Spherical quasi-interpolation using scaled zonal kernels
<|reference_start|>Spherical quasi-interpolation using scaled zonal kernels: We propose and study a new quasi-interpolation method on spheres featuring the following two-phase construction and analysis. In Phase I, we analyze and characterize a large family of zonal kernels (e.g., the spherical version of Poisson kernel, Gaussian, compactly-supported radial kernels), so that the underlying spherical convolution operators (upon the introduction of a scaling parameter) attains a high-order of approximation to target functions. In Phase II, we discretize the spherical integrals utilizing quadrature rules of optimal order to produce the final quasi-interpolants. Numerical experiments demonstrate that the new quasi-interpolation algorithm is robust and amenable to integrated as well as distributed ways of implementation. Moreover, the underlying error-analysis shows that by fine-tuning the scaling parameter in the radial kernels employed, the resulting quasi-interpolants achieve a well-balanced trade-off between approximation and sampling errors.<|reference_end|>
@article{sun2024spherical,
    title={Spherical quasi-interpolation using scaled zonal kernels},
    author={Zhengjie Sun, Wenwu Gao, Xingping Sun},
    journal={arXiv preprint arXiv:2408.14803},
    year={2024},
    archivePrefix={arXiv},
    eprint={2408.14803},
    primaryClass={math.NA cs.NA}
}