Boundary Value Caching for Walk on Spheres

Boundary Value Caching for Walk on Spheres
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球体行走的边界值缓存

DOI:
10.1145/3592400
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发表时间:
2023
影响因子:
6.2
通讯作者:
Gkioulekas, Ioannis
Gkioulekas, Ioannis
中科院分区:
计算机科学1区
文献类型:
--
作者:
Miller, Bailey;Sawhney, Rohan;Crane, Keenan;Gkioulekas, Ioannis

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无网格蒙特卡罗方法(例如球上行走)可用于求解椭圆偏微分方程,而无需网格生成或全局求解。然而,此类方法独立地估计每个点的解,因此没有利用椭圆问题解的高度空间规律性。我们提出了一种快速缓存策略,该策略首先估计沿域边界(或局部感兴趣区域)随机采样点的解值和导数。然后,这些缓存的值通过边界积分公式提供内点处解(或其梯度)的廉价、输出敏感的评估。与经典的边界积分方法不同,我们的缓存方案引入了零统计偏差,并且不需要密集的全局求解。此外,我们可以处理不完美的几何形状(例如,具有自相交)和详细的边界/源项,而无需修复或重新采样边界表示。总体而言,我们的方案在精神上类似于真实感渲染中的虚拟点光方法:它抑制了独立蒙特卡罗估计的典型椒盐噪声特征,同时仍然保留了蒙特卡罗求解器的许多优点:渐进评估、简单并行化、几何鲁棒性等。我们使用视觉和几何计算的测试问题来验证我们的方法。
Grid-free Monte Carlo methods such as walk on spheres can be used to solve elliptic partial differential equations without mesh generation or global solves. However, such methods independently estimate the solution at every point, and hence do not take advantage of the high spatial regularity of solutions to elliptic problems. We propose a fast caching strategy which first estimates solution values and derivatives at randomly sampled points along the boundary of the domain (or a local region of interest). These cached values then provide cheap, output-sensitive evaluation of the solution (or its gradient) at interior points, via a boundary integral formulation. Unlike classic boundary integral methods, our caching scheme introduces zero statistical bias and does not require a dense global solve. Moreover we can handle imperfect geometry (e.g., with self-intersections) and detailed boundary/source terms without repairing or resampling the boundary representation. Overall, our scheme is similar in spirit to virtual point light methods from photorealistic rendering: it suppresses the typical salt-and-pepper noise characteristic of independent Monte Carlo estimates, while still retaining the many advantages of Monte Carlo solvers: progressive evaluation, trivial parallelization, geometric robustness, etc. We validate our approach using test problems from visual and geometric computing.
星上行走:具有诺伊曼边界条件的偏微分方程的无网格蒙特卡罗方法
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发表时间: 2023
影响因子: 6.2
作者:
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发表时间: 2020-07
期刊: ACM Transactions on Graphics (TOG)
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