Andrei Osipov

Andrei Osipov, Vladimir Rokhlin

As demonstrated by Slepian et. al. in a sequence of classical papers, prolate spheroidal wave functions (PSWFs) provide a natural and efficient tool for computing with bandlimited functions defined on an interval. Recently, PSWFs have been becoming increasingly popular in various areas in which such functions occur - this includes physics (e.g. wave phenomena, fluid dynamics), engineering (signal processing, filter design), etc. To use PSWFs as a computational tool, one needs fast and accurate numerical algorithms for the evaluation of PSWFs and related quantities, as well as for the construction of corresponding quadrature rules, interpolation formulas, etc. During the last 15 years, substantial progress has been made in the design of such algorithms. However, many of the existing algorithms tend to be relatively slow when $c$ is large (e.g. c>10^4). In this paper, we describe several numerical algorithms for the evaluation of PSWFs and related quantities, and design a class of PSWF-based quadratures for the integration of bandlimited functions. While the analysis is somewhat involved and will be published separately, the resulting numerical algorithms are quite simple and efficient in practice. For example, the evaluation of the $n$th eigenvalue of the prolate integral operator requires $O(n+c \cdot \log c)$ operations; the construction of accurate quadrature rules for the integration (and associated interpolation) of bandlimited functions with band limit $c$ requires $O(c)$ operations. All algorithms described in this paper produce results essentially to machine precision. Our results are illustrated via several numerical experiments.

Andrei Osipov, Vladimir Rokhlin

As demonstrated by Slepian et. al. in a sequence of classical papers, prolate spheroidal wave functions (PSWFs) provide a natural and efficient tool for computing with bandlimited functions defined on an interval. As a result, PSWFs are becoming increasing popular in various areas in which such function occur - this includes physics (e.g. wave phenomena, fluid dynamics), engineering (e.g. signal processing, filter design), etc. To use PSWFs as a computational tool, one needs fast and accurate numerical algorithms for the evaluation of PSWFs and related quantities, as well as for the construction of quadratures, interpolation formulas, etc. Even though, for the last half a century, substantial progress has been made in design of such algorithms, the complexity of many of the existing algorithms, however, is at least quadratic in the band limit $c$. For example, the evaluation of the $n$th eigenvalue of the prolate integral operator requires at least $O(c^2)$ operations. Therefore, while the existing algorithms are quite satisfactory for moderate values of $c$ (e.g. $c \leq 10^3$), they tend to be relatively slow when $c$ is large (e.g. $c \geq 10^4$). In this paper, we describe several numerical algorithms for the evaluation of PSWFs and related quantities, and design a class of PSWF-based quadratures for the integration of bandlimited functions. Also, we perform detailed analysis of the related properties of PSWFs. While the analysis is somewhat involved, the resulting numerical algorithms are quite simple and efficient in practice. For example, the evaluation of the $n$th eigenvalue of the prolate integral operator requires $O(n+c)$ operations; also, the construction of related accurate quadrature rules requires $O(c)$ operations. Our results are illustrated via several numerical experiments.

Andrei Osipov

Prolate spheroidal wave functions (PSWFs) play an important role in various areas, from physics (e.g. wave phenomena, fluid dynamics) to engineering (e.g. signal processing, filter design). One of the principal reasons for the importance of PSWFs is that they are a natural and efficient tool for computing with bandlimited functions, that frequently occur in the abovementioned areas. This is due to the fact that PSWFs are the eigenfunctions of the integral operator, that represents timelimiting followed by lowpassing. Needless to say, the behavior of this operator is governed by the decay rate of its eigenvalues. Therefore, investigation of this decay rate plays a crucial role in the related theory and applications - for example, in construction of quadratures, interpolation, filter design, etc. The significance of PSWFs and, in particular, of the decay rate of the eigenvalues of the associated integral operator, was realized at least half a century ago. Nevertheless, perhaps surprisingly, despite vast numerical experience and existence of several asymptotic expansions, a non-trivial explicit upper bound on the magnitude of the eigenvalues has been missing for decades. The principal goal of this paper is to close this gap in the theory of PSWFs. We analyze the integral operator associated with PSWFs, to derive fairly tight non-asymptotic upper bounds on the magnitude of its eigenvalues. Our results are illustrated via several numerical experiments.

Andrei Osipov

Prolate spheroidal wave functions (PSWFs) play an important role in various areas, from physics (e.g. wave phenomena, fluid dynamics) to engineering (e.g. signal processing, filter design). Even though the significance of PSWFs was realized at least half a century ago, and they frequently occur in applications, their analytical properties have not been investigated as much as those of many other special functions. In particular, despite some recent progress, the gap between asymptotic expansions and numerical experience, on the one hand, and rigorously proven explicit bounds and estimates, on the other hand, is still rather wide. This paper attempts to improve the current situation. We analyze the differential operator associated with PSWFs, to derive fairly tight estimates on its eigenvalues. By combining these inequalities with a number of standard techniques, we also obtain several other properties of the PSFWs. The results are illustrated via numerical experiments.

Andrei Osipov

Evaluation of the eigenvectors of symmetric tridiagonal matrices is one of the most basic tasks in numerical linear algebra. It is a widely known fact that, in the case of well separated eigenvalues, the eigenvectors can be evaluated with high relative accuracy. Nevertheless, in general, each coordinate of the eigenvector is evaluated with only high $absolute$ accuracy. In particular, those coordinates whose magnitude is below the machine precision are not expected to be evaluated with any accuracy whatsoever. It turns out that, under certain conditions, frequently ecountered in applications, small (e.g. $10^{-50}$) coordinates of eigenvectors of symmetric tridiagonal matrices can be evaluated with high $relative$ accuracy. In this paper, we investigate such conditions, carry out the analysis, and describe the resulting numerical schemes. While our schemes can be viewed as a modification of already existing (and well known) numerical algorithms, the related error analysis appears to be new. Our results are illustrated via several numerical examples.