Scaled zonal kernel quasi-interpolation on spheres

Abstract 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) attain a high-order approximation to target functions. In Phase II we discretize the spherical integrals utilizing quadrature rules to produce the final quasi-interpolants. Numerical experiments demonstrate that the new approximation algorithm is robust and amenable to be 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.