Étant donné un opérateur agissant sur un espace de Banach , nous étudions l’existence d’une mesure de probabilité sur telle que, pour de nombreuses fonctions , la suite converge en loi vers une variable aléatoire gaussienne.
Given a bounded operator on a Banach space , we study the existence of a probability measure on such that, for many functions , the sequence converges in distribution to a Gaussian random variable.
@article{AIHPB_2015__51_3_1131_0, author = {Bayart, Fr\'ed\'eric}, title = {Central limit theorems in linear dynamics}, journal = {Annales de l'I.H.P. Probabilit\'es et statistiques}, volume = {51}, year = {2015}, pages = {1131-1158}, doi = {10.1214/13-AIHP585}, mrnumber = {3365976}, language = {en}, url = {http://dml.mathdoc.fr/item/AIHPB_2015__51_3_1131_0} }
Bayart, Frédéric. Central limit theorems in linear dynamics. Annales de l'I.H.P. Probabilités et statistiques, Tome 51 (2015) pp. 1131-1158. doi : 10.1214/13-AIHP585. http://gdmltest.u-ga.fr/item/AIHPB_2015__51_3_1131_0/
[1] Frequently hypercyclic operators. Trans. Amer. Math. Soc. 358 (11) (2006) 5083–5117. | MR 2231886 | Zbl 1115.47005
and .[2] Invariant Gaussian measures for operators on Banach spaces and linear dynamics. Proc. Lond. Math. Soc. 94 (2007) 181–210. | MR 2294994 | Zbl 1115.47006
and .[3] Dynamics of Linear Operators. Cambridge Tracts in Math. 179. Cambridge Univ. Press, Cambridge, 2009. | MR 2533318 | Zbl 1187.47001
and .[4] Mixing operators and small subsets of the circle. J. Reine Angew. Math. To appear, 2015. Available at arXiv:1112.1289.
and .[5] Difference sets and frequently hypercyclic weighted shifts. Ergodic Theory Dynam. Syst. 35 (2015) 691–709. | MR 3334899
and .[6] Théorème central limite pour les endomorphismes holomorphes et les correspondances modulaires. Int. Math. Res. Not. 56 (2005) 3479–3510. | MR 2200586 | Zbl 1094.37004
and .[7] Limit theorems and Markov approximations for chaotic dynamical systems. Probab. Theory Related Fields 101 (1995) 321–362. | MR 1324089 | Zbl 0839.60025
.[8] Strongly mixing operators on Hilbert spaces and speed of mixing. Proc. Lond. Math. Soc. 106 (2013) 1394–1434. | MR 3072286 | Zbl 1275.37004
.[9] Decay of correlations and central limit theorem for meromorphic maps. Comm. Pure Appl. Math. 59 (2006) 754–768. | MR 2172806 | Zbl 1137.37023
and .[10] Bernoulli coding map and almost-sure invariance principle for endomorphisms of . Probab. Theory Related Fields 146 (2010) 337–359. | MR 2574731 | Zbl 1244.37028
.[11] Unimodular eigenvalues and linear chaos in Hilbert spaces. Geom. Funct. Anal. 5 (1995) 1–13. | MR 1312018 | Zbl 0827.46043
.[12] Linear Chaos. Springer, Berlin, 2011. | MR 2919812 | Zbl 1246.47004
and .[13] The central limit theorem for stationary processes. Soviet Math. Dokl. 10 (1969) 1174–1176. | MR 251785 | Zbl 0212.50005
.[14] Limit theorems for non-hyperbolic automorphisms of the torus. Israel J. Math. 109 (1999) 61–73. | MR 1679589 | Zbl 0989.37001
.[15] Central limit theorem for deterministic systems. In International Conference on Dynamical Systems (Montevideo, 1995). Pitman Res. Notes Math. Ser. 362 56–75. Longman, Harlow, 1996. | MR 1460797 | Zbl 0871.58055
.[16] Strong mixing measures for linear operators and frequent hypercyclicity. J. Math. Anal. Appl. 398 (2013) 462–465. | MR 2990071 | Zbl 1288.47009
and .[17] Central limit theorems for additive functionals of Markov chains. Ann. Probab. 28 (2000) 713–724. | MR 1782272 | Zbl 1044.60014
and .[18] Strong ergodic properties of a first-order partial differential equation. J. Math. Anal. Appl. 133 (1988) 14–26. | MR 949314 | Zbl 0673.35012
.[19] Gaussian measure-preserving linear transformations. Univ. Iagel. Acta Math. 30 (1993) 105–112. | MR 1233772 | Zbl 0836.28005
.[20] Chaos for some infinite-dimensional dynamical systems. Math. Methods Appl. Sci. 27 (2004) 723–738. | MR 2070224 | Zbl 1156.37322
.[21] On limit theorems and category for dynamical systems. Yokohama Math. J. 38 (1990) 29–35. | MR 1093661 | Zbl 0735.60025
.[22] Martingale approximation of non adapted stochastic processes with nonlinear growth of variance. In Dependence in Probability and Statistics. Lecture Notes in Statistics 187 141–156. Springer, Berlin, 2006. | MR 2283254 | Zbl 1111.60016
.