{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:SYSYSM2MTOLCJAAQCVABYO3KTU","short_pith_number":"pith:SYSYSM2M","schema_version":"1.0","canonical_sha256":"962589334c9b9624801015401c3b6a9d1dee0ebc849ef516c05a43e68faa96fc","source":{"kind":"arxiv","id":"1904.07097","version":1},"attestation_state":"computed","paper":{"title":"Taming chaos to sample rare events: the effect of weak chaos","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["physics.comp-ph"],"primary_cat":"cond-mat.stat-mech","authors_text":"Eduardo G. Altmann, Joao M. V. P. Lopes, Jorge C. Leitao","submitted_at":"2019-04-09T04:04:41Z","abstract_excerpt":"Rare events in non-linear dynamical systems are difficult to sample because of the sensitivity to perturbations of initial conditions and of complex landscapes in phase space. Here we discuss strategies to control these difficulties and succeed in obtainining an efficient sampling within a Metropolis-Hastings Monte Carlo framework. After reviewing previous successes in the case of strongly chaotic systems, we discuss the case of weakly chaotic systems. We show how different types of non-hyperbolicities limit the efficiency of previously designed sampling methods and we discuss strategies how t"},"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":"1904.07097","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cond-mat.stat-mech","submitted_at":"2019-04-09T04:04:41Z","cross_cats_sorted":["physics.comp-ph"],"title_canon_sha256":"38e6df5d956691937b9c1c0d9b9ecccaff2d09b025c27b558028b63eb32eb316","abstract_canon_sha256":"0ece68235c5406cc450c20b78ddc29d96b116f7142474f2400fd55c85043e6d9"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:48:19.578626Z","signature_b64":"UPBhkpMgDOGa000WdlC9I0qhp9TyU+1jY15Sc44OviUxKXoxGiZsI82CnRA6whU2t0mcZk2LPTDGd6eJO0K5AA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"962589334c9b9624801015401c3b6a9d1dee0ebc849ef516c05a43e68faa96fc","last_reissued_at":"2026-05-17T23:48:19.577915Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:48:19.577915Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Taming chaos to sample rare events: the effect of weak chaos","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["physics.comp-ph"],"primary_cat":"cond-mat.stat-mech","authors_text":"Eduardo G. Altmann, Joao M. V. P. Lopes, Jorge C. Leitao","submitted_at":"2019-04-09T04:04:41Z","abstract_excerpt":"Rare events in non-linear dynamical systems are difficult to sample because of the sensitivity to perturbations of initial conditions and of complex landscapes in phase space. Here we discuss strategies to control these difficulties and succeed in obtainining an efficient sampling within a Metropolis-Hastings Monte Carlo framework. After reviewing previous successes in the case of strongly chaotic systems, we discuss the case of weakly chaotic systems. We show how different types of non-hyperbolicities limit the efficiency of previously designed sampling methods and we discuss strategies how t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.07097","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":"1904.07097","created_at":"2026-05-17T23:48:19.578033+00:00"},{"alias_kind":"arxiv_version","alias_value":"1904.07097v1","created_at":"2026-05-17T23:48:19.578033+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.07097","created_at":"2026-05-17T23:48:19.578033+00:00"},{"alias_kind":"pith_short_12","alias_value":"SYSYSM2MTOLC","created_at":"2026-05-18T12:33:27.125529+00:00"},{"alias_kind":"pith_short_16","alias_value":"SYSYSM2MTOLCJAAQ","created_at":"2026-05-18T12:33:27.125529+00:00"},{"alias_kind":"pith_short_8","alias_value":"SYSYSM2M","created_at":"2026-05-18T12:33:27.125529+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/SYSYSM2MTOLCJAAQCVABYO3KTU","json":"https://pith.science/pith/SYSYSM2MTOLCJAAQCVABYO3KTU.json","graph_json":"https://pith.science/api/pith-number/SYSYSM2MTOLCJAAQCVABYO3KTU/graph.json","events_json":"https://pith.science/api/pith-number/SYSYSM2MTOLCJAAQCVABYO3KTU/events.json","paper":"https://pith.science/paper/SYSYSM2M"},"agent_actions":{"view_html":"https://pith.science/pith/SYSYSM2MTOLCJAAQCVABYO3KTU","download_json":"https://pith.science/pith/SYSYSM2MTOLCJAAQCVABYO3KTU.json","view_paper":"https://pith.science/paper/SYSYSM2M","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1904.07097&json=true","fetch_graph":"https://pith.science/api/pith-number/SYSYSM2MTOLCJAAQCVABYO3KTU/graph.json","fetch_events":"https://pith.science/api/pith-number/SYSYSM2MTOLCJAAQCVABYO3KTU/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/SYSYSM2MTOLCJAAQCVABYO3KTU/action/timestamp_anchor","attest_storage":"https://pith.science/pith/SYSYSM2MTOLCJAAQCVABYO3KTU/action/storage_attestation","attest_author":"https://pith.science/pith/SYSYSM2MTOLCJAAQCVABYO3KTU/action/author_attestation","sign_citation":"https://pith.science/pith/SYSYSM2MTOLCJAAQCVABYO3KTU/action/citation_signature","submit_replication":"https://pith.science/pith/SYSYSM2MTOLCJAAQCVABYO3KTU/action/replication_record"}},"created_at":"2026-05-17T23:48:19.578033+00:00","updated_at":"2026-05-17T23:48:19.578033+00:00"}