Laguerre-Sobolev orthogonal Polynomials and Boundary Value Problems on a semi-infinite domain
Cleonice F. Bracciali, Miguel A. Piñar
TL;DR
This work addresses solving Schrödinger-type boundary value problems on the half-line $(0,+\infty)$ with a singular potential $V(x)=1/x$ by developing Laguerre-Sobolev polynomials associated with a Sobolev inner product. It builds a diagonalized spectral method by expanding the solution in the basis $\{S_n(x) x e^{-x/2}\}$, using explicit connection formulas to classical Laguerre polynomials, and a generating function involving $J_1$ to derive recurrence for the coefficients. The paper derives asymptotics for the connection coefficients, provides explicit formulas for $a_n$ and a practical recurrence, and demonstrates how to implement the diagonalized solver without linear systems. Numerical experiments with Schrödinger-type equations confirm spectral accuracy and exponential convergence for decaying solutions, while highlighting limitations for non-decaying cases, validating the approach for singular half-line problems.
Abstract
We study a family of Laguerre--Sobolev orthogonal polynomials associated with a Sobolev inner product arising from second--order boundary value problems on the semi--infinite interval $(0,+\infty)$. These polynomials generate an orthogonal basis of test functions vanishing at the endpoints and are especially well suited for the spectral approximation of Schrödinger--type problems with singular potentials. Explicit connection formulas with classical Laguerre polynomials are obtained, together with recurrence relations and asymptotic properties of the corresponding coefficients. A generating function involving Bessel functions is also derived. As an application, we develop a fully diagonalized Laguerre--Sobolev spectral method for Dirichlet problems with singular potentials. The method avoids the solution of linear systems and can be implemented recursively. Numerical experiments for a Schrödinger--type equation with inverse--distance potential confirm spectral accuracy and exponential convergence.
