2017
DOI: 10.1016/j.jfa.2016.07.009
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On Szegő's theorem for a nonclassical case

Abstract: In this paper we prove Szegő's Theorem for the case when a finite number of Verblunsky coefficients lie outside the closed unit disk. Although a form of this result was already proved by A.L. Sakhnovich, we use a very different method, which shows that the OPUC machinery can still be applied to deal with such nonclassical cases. The basic tool we use is Khrushchev's formula that in the classical case relates the absolutely continuous part of the measure and the N -th iterate of the Schur algorithm. It is notew… Show more

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Cited by 11 publications
(16 citation statements)
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“…To formulate the next result, which is a generalization of [15, Theorem 2.4.1, part (iv)], we should recall from [4] that the zeros of ϕ * n inside D will either tend to the poles of F in D or to the boundary of the unit disk as n → ∞. So, let B n be the Blaschke product formed by the zeroes of ϕ * n inside D, that is…”
Section: The Generalized Szegő Functionmentioning
confidence: 97%
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“…To formulate the next result, which is a generalization of [15, Theorem 2.4.1, part (iv)], we should recall from [4] that the zeros of ϕ * n inside D will either tend to the poles of F in D or to the boundary of the unit disk as n → ∞. So, let B n be the Blaschke product formed by the zeroes of ϕ * n inside D, that is…”
Section: The Generalized Szegő Functionmentioning
confidence: 97%
“…In [4] an analog of Szegő's Theorem was proven in this non-classical setting. The aim of the present paper is to further develop the asymptotic theory of polynomials generated from the Szegő recursion using a sequence satisfying (1.1).…”
Section: Introductionmentioning
confidence: 94%
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“…⊤ , which is proved to be a generalized Nevanlinna function. Remarkably, some nonclassical orthogonal polynomials on the unit disk were introduced in [7] and the Szegő mapping applied to those polynomials leads to tridiagonal matrices that have the same structure as H does [8].…”
Section: The Underlying Jacobi Matricesmentioning
confidence: 99%