http://arxiv.org/abs/2109.13926
Interpolating unstructured data using barycentric coordinates becomes infeasible at high dimensions due to the prohibitive memory requirements of building a Delaunay triangulation. We present a new algorithm to construct ad-hoc simplices that are empirically guaranteed to contain the target coordinates, based on a nearest neighbor heuristic and an iterative dimensionality reduction through projection. We use these simplices to interpolate the astrophysical cooling function $\Lambda$ and show that this new approach clearly outperforms our previous implementation at high dimensions.
S. Lüders and K. Dolag
Thu, 30 Sep 21
51/82
Comments: 4 pages, 2 figures