pith:YTUDTDDX
An Efficient Multilevel Preconditioned Nonlinear Conjugate Gradient Method for Incremental Potential Contact
The MAS-PNCG method with a Sparse-Input Woodbury update adapts multilevel preconditioners to changing contacts, enabling faster nonlinear conjugate gradient solves than Newton's method while keeping simulations intersection-free.
arxiv:2604.19892 v1 · 2026-04-21 · cs.GR · cs.AI
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Claims
Experiments demonstrate that our MAS-PNCG outperforms state-of-the-art Newton-PCG solvers, GIPC and StiffGIPC, both preconditioned with MAS up to 5.66× and 2.07× respectively.
The Sparse-Input Woodbury update algorithm maintains effective spectral properties of the multilevel preconditioner for rapidly changing contact sets without requiring full rebuilds or introducing instability in the nonlinear iterations.
MAS-PNCG accelerates IPC by incrementally updating multilevel MAS preconditioners via Sparse-Input Woodbury, adding Hessian-aware 2D subspace minimization and per-subdomain CCD, achieving up to 5.66x speedup over Newton-PCG baselines.
References
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| First computed | 2026-05-20T01:05:14.137105Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
c4e8398c7744499f8ebee8445cb86ff6d150ff095de1707704e92dde7620d221
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/YTUDTDDXIREZ7DV65BCFZODP63 \
| jq -c '.canonical_record' \
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Canonical record JSON
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