"ab156fb5232de42a600b6194795a4e5dc8285d29e26bb0396019f887a4a11d18"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-08-07T00:48:01.097330Z","signature_b64":"SahSIIRWKoZyN3HRTAO9/SY6Cd6nE+Qx28Ky6xlnh8B/AyIyTimlt9H0P0W8qVQVCm5MUeGUFYwMPmfdCqCIDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f5defbd6f477085d91e171256995ebf3aace88edd65539996eec0f8173038dbf","last_reissued_at":"2026-08-07T00:48:01.095860Z","signature_status":"signed_v1","first_computed_at":"2026-08-07T00:48:01.095860Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Equation-Free Period-Aware Forecast-Error Contraction for Estimating Negative Largest Lyapunov Exponents from Short Trajectory Ensembles","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","physics.data-an"],"primary_cat":"nlin.CD","authors_text":"Andrei Velichko, N'Gbo N'Gbo, Viet-Thanh Pham","submitted_at":"2026-08-06T01:58:00Z","abstract_excerpt":"Estimating positive largest Lyapunov exponents from data is comparatively natural because neighboring trajectories separate, whereas stable dynamics require resolving contraction before measurement noise or finite precision erases the signal. We introduce a period-aware forecast-error contraction procedure for estimating a dominant negative Lyapunov exponent from ensembles of short scalar trajectories without using governing equations or an analytical Jacobian. A k-nearest-neighbor predictor is trained on trajectory histories, the geometric-mean absolute forecast error is evaluated at phase-co"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.05522","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/2608.05522/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":"2608.05522","created_at":"2026-08-07T00:48:01.097212+00:00"},{"alias_kind":"arxiv_version","alias_value":"2608.05522v1","created_at":"2026-08-07T00:48:01.097212+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.05522","created_at":"2026-08-07T00:48:01.097212+00:00"},{"alias_kind":"pith_short_12","alias_value":"6XPPXVXUO4EF","created_at":"2026-08-07T00:48:01.097212+00:00"},{"alias_kind":"pith_short_16","alias_value":"6XPPXVXUO4EF3EPB","created_at":"2026-08-07T00:48:01.097212+00:00"},{"alias_kind":"pith_short_8","alias_value":"6XPPXVXU","created_at":"2026-08-07T00:48:01.097212+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/6XPPXVXUO4EF3EPBOESWTFPL6O","json":"https://pith.science/pith/6XPPXVXUO4EF3EPBOESWTFPL6O.json","graph_json":"https://pith.science/api/pith-number/6XPPXVXUO4EF3EPBOESWTFPL6O/graph.json","events_json":"https://pith.science/api/pith-number/6XPPXVXUO4EF3EPBOESWTFPL6O/events.json","paper":"https://pith.science/paper/6XPPXVXU"},"agent_actions":{"view_html":"https://pith.science/pith/6XPPXVXUO4EF3EPBOESWTFPL6O","download_json":"https://pith.science/pith/6XPPXVXUO4EF3EPBOESWTFPL6O.json","view_paper":"https://pith.science/paper/6XPPXVXU","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2608.05522&json=true","fetch_graph":"https://pith.science/api/pith-number/6XPPXVXUO4EF3EPBOESWTFPL6O/graph.json","fetch_events":"https://pith.science/api/pith-number/6XPPXVXUO4EF3EPBOESWTFPL6O/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/6XPPXVXUO4EF3EPBOESWTFPL6O/action/timestamp_anchor","attest_storage":"https://pith.science/pith/6XPPXVXUO4EF3EPBOESWTFPL6O/action/storage_attestation","attest_author":"https://pith.science/pith/6XPPXVXUO4EF3EPBOESWTFPL6O/action/author_attestation","sign_citation":"https://pith.science/pith/6XPPXVXUO4EF3EPBOESWTFPL6O/action/citation_signature","submit_replication":"https://pith.science/pith/6XPPXVXUO4EF3EPBOESWTFPL6O/action/replication_record"}},"created_at":"2026-08-07T00:48:01.097212+00:00","updated_at":"2026-08-07T00:48:01.097212+00:00"}