2020/05/29 by Wei Guo, Juntao Huang, Zhanjing Tao +1
Mathematics · Computer Science · #math.NA #cs.NA
paper · pdf · doi:10.1016/j.jcp.2021.110294
arXiv admin note: text overlap with arXiv:2004.08525
arxiv created 2020/05/29 · arxiv updated 2021/04/14
We are interested in numerically solving the Hamilton-Jacobi (HJ) equations, which arise in optimal control and many other applications. Oftentimes, such equations are posed in high dimensions, and this poses great numerical challenges. This work proposes a class of adaptive sparse grid (also called adaptive multiresolution) local discontinuous Galerkin (DG) methods for solving Hamilton-Jacobi equations in high dimensions. By using the sparse grid techniques, we can treat moderately high dimensional cases. Adaptivity is incorporated to capture kinks and other local structures of the solutions. Two classes of multiwavelets are used to achieve multiresolution, which are the orthonormal Alpert's multiwavelets and the interpolatory multiwavelets. Numerical tests in up to four dimensions are provided to validate the performance of the method.