{ "id": "1308.3883", "version": "v1", "published": "2013-08-18T18:22:18.000Z", "updated": "2013-08-18T18:22:18.000Z", "title": "Efficient sum-of-exponentials approximations for the heat kernel and their applications", "authors": [ "Shidong Jiang", "Leslie Greengard", "Shaobo Wang" ], "comment": "23 pages, 5 figures, 3 tables", "categories": [ "math.NA" ], "abstract": "In this paper, we show that efficient separated sum-of-exponentials approximations can be constructed for the heat kernel in any dimension. In one space dimension, the heat kernel admits an approximation involving a number of terms that is of the order $O(\\log(\\frac{T}{\\delta}) (\\log(\\frac{1}{\\epsilon})+\\log\\log(\\frac{T}{\\delta})))$ for any $x\\in\\bbR$ and $\\delta \\leq t \\leq T$, where $\\epsilon$ is the desired precision. In all higher dimensions, the corresponding heat kernel admits an approximation involving only $O(\\log^2(\\frac{T}{\\delta}))$ terms for fixed accuracy $\\epsilon$. These approximations can be used to accelerate integral equation-based methods for boundary value problems governed by the heat equation in complex geometry. The resulting algorithms are nearly optimal. For $N_S$ points in the spatial discretization and $N_T$ time steps, the cost is $O(N_S N_T \\log^2 \\frac{T}{\\delta})$ in terms of both memory and CPU time for fixed accuracy $\\epsilon$. The algorithms can be parallelized in a straightforward manner. Several numerical examples are presented to illustrate the accuracy and stability of these approximations.", "revisions": [ { "version": "v1", "updated": "2013-08-18T18:22:18.000Z" } ], "analyses": { "subjects": [ "30E15", "35K05", "35K08", "45D05", "65E05", "65R10", "80A20" ], "keywords": [ "efficient sum-of-exponentials approximations", "applications", "corresponding heat kernel admits", "fixed accuracy", "accelerate integral equation-based methods" ], "note": { "typesetting": "TeX", "pages": 23, "language": "en", "license": "arXiv", "status": "editable", "adsabs": "2013arXiv1308.3883J" } } }