From Walks to Skeletons: A Reusable Transport Architecture for Interactive Monte Carlo PDE Solvers
Abstract
Walk-on-Spheres (WoS) enables mesh-free solutions of elliptic PDEs, but conventional methods repeatedly discard sampled trajectories, limiting their efficiency in interactive applications. We introduce reusable transport skeletons, a persistent representation that organizes stochastic walks into a shared computational graph. Our framework enables efficient reuse across spatial queries and boundary conditions, while supporting progressive refinement, structure-preserving compression, and local adaptation to dynamic geometry. It further enables interactive editing of transport between selected regions. Experiments demonstrate substantial computational savings while preserving solution accuracy. By transforming transient stochastic trajectories into reusable transport structures, our method provides a flexible foundation for interactive Monte Carlo PDE solving.
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BibTeX
@misc{liao2026from,
title = {{From Walks to Skeletons: A Reusable Transport Architecture for Interactive Monte Carlo PDE Solvers}},
author = {Yunfeng Liao and Yucheng Wu and Xiucheng Li},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.36931},
eprint = {2610.36931},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.36931},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - From Walks to Skeletons: A Reusable Transport Architecture for Interactive Monte Carlo PDE Solvers
AU - Yunfeng Liao
AU - Yucheng Wu
AU - Xiucheng Li
PY - 2026
DA - 2026/10/27
PB - arXiv
DO - 10.48550/arxiv.2610.36931
UR - https://arxiv.org/abs/2610.36931
AB - Walk-on-Spheres (WoS) enables mesh-free solutions of elliptic PDEs, but conventional methods repeatedly discard sampled trajectories, limiting their efficiency in interactive applications. We introduce reusable transport skeletons, a persistent representation that organizes stochastic walks into a shared computational graph. Our framework enables efficient reuse across spatial queries and boundary conditions, while supporting progressive refinement, structure-preserving compression, and local adaptation to dynamic geometry. It further enables interactive editing of transport between selected regions. Experiments demonstrate substantial computational savings while preserving solution accuracy. By transforming transient stochastic trajectories into reusable transport structures, our method provides a flexible foundation for interactive Monte Carlo PDE solving.
ER -