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Linear rigidity of stationary stochastic processes

Published online by Cambridge University Press:  03 April 2017

ALEXANDER I. BUFETOV
Affiliation:
Aix-Marseille Université, Centrale Marseille, CNRS, I2M, UMR7373, 39 rue F. Joliot Curie, 13453 Marseille Cedex 13, France email [email protected] Steklov Institute of Mathematics, 8 Gubkina Street, Moscow, 119991, Russia Institute for Information Transmission Problems, Bolshoy Karetny per. 19, 127994, Moscow, Russia National Research University Higher School of Economics, Myasnitskaya ul., 20, Moscow, 101000, Russia email [email protected]
YOANN DABROWSKI
Affiliation:
Université de Lyon, Université Lyon 1, Institut Camille Jordan, 43 bd. du 11 novembre 1918, 69622 Villeurbanne Cedex, France email [email protected]
YANQI QIU
Affiliation:
Aix-Marseille Université, Centrale Marseille, CNRS, I2M, UMR7373, 39 rue F. Joliot Curie, 13453 Marseille Cedex 13, France email [email protected]

Abstract

We consider stationary stochastic processes $\{X_{n}:n\in \mathbb{Z}\}$ such that $X_{0}$ lies in the closed linear span of $\{X_{n}:n\neq 0\}$; following Ghosh and Peres, we call such processes linearly rigid. Using a criterion of Kolmogorov, we show that it suffices, for a stationary stochastic process to be linearly rigid, that the spectral density vanishes at zero and belongs to the Zygmund class $\unicode[STIX]{x1D6EC}_{\ast }(1)$. We next give a sufficient condition for stationary determinantal point processes on $\mathbb{Z}$ and on $\mathbb{R}$ to be linearly rigid. Finally, we show that the determinantal point process on $\mathbb{R}^{2}$ induced by a tensor square of Dyson sine kernels is not linearly rigid.

Type
Original Article
Copyright
© Cambridge University Press, 2017 

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