On shrinking targets for linear expanding and hyperbolic toral endomorphisms

Abstract Let be an invertible matrix with integer elements. Then determines a self‐map of the ‐dimensional torus . Given a real number , and a sequence of points in , let be the set of points such that for infinitely many . The Hausdorff dimension of has previously been studied by Hill–Velani and Li–Liao–Velani–Zorin. We provide a lower bound on the Hausdorff dimension of for any expanding matrix. For hyperbolic matrices, we compute the dimension of only when is a matrix. We give counterexamples to a natural candidate for a dimension formula for general dimension .

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Publication Details

Journal
Journal of the London Mathematical Society
Published
2025-09-01
DOI
https://doi.org/10.1112/jlms.70287
Citations
1
Primary Topic
Mathematical Dynamics and Fractals
Type
article
Field-Weighted Citation Impact
3.69
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article

On shrinking targets for linear expanding and hyperbolic toral endomorphisms

Zhang‐nan Hu, Wanlou Wu, Yiwei Zhang, Tomas Persson
1 citations
Journal of the London Mathematical Society
Mathematical Dynamics and Fractals
3.69
article

On shrinking targets for linear expanding and hyperbolic toral endomorphisms

Zhang‐nan Hu, Wanlou Wu, Yiwei Zhang, Tomas Persson
article en
1 citations

Abstract

Abstract Let be an invertible matrix with integer elements. Then determines a self‐map of the ‐dimensional torus . Given a real number , and a sequence of points in , let be the set of points such that for infinitely many . The Hausdorff dimension of has previously been studied by Hill–Velani and Li–Liao–Velani–Zorin. We provide a lower bound on the Hausdorff dimension of for any expanding matrix. For hyperbolic matrices, we compute the dimension of only when is a matrix. We give counterexamples to a natural candidate for a dimension formula for general dimension .

Journal of the London Mathematical SocietyVol. 112(3)
Jiangsu Normal University (CN), Statistics Sweden (SE), Anhui University of Science and Technology (CN), Lund University (SE), China University of Petroleum, Beijing (CN)
Openalex Percentile: Top 7%
Mathematical Dynamics and Fractals
3.69
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