Polynomial Approximation in $ L^2 $ of the Double Exponential via Complex Analysis

TL;DR

This paper establishes a tight inequality for polynomial approximation in L^2 space with a specific exponential weight, revealing the rate of approximation and extending results to higher dimensions using complex analysis.

Contribution

It provides a new, tight inequality for polynomial approximation in L^2 with exponential weights and extends approximation rates to higher dimensions via tensorization.

Findings

Proves a tight inequality involving orthonormal polynomials and logarithmic weights.

Derives approximation rates for functions in L^2 with exponential decay.

Extends approximation results to product measures in higher dimensions.

Abstract

We study the polynomial approximation problem in $L^2(\mu_1)$ where $\mu_1(dx) = e^{-|x|}/2 dx$. We show that for any absolutely continuous function $f$, $$ \sum_{k=1}^{\infty} \log^2(e+k) \langle f, P_k \rangle^2 \ \leq C \left( \int_{\mathbb{R}} \log^2(e+\lvert x \rvert) f^2 \, d\mu_1 \ + \ \int_{\mathbb{R}} (f')^2 \, d\mu_1 \right) $$ for some universal constant $C>0$, where $(P_k)_{k \in N}$ are the orthonormal polynomials associated with $\mu_1$. This inequality is tight in the sense that $\log^2(e +k)$ on the left hand-side cannot be replaced by $a_k \log^2(e +k)$ with a sequence $a_k \longrightarrow \infty$. When the right hand-side is bounded this inequality implies a logarithmic rate of approximation for $f$, which was previously obtained by Lubinsky. We also obtain some rates of approximation for the product measure $\mu_1^{\otimes d}$ in $\mathbb{R}^d$ via a tensorization argument. Our proof relies on an explicit formula for the generating function of orthonormal polynomials associated with the weight $\frac{1}{2\cosh(\pi x/2)}$ and some complex analysis.