284 research outputs found

    Kernel Approximation on Manifolds I: Bounding the Lebesgue Constant

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    The purpose of this paper is to establish that for any compact, connected C^{\infty} Riemannian manifold there exists a robust family of kernels of increasing smoothness that are well suited for interpolation. They generate Lagrange functions that are uniformly bounded and decay away from their center at an exponential rate. An immediate corollary is that the corresponding Lebesgue constant will be uniformly bounded with a constant whose only dependence on the set of data sites is reflected in the mesh ratio, which measures the uniformity of the data. The analysis needed for these results was inspired by some fundamental work of Matveev where the Sobolev decay of Lagrange functions associated with certain kernels on \Omega \subset R^d was obtained. With a bit more work, one establishes the following: Lebesgue constants associated with surface splines and Sobolev splines are uniformly bounded on R^d provided the data sites \Xi are quasi-uniformly distributed. The non-Euclidean case is more involved as the geometry of the underlying surface comes into play. In addition to establishing bounded Lebesgue constants in this setting, a "zeros lemma" for compact Riemannian manifolds is established.Comment: 33 pages, 2 figures, new title, accepted for publication in SIAM J. on Math. Ana

    A unified approach to quantum dynamical maps and gaussian Wigner distributions

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    The KLM conditions are conditions that are necessary and sufficient for a phase-space function to be a Wigner distribution function (WDF). We apply them here to discuss three questions that have arisen recently: (1) For which WDFs P0 will the map P→P0*P be a quantum dynamical map - i.e. a map that takes WDFs to WDFs? (2) What are necessary and sufficient conditions for a phase-space gaussian to be a WDF? (3) Are there non-gaussian, non-negative WDFs? © 1988

    Error estimates for interpolation of rough data using the scattered shifts of a radial basis function

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    The error between appropriately smooth functions and their radial basis function interpolants, as the interpolation points fill out a bounded domain in R^d, is a well studied artifact. In all of these cases, the analysis takes place in a natural function space dictated by the choice of radial basis function -- the native space. The native space contains functions possessing a certain amount of smoothness. This paper establishes error estimates when the function being interpolated is conspicuously rough.Comment: 12 page
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