{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:X5ANBY3KCOIIMKATOCLTMIRT7D","short_pith_number":"pith:X5ANBY3K","schema_version":"1.0","canonical_sha256":"bf40d0e36a13908628137097362233f8e63eb0ebdc3221562ec28a5111eee5e2","source":{"kind":"arxiv","id":"2303.15463","version":2},"attestation_state":"computed","paper":{"title":"Uniform in time convergence of numerical schemes for stochastic differential equations via Strong Exponential stability: Euler methods, Split-Step and Tamed Schemes","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.NA","math.PR"],"primary_cat":"math.NA","authors_text":"Dan Crisan, Letizia Angeli, Michela Ottobre","submitted_at":"2023-03-23T08:37:12Z","abstract_excerpt":"We prove a general criterion providing sufficient conditions under which a time-discretiziation of a given Stochastic Differential Equation (SDE) is a uniform in time approximation of the SDE. The criterion is also, to a certain extent, discussed in the paper, necessary. Using such a criterion we then analyse the convergence properties of numerical methods for solutions of SDEs; we consider Explicit and Implicit Euler, split-step and (truncated) tamed Euler methods. In particular, we show that, under mild conditions on the coefficients of the SDE (locally Lipschitz and strictly monotonic), 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":"2303.15463","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.NA","submitted_at":"2023-03-23T08:37:12Z","cross_cats_sorted":["cs.NA","math.PR"],"title_canon_sha256":"243bd9aa78fed786a1386e0d6bcd82779576982789168c867ab465040623c2f4","abstract_canon_sha256":"7480e632b1d0604cbea01069f8b5cadcffc19c59eb13e1ec86e23f9120ffa3ca"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:03:22.604552Z","signature_b64":"7VNJ7jcLB/rVPn1kBHEM0b8XwHZm9ot98JelHtkeTeYz0yrgApgG/fwTxqoiSgCpDYWUC1YsQninli1f2RUZCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bf40d0e36a13908628137097362233f8e63eb0ebdc3221562ec28a5111eee5e2","last_reissued_at":"2026-07-05T10:03:22.604119Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:03:22.604119Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Uniform in time convergence of numerical schemes for stochastic differential equations via Strong Exponential stability: Euler methods, Split-Step and Tamed Schemes","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.NA","math.PR"],"primary_cat":"math.NA","authors_text":"Dan Crisan, Letizia Angeli, Michela Ottobre","submitted_at":"2023-03-23T08:37:12Z","abstract_excerpt":"We prove a general criterion providing sufficient conditions under which a time-discretiziation of a given Stochastic Differential Equation (SDE) is a uniform in time approximation of the SDE. The criterion is also, to a certain extent, discussed in the paper, necessary. Using such a criterion we then analyse the convergence properties of numerical methods for solutions of SDEs; we consider Explicit and Implicit Euler, split-step and (truncated) tamed Euler methods. In particular, we show that, under mild conditions on the coefficients of the SDE (locally Lipschitz and strictly monotonic), the"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2303.15463","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/2303.15463/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":"2303.15463","created_at":"2026-07-05T10:03:22.604188+00:00"},{"alias_kind":"arxiv_version","alias_value":"2303.15463v2","created_at":"2026-07-05T10:03:22.604188+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2303.15463","created_at":"2026-07-05T10:03:22.604188+00:00"},{"alias_kind":"pith_short_12","alias_value":"X5ANBY3KCOII","created_at":"2026-07-05T10:03:22.604188+00:00"},{"alias_kind":"pith_short_16","alias_value":"X5ANBY3KCOIIMKAT","created_at":"2026-07-05T10:03:22.604188+00:00"},{"alias_kind":"pith_short_8","alias_value":"X5ANBY3K","created_at":"2026-07-05T10:03:22.604188+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2505.14262","citing_title":"Strong convergence in the infinite horizon of numerical methods for stochastic delay differential equations","ref_index":1,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/X5ANBY3KCOIIMKATOCLTMIRT7D","json":"https://pith.science/pith/X5ANBY3KCOIIMKATOCLTMIRT7D.json","graph_json":"https://pith.science/api/pith-number/X5ANBY3KCOIIMKATOCLTMIRT7D/graph.json","events_json":"https://pith.science/api/pith-number/X5ANBY3KCOIIMKATOCLTMIRT7D/events.json","paper":"https://pith.science/paper/X5ANBY3K"},"agent_actions":{"view_html":"https://pith.science/pith/X5ANBY3KCOIIMKATOCLTMIRT7D","download_json":"https://pith.science/pith/X5ANBY3KCOIIMKATOCLTMIRT7D.json","view_paper":"https://pith.science/paper/X5ANBY3K","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2303.15463&json=true","fetch_graph":"https://pith.science/api/pith-number/X5ANBY3KCOIIMKATOCLTMIRT7D/graph.json","fetch_events":"https://pith.science/api/pith-number/X5ANBY3KCOIIMKATOCLTMIRT7D/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/X5ANBY3KCOIIMKATOCLTMIRT7D/action/timestamp_anchor","attest_storage":"https://pith.science/pith/X5ANBY3KCOIIMKATOCLTMIRT7D/action/storage_attestation","attest_author":"https://pith.science/pith/X5ANBY3KCOIIMKATOCLTMIRT7D/action/author_attestation","sign_citation":"https://pith.science/pith/X5ANBY3KCOIIMKATOCLTMIRT7D/action/citation_signature","submit_replication":"https://pith.science/pith/X5ANBY3KCOIIMKATOCLTMIRT7D/action/replication_record"}},"created_at":"2026-07-05T10:03:22.604188+00:00","updated_at":"2026-07-05T10:03:22.604188+00:00"}