{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:EBAC5BUHKKSASISIV2G5FXAE5S","short_pith_number":"pith:EBAC5BUH","schema_version":"1.0","canonical_sha256":"20402e868752a4092248ae8dd2dc04ec9c4358cb3474700551f3b12a0329c6a7","source":{"kind":"arxiv","id":"2501.06144","version":1},"attestation_state":"computed","paper":{"title":"Hybrid Weight Window Techniques for Time-Dependent Monte Carlo Neutronics","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.NA","physics.data-an"],"primary_cat":"math.NA","authors_text":"Caleb S. Shaw, Dmitriy Y. Anistratov","submitted_at":"2025-01-10T18:08:11Z","abstract_excerpt":"Efficient variance reduction of Monte Carlo simulations is desirable to avoid wasting computational resources. This paper presents an automated weight window algorithm for solving time-dependent particle transport problems. The weight window centers are defined by a hybrid forward solution of the discretized low-order second moment (LOSM) problem. The second-moment (SM) functionals defining the closure for the LOSM equations are computed by Monte Carlo solution. A filtering algorithm is applied to reduce noise in the SM functionals. The LOSM equations are discretized with first- and second-ord"},"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":"2501.06144","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.NA","submitted_at":"2025-01-10T18:08:11Z","cross_cats_sorted":["cs.NA","physics.data-an"],"title_canon_sha256":"1326541e66b6aed572bc044be8d3ae6d4c40a33f07bb040509a1787482b9cbde","abstract_canon_sha256":"00587a385ae445f795d25ddb8ce5f41c369b3522904789a7d09e4c03dbccdfdc"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:48:22.294578Z","signature_b64":"9I0+J7DfkBS8aTLotkrGcj2Pad+qRCYmbl9B/CgsLahTgWj78XELjqh6nJ1psGRFRUgHTKShRP2F7+FsrQP9Ag==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"20402e868752a4092248ae8dd2dc04ec9c4358cb3474700551f3b12a0329c6a7","last_reissued_at":"2026-07-05T11:48:22.294040Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:48:22.294040Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Hybrid Weight Window Techniques for Time-Dependent Monte Carlo Neutronics","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.NA","physics.data-an"],"primary_cat":"math.NA","authors_text":"Caleb S. Shaw, Dmitriy Y. Anistratov","submitted_at":"2025-01-10T18:08:11Z","abstract_excerpt":"Efficient variance reduction of Monte Carlo simulations is desirable to avoid wasting computational resources. This paper presents an automated weight window algorithm for solving time-dependent particle transport problems. The weight window centers are defined by a hybrid forward solution of the discretized low-order second moment (LOSM) problem. The second-moment (SM) functionals defining the closure for the LOSM equations are computed by Monte Carlo solution. A filtering algorithm is applied to reduce noise in the SM functionals. The LOSM equations are discretized with first- and second-ord"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.06144","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/2501.06144/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":"2501.06144","created_at":"2026-07-05T11:48:22.294099+00:00"},{"alias_kind":"arxiv_version","alias_value":"2501.06144v1","created_at":"2026-07-05T11:48:22.294099+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.06144","created_at":"2026-07-05T11:48:22.294099+00:00"},{"alias_kind":"pith_short_12","alias_value":"EBAC5BUHKKSA","created_at":"2026-07-05T11:48:22.294099+00:00"},{"alias_kind":"pith_short_16","alias_value":"EBAC5BUHKKSASISI","created_at":"2026-07-05T11:48:22.294099+00:00"},{"alias_kind":"pith_short_8","alias_value":"EBAC5BUH","created_at":"2026-07-05T11:48:22.294099+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/EBAC5BUHKKSASISIV2G5FXAE5S","json":"https://pith.science/pith/EBAC5BUHKKSASISIV2G5FXAE5S.json","graph_json":"https://pith.science/api/pith-number/EBAC5BUHKKSASISIV2G5FXAE5S/graph.json","events_json":"https://pith.science/api/pith-number/EBAC5BUHKKSASISIV2G5FXAE5S/events.json","paper":"https://pith.science/paper/EBAC5BUH"},"agent_actions":{"view_html":"https://pith.science/pith/EBAC5BUHKKSASISIV2G5FXAE5S","download_json":"https://pith.science/pith/EBAC5BUHKKSASISIV2G5FXAE5S.json","view_paper":"https://pith.science/paper/EBAC5BUH","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2501.06144&json=true","fetch_graph":"https://pith.science/api/pith-number/EBAC5BUHKKSASISIV2G5FXAE5S/graph.json","fetch_events":"https://pith.science/api/pith-number/EBAC5BUHKKSASISIV2G5FXAE5S/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/EBAC5BUHKKSASISIV2G5FXAE5S/action/timestamp_anchor","attest_storage":"https://pith.science/pith/EBAC5BUHKKSASISIV2G5FXAE5S/action/storage_attestation","attest_author":"https://pith.science/pith/EBAC5BUHKKSASISIV2G5FXAE5S/action/author_attestation","sign_citation":"https://pith.science/pith/EBAC5BUHKKSASISIV2G5FXAE5S/action/citation_signature","submit_replication":"https://pith.science/pith/EBAC5BUHKKSASISIV2G5FXAE5S/action/replication_record"}},"created_at":"2026-07-05T11:48:22.294099+00:00","updated_at":"2026-07-05T11:48:22.294099+00:00"}