A note on “Euclidean algorithms are Gaussian” by V. Baladi and B. Vallée

The paper “Euclidean algorithms are Gaussian” [V. Baladi, B. Vallée, Euclidean algorithm are Gaussian, J. Number Theory 110 (2005) 331–386], is devoted to the distributional analysis of three variants of Euclidean algorithms. The Central Limit Theorem and the Local Limit Theorem obtained there are the first ones in the context of the “dynamical analysis” method. The techniques developed have been applied in further various works (e.g. [V. Baladi, A. Hachemi, A local limit theorem with speed of convergence for Euclidean algorithms and Diophantine costs, Ann. Inst. H. Poincaré Probab. Statist. 44 (2008) 749–770; E. Cesaratto, J. Clément, B. Daireaux, L. Lhote, V. Maume, B. Vallée, Analysis of fast versions of the Euclid algorithm, in: Proceedings of Third Workshop on Analytic Algorithmics and Combinatorics, ANALCO'08, SIAM, 2008; E. Cesaratto, A. Plagne, B. Vallée, On the non-randomness of modular arithmetic progressions, in: Fourth Colloquium on Mathematics and Computer Science. Algorithms, Trees, Combinatorics and Probabilities, in: Discrete Math. Theor. Comput. Sci. Proc., vol. AG, 2006, pp. 271–288]). These theorems are proved first for an auxiliary probabilistic model, called “the smoothed model,” and after, the estimates are transferred to the “true” probabilistic model. In this note, we remark that “the smoothed model” described in [V. Baladi, B. Vallée, Euclidean algorithm are Gaussian, J. Number Theory 110 (2005) 331–386] is not adapted to this transfer and replaces it by an adapted one. However, the results remain unchanged.