{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:BLVGQTL225L3M2HWIZTMPXTJHV","short_pith_number":"pith:BLVGQTL2","schema_version":"1.0","canonical_sha256":"0aea684d7ad757b668f64666c7de693d7e97c90d65a6df2cda810bb5fb4a9ec3","source":{"kind":"arxiv","id":"1603.04039","version":1},"attestation_state":"computed","paper":{"title":"AP-Cloud: Adaptive Particle-in-Cloud Method for Optimal Solutions to Vlasov-Poisson Equation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.NA","authors_text":"Kwangmin Yu, Roman Samulyak, Xiangmin Jiao, Xingyu Wang","submitted_at":"2016-03-13T15:15:08Z","abstract_excerpt":"We propose a new adaptive Particle-in-Cloud (AP-Cloud) method for obtaining optimal numerical solutions to the Vlasov-Poisson equation. Unlike the traditional particle-in-cell (PIC) method, which is commonly used for solving this problem, the AP-Cloud adaptively selects computational nodes or particles to deliver higher accuracy and efficiency when the particle distribution is highly non-uniform. Unlike other adaptive techniques for PIC, our method balances the errors in PDE discretization and Monte Carlo integration, and discretizes the differential operators using a generalized finite differ"},"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":"1603.04039","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.NA","submitted_at":"2016-03-13T15:15:08Z","cross_cats_sorted":[],"title_canon_sha256":"b16e8cd34fa61462aeb79f53f594864bf5d95cef705d831188ac90afd2b82aba","abstract_canon_sha256":"b30a6d27e09de52c6b536febf97ed9f7b6c59ee5b3593eef6b36ec2d4581290f"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:13:54.256238Z","signature_b64":"HCeFUDgUaZXU69i9KMyc6U1Rx8J0gPH1FUI4tWR5FqW7ZgHABPf5lyNvGmVaXds5BlM87VPOf/02Hz5/bOiuDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0aea684d7ad757b668f64666c7de693d7e97c90d65a6df2cda810bb5fb4a9ec3","last_reissued_at":"2026-05-18T01:13:54.255735Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:13:54.255735Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"AP-Cloud: Adaptive Particle-in-Cloud Method for Optimal Solutions to Vlasov-Poisson Equation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.NA","authors_text":"Kwangmin Yu, Roman Samulyak, Xiangmin Jiao, Xingyu Wang","submitted_at":"2016-03-13T15:15:08Z","abstract_excerpt":"We propose a new adaptive Particle-in-Cloud (AP-Cloud) method for obtaining optimal numerical solutions to the Vlasov-Poisson equation. Unlike the traditional particle-in-cell (PIC) method, which is commonly used for solving this problem, the AP-Cloud adaptively selects computational nodes or particles to deliver higher accuracy and efficiency when the particle distribution is highly non-uniform. Unlike other adaptive techniques for PIC, our method balances the errors in PDE discretization and Monte Carlo integration, and discretizes the differential operators using a generalized finite differ"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1603.04039","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":"1603.04039","created_at":"2026-05-18T01:13:54.255807+00:00"},{"alias_kind":"arxiv_version","alias_value":"1603.04039v1","created_at":"2026-05-18T01:13:54.255807+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1603.04039","created_at":"2026-05-18T01:13:54.255807+00:00"},{"alias_kind":"pith_short_12","alias_value":"BLVGQTL225L3","created_at":"2026-05-18T12:30:07.202191+00:00"},{"alias_kind":"pith_short_16","alias_value":"BLVGQTL225L3M2HW","created_at":"2026-05-18T12:30:07.202191+00:00"},{"alias_kind":"pith_short_8","alias_value":"BLVGQTL2","created_at":"2026-05-18T12:30:07.202191+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/BLVGQTL225L3M2HWIZTMPXTJHV","json":"https://pith.science/pith/BLVGQTL225L3M2HWIZTMPXTJHV.json","graph_json":"https://pith.science/api/pith-number/BLVGQTL225L3M2HWIZTMPXTJHV/graph.json","events_json":"https://pith.science/api/pith-number/BLVGQTL225L3M2HWIZTMPXTJHV/events.json","paper":"https://pith.science/paper/BLVGQTL2"},"agent_actions":{"view_html":"https://pith.science/pith/BLVGQTL225L3M2HWIZTMPXTJHV","download_json":"https://pith.science/pith/BLVGQTL225L3M2HWIZTMPXTJHV.json","view_paper":"https://pith.science/paper/BLVGQTL2","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1603.04039&json=true","fetch_graph":"https://pith.science/api/pith-number/BLVGQTL225L3M2HWIZTMPXTJHV/graph.json","fetch_events":"https://pith.science/api/pith-number/BLVGQTL225L3M2HWIZTMPXTJHV/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/BLVGQTL225L3M2HWIZTMPXTJHV/action/timestamp_anchor","attest_storage":"https://pith.science/pith/BLVGQTL225L3M2HWIZTMPXTJHV/action/storage_attestation","attest_author":"https://pith.science/pith/BLVGQTL225L3M2HWIZTMPXTJHV/action/author_attestation","sign_citation":"https://pith.science/pith/BLVGQTL225L3M2HWIZTMPXTJHV/action/citation_signature","submit_replication":"https://pith.science/pith/BLVGQTL225L3M2HWIZTMPXTJHV/action/replication_record"}},"created_at":"2026-05-18T01:13:54.255807+00:00","updated_at":"2026-05-18T01:13:54.255807+00:00"}