A Practical Walk-on-Boundary Method for Boundary Value Problems
arXiv:2305.04403 · doi:10.1145/3592109
Abstract
We introduce the walk-on-boundary (WoB) method for solving boundary value problems to computer graphics. WoB is a grid-free Monte Carlo solver for certain classes of second order partial differential equations. A similar Monte Carlo solver, the walk-on-spheres (WoS) method, has been recently popularized in computer graphics due to its advantages over traditional spatial discretization-based alternatives. We show that WoB's intrinsic properties yield further advantages beyond those of WoS. Unlike WoS, WoB naturally supports various boundary conditions (Dirichlet, Neumann, Robin, and mixed) for both interior and exterior domains. WoB builds upon boundary integral formulations, and it is mathematically more similar to light transport simulation in rendering than the random walk formulation of WoS. This similarity between WoB and rendering allows us to implement WoB on top of Monte Carlo ray tracing, and to incorporate advanced rendering techniques (e.g., bidirectional estimators with multiple importance sampling, the virtual point lights method, and Markov chain Monte Carlo) into WoB. WoB does not suffer from the intrinsic bias of WoS near the boundary and can estimate solutions precisely on the boundary. Our numerical results highlight the advantages of WoB over WoS as an attractive alternative to solve boundary value problems based on Monte Carlo.
arXiv commentAccepted to ACM SIGGRAPH North America 2023 / Transactions on Graphics. See https://rsugimoto.net/WoBforBVPsProject/ for updates, including the reference implementation
References in corpus (3)
Cited by in corpus (7)
- Walk on Stars: A Grid-Free Monte Carlo Method for PDEs with Neumann Boundary Conditions
- Differential Walk on Spheres
- Velocity-Based Monte Carlo Fluids
- Projected Walk on Spheres: A Monte Carlo Closest Point Method for Surface PDEs
- A Closest Point Method for PDEs on Manifolds with Interior Boundary Conditions for Geometry Processing
- Stochastic Barnes-Hut Approximation for Fast Summation on the GPU
- Solving partial differential equations in participating media