{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:DLYUWNSMIBD3RZDHFK3UNJDPIQ","short_pith_number":"pith:DLYUWNSM","schema_version":"1.0","canonical_sha256":"1af14b364c4047b8e4672ab746a46f442d82e3613c6ff0dabdd1a3223bc48107","source":{"kind":"arxiv","id":"2505.13390","version":1},"attestation_state":"computed","paper":{"title":"MGPBD: A Multigrid Accelerated Global XPBD Solver","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.GR","authors_text":"Aimin Hao, Chunlei Li, Peng Yu, Qinping Zhao, Shuai Li, Siyuan Yu, Tiantian Liu, Yang Gao, Yuting Xiao","submitted_at":"2025-05-19T17:31:47Z","abstract_excerpt":"We introduce a novel Unsmoothed Aggregation (UA) Algebraic Multigrid (AMG) method combined with Preconditioned Conjugate Gradient (PCG) to overcome the limitations of Extended Position-Based Dynamics (XPBD) in high-resolution and high-stiffness simulations. While XPBD excels in simulating deformable objects due to its speed and simplicity, its nonlinear Gauss-Seidel (GS) solver often struggles with low-frequency errors, leading to instability and stalling issues, especially in high-resolution, high-stiffness simulations. Our multigrid approach addresses these issues efficiently by leveraging A"},"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":"2505.13390","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.GR","submitted_at":"2025-05-19T17:31:47Z","cross_cats_sorted":[],"title_canon_sha256":"d604820b6ae817eb011751b6c2ccf9de4fa7ab77b9f6efc2cab056ce32614350","abstract_canon_sha256":"e16ca818527fe4140dcbe454785fe77da52a46dafff47817162f25874323aa9e"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:05:29.352434Z","signature_b64":"PGYnQI1NcW0kCUKtUAcwbBd67tgpNQ6BaS89BRNtdlmVbfHNqR9EoHCP4megAkSHJ0ZMwQw/CxW7q0AmFHdyCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1af14b364c4047b8e4672ab746a46f442d82e3613c6ff0dabdd1a3223bc48107","last_reissued_at":"2026-07-05T11:05:29.351938Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:05:29.351938Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"MGPBD: A Multigrid Accelerated Global XPBD Solver","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.GR","authors_text":"Aimin Hao, Chunlei Li, Peng Yu, Qinping Zhao, Shuai Li, Siyuan Yu, Tiantian Liu, Yang Gao, Yuting Xiao","submitted_at":"2025-05-19T17:31:47Z","abstract_excerpt":"We introduce a novel Unsmoothed Aggregation (UA) Algebraic Multigrid (AMG) method combined with Preconditioned Conjugate Gradient (PCG) to overcome the limitations of Extended Position-Based Dynamics (XPBD) in high-resolution and high-stiffness simulations. While XPBD excels in simulating deformable objects due to its speed and simplicity, its nonlinear Gauss-Seidel (GS) solver often struggles with low-frequency errors, leading to instability and stalling issues, especially in high-resolution, high-stiffness simulations. Our multigrid approach addresses these issues efficiently by leveraging A"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.13390","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/2505.13390/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":"2505.13390","created_at":"2026-07-05T11:05:29.351997+00:00"},{"alias_kind":"arxiv_version","alias_value":"2505.13390v1","created_at":"2026-07-05T11:05:29.351997+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.13390","created_at":"2026-07-05T11:05:29.351997+00:00"},{"alias_kind":"pith_short_12","alias_value":"DLYUWNSMIBD3","created_at":"2026-07-05T11:05:29.351997+00:00"},{"alias_kind":"pith_short_16","alias_value":"DLYUWNSMIBD3RZDH","created_at":"2026-07-05T11:05:29.351997+00:00"},{"alias_kind":"pith_short_8","alias_value":"DLYUWNSM","created_at":"2026-07-05T11:05:29.351997+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/DLYUWNSMIBD3RZDHFK3UNJDPIQ","json":"https://pith.science/pith/DLYUWNSMIBD3RZDHFK3UNJDPIQ.json","graph_json":"https://pith.science/api/pith-number/DLYUWNSMIBD3RZDHFK3UNJDPIQ/graph.json","events_json":"https://pith.science/api/pith-number/DLYUWNSMIBD3RZDHFK3UNJDPIQ/events.json","paper":"https://pith.science/paper/DLYUWNSM"},"agent_actions":{"view_html":"https://pith.science/pith/DLYUWNSMIBD3RZDHFK3UNJDPIQ","download_json":"https://pith.science/pith/DLYUWNSMIBD3RZDHFK3UNJDPIQ.json","view_paper":"https://pith.science/paper/DLYUWNSM","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2505.13390&json=true","fetch_graph":"https://pith.science/api/pith-number/DLYUWNSMIBD3RZDHFK3UNJDPIQ/graph.json","fetch_events":"https://pith.science/api/pith-number/DLYUWNSMIBD3RZDHFK3UNJDPIQ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/DLYUWNSMIBD3RZDHFK3UNJDPIQ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/DLYUWNSMIBD3RZDHFK3UNJDPIQ/action/storage_attestation","attest_author":"https://pith.science/pith/DLYUWNSMIBD3RZDHFK3UNJDPIQ/action/author_attestation","sign_citation":"https://pith.science/pith/DLYUWNSMIBD3RZDHFK3UNJDPIQ/action/citation_signature","submit_replication":"https://pith.science/pith/DLYUWNSMIBD3RZDHFK3UNJDPIQ/action/replication_record"}},"created_at":"2026-07-05T11:05:29.351997+00:00","updated_at":"2026-07-05T11:05:29.351997+00:00"}