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An Efficient Multilevel Preconditioned Nonlinear Conjugate Gradient Method for Incremental Potential Contact

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An Efficient Multilevel Preconditioned Nonlinear Conjugate Gradient Method for Incremental Potential Contact
⚡ TL;DR · AI summary

A new method called MAS-PNCG has been developed to improve the efficiency of Incremental Potential Contact simulations. This method addresses the high computational costs associated with traditional approaches by utilizing a Sparse-Input Woodbury update algorithm. Experimental results show that MAS-PNCG significantly outperforms existing solvers in terms of speed and efficiency.

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arXiv cs.AI
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Computer Science > Graphics arXiv:2604.19892 (cs) [Submitted on 21 Apr 2026] Title:An Efficient Multilevel Preconditioned Nonlinear Conjugate Gradient Method for Incremental Potential Contact Authors:Yu Zhang, Xing Shen, Kemeng Huang, Wei Chen, Yin Yang, Taku Komura, Tiantian Liu, Xingang Pan View a PDF of the paper titled An Efficient Multilevel Preconditioned Nonlinear Conjugate Gradient Method for Incremental Potential Contact, by Yu Zhang and 7 other authors View PDF HTML (experimental) Abstract:Incremental Potential Contact (IPC) guarantees intersection-free simulation but suffers from high computational costs due to the expensive Hessian assembly and linear solves required by Newton's method.

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