{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:MJOTMCKCKADIUX5X2JJA7XC7GE","short_pith_number":"pith:MJOTMCKC","schema_version":"1.0","canonical_sha256":"625d36094250068a5fb7d2520fdc5f311ea09b5487dc32e050f33c7e2a6b29af","source":{"kind":"arxiv","id":"2606.24207","version":1},"attestation_state":"computed","paper":{"title":"Quasi-Monte Carlo for SDE Simulation: Error Analysis and Dimensionality Reduction","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.NA"],"primary_cat":"math.NA","authors_text":"Du Ouyang, Zexin Pan, Zhijian He","submitted_at":"2026-06-23T06:48:28Z","abstract_excerpt":"We investigate the numerical simulation of general stochastic differential equations (SDEs) using Quasi-Monte Carlo (QMC) methods. First, we provide a rigorous theoretical analysis of the QMC method applied to the Euler-Maruyama (EM) scheme, establishing that it significantly accelerates the decay of the sampling error and achieves an asymptotically superior convergence rate over the classical Monte Carlo method. Second, the traditional EM scheme exhibits a slow polynomial decay of the discretization error, which necessitates a large number of time steps and leads to a significantly high integ"},"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":"2606.24207","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.NA","submitted_at":"2026-06-23T06:48:28Z","cross_cats_sorted":["cs.NA"],"title_canon_sha256":"5202cf767276076dcc42a2251f1dd96ffb784e46140254857d7c41d3d8c1c0e9","abstract_canon_sha256":"56c18261c448204f76d5fdeb7dcc29dc593eba035eec6b898f34ad207e0f2866"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-24T01:14:46.172097Z","signature_b64":"UupG9EcgLSyDa/xttLZ/UlkZSKojzE4aWRUpfCgqKqjTIkEiLw+zyFpV+OBNaewYydP3ChNvHIQYvSYrtIDBDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"625d36094250068a5fb7d2520fdc5f311ea09b5487dc32e050f33c7e2a6b29af","last_reissued_at":"2026-06-24T01:14:46.171484Z","signature_status":"signed_v1","first_computed_at":"2026-06-24T01:14:46.171484Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Quasi-Monte Carlo for SDE Simulation: Error Analysis and Dimensionality Reduction","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.NA"],"primary_cat":"math.NA","authors_text":"Du Ouyang, Zexin Pan, Zhijian He","submitted_at":"2026-06-23T06:48:28Z","abstract_excerpt":"We investigate the numerical simulation of general stochastic differential equations (SDEs) using Quasi-Monte Carlo (QMC) methods. First, we provide a rigorous theoretical analysis of the QMC method applied to the Euler-Maruyama (EM) scheme, establishing that it significantly accelerates the decay of the sampling error and achieves an asymptotically superior convergence rate over the classical Monte Carlo method. Second, the traditional EM scheme exhibits a slow polynomial decay of the discretization error, which necessitates a large number of time steps and leads to a significantly high integ"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.24207","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/2606.24207/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":"2606.24207","created_at":"2026-06-24T01:14:46.171596+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.24207v1","created_at":"2026-06-24T01:14:46.171596+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.24207","created_at":"2026-06-24T01:14:46.171596+00:00"},{"alias_kind":"pith_short_12","alias_value":"MJOTMCKCKADI","created_at":"2026-06-24T01:14:46.171596+00:00"},{"alias_kind":"pith_short_16","alias_value":"MJOTMCKCKADIUX5X","created_at":"2026-06-24T01:14:46.171596+00:00"},{"alias_kind":"pith_short_8","alias_value":"MJOTMCKC","created_at":"2026-06-24T01:14:46.171596+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/MJOTMCKCKADIUX5X2JJA7XC7GE","json":"https://pith.science/pith/MJOTMCKCKADIUX5X2JJA7XC7GE.json","graph_json":"https://pith.science/api/pith-number/MJOTMCKCKADIUX5X2JJA7XC7GE/graph.json","events_json":"https://pith.science/api/pith-number/MJOTMCKCKADIUX5X2JJA7XC7GE/events.json","paper":"https://pith.science/paper/MJOTMCKC"},"agent_actions":{"view_html":"https://pith.science/pith/MJOTMCKCKADIUX5X2JJA7XC7GE","download_json":"https://pith.science/pith/MJOTMCKCKADIUX5X2JJA7XC7GE.json","view_paper":"https://pith.science/paper/MJOTMCKC","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.24207&json=true","fetch_graph":"https://pith.science/api/pith-number/MJOTMCKCKADIUX5X2JJA7XC7GE/graph.json","fetch_events":"https://pith.science/api/pith-number/MJOTMCKCKADIUX5X2JJA7XC7GE/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/MJOTMCKCKADIUX5X2JJA7XC7GE/action/timestamp_anchor","attest_storage":"https://pith.science/pith/MJOTMCKCKADIUX5X2JJA7XC7GE/action/storage_attestation","attest_author":"https://pith.science/pith/MJOTMCKCKADIUX5X2JJA7XC7GE/action/author_attestation","sign_citation":"https://pith.science/pith/MJOTMCKCKADIUX5X2JJA7XC7GE/action/citation_signature","submit_replication":"https://pith.science/pith/MJOTMCKCKADIUX5X2JJA7XC7GE/action/replication_record"}},"created_at":"2026-06-24T01:14:46.171596+00:00","updated_at":"2026-06-24T01:14:46.171596+00:00"}