The Shrinking Target Problem for Matrix Transformations of Tori: revisiting the standard problem
Bing Li (SCUT), Lingmin Liao (Wuhan), Sanju Velani (York), Evgeniy, Zorin (York), Baowei Wang (appendix, HUST)

TL;DR
This paper investigates the measure and Hausdorff dimension of shrinking target sets under matrix transformations on tori, providing zero-one laws, quantitative counting, and explicit dimension formulas for various target shapes.
Contribution
It extends classical shrinking target results to real matrices, offers quantitative measure estimates, and derives explicit Hausdorff dimension formulas for different geometric targets.
Findings
Lebesgue measure of target sets is zero or one depending on volume sum convergence.
Provides asymptotic counting function for points hitting targets infinitely often.
Derives explicit Hausdorff dimension formulas for targets shaped as balls, rectangles, or hyperboloids.
Abstract
Let be a matrix with real coefficients. Then determines a self-map of the -dimensional torus . Let be a sequence of subsets of and let be the set of points such that for infinitely many . For a large class of subsets (namely, those satisfying the so called bounded property which includes balls, rectangles, and hyperboloids) we show that the -dimensional Lebesgue measure of the shrinking target set is zero (resp. one) if a natural volume sum converges (resp. diverges). In fact, we prove a quantitative form of this zero-one criteria that describes the asymptotic behaviour of the counting function $R(x,N):= \# \big\{ 1\le n \le N : T^{n}(x) \in E_n \}…
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Taxonomy
TopicsMathematical Dynamics and Fractals · Markov Chains and Monte Carlo Methods · advanced mathematical theories
