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Generalized Bounded Variation and Inserting point masses

Abstract

Let dμd\mu be a probability measure on the unit circle and dνd\nu be the measure formed by adding a pure point to dμd\mu. We give a simple formula for the Verblunsky coefficients of dνd\nu based on a result of Simon. Then we consider dμ0d\mu_0, a probability measure on the unit circle with 2\ell^2 Verblunsky coefficients (αn(dμ0))n=0(\alpha_n (d\mu_0))_{n=0}^{\infty} of bounded variation. We insert mm pure points to dμd\mu, rescale, and form the probability measure dμmd\mu_m. We use the formula above to prove that the Verblunsky coefficients of dμmd\mu_m are in the form \alpha_n(d\mu_0) + \sum_{j=1}^m \frac{\ol{z_j}^{n} c_j}{n} + E_n, where the cjc_j's are constants of norm 1 independent of the weights of the pure points and independent of nn; the error term EnE_n is in the order of o(1/n)o(1/n). Furthermore, we prove that dμmd\mu_m is of (m+1)(m+1)-generalized bounded variation - a notion that we shall introduce in the paper. Then we use this fact to prove that \lim_{n \to \infty} \vp_n^*(z, d\mu_m) is continuous and is equal to D(z,dμm)1D(z, d\mu_m)^{-1} away from the pure points.Comment: To appear in Constructive Approximatio

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