Mollified Christoffel-Darboux Kernels and Density Recovery on Varieties

TL;DR

This paper develops mollified Christoffel-Darboux kernels on varieties to improve density recovery from moments, providing uniform bounds inside support and exponential growth outside, with explicit convergence rates.

Contribution

It introduces a systematic regularization of CD kernels on varieties, enabling better density recovery without needing the equilibrium measure, and derives explicit convergence rates.

Findings

Mollified CD kernels are uniformly bounded inside support.

Outside support, mollified CD kernels grow exponentially with degree.

Explicit convergence rates for density recovery are established.

Abstract

We introduce mollified Christoffel-Darboux (CD) kernels on varieties, a systematic regularization of the classical CD kernel associated with a probability measure on a compact domain. The main motivations are twofold: first, to sharpen the classical on/off-support dichotomy of the CD polynomial by replacing linear growth on the support by a uniform bound; second, to obtain consistent and quantitatively controlled recovery of densities from moment data, without the need to know the equilibrium measure of the underlying domain. Our contributions are the following: (i) We introduce families of mollifiers on algebraic varieties. For each measure and degree on such a variety we define a mollified CD kernel, which can be computed from the moments of the underlying measure by linear algebra. (ii) We prove, by elementary arguments, that an improved dichotomy property holds: on the interior of the support the mollified CD polynomial is uniformly bounded in the degree, while outside the support it grows exponentially with the degree. (iii) Assuming Sobolev regularity of the density with respect to a reference measure, we derive explicit convergence rates for density recovery for measures in Euclidean space via mollified CD kernel. (iv) On the unit sphere, we show that suitably chosen algebraic mollifiers, constructed from zonal polynomials, lead to kernels with improved rates, building on classical constructive approximation results.