Barcode entropy of geodesic flows

We introduce and study the barcode entropy for geodesic flows of closed Riemannian manifolds, which measures the exponential growth rate of the number of not-too-short bars in the Morse-theoretic barcode of the energy functional. We prove that the barcode entropy bounds from below the topological entropy of the geodesic flow and, conversely, bounds from above the topological entropy of any hyperbolic compact invariant set. As a consequence, for Riemannian metrics on surfaces, the barcode entropy is equal to the topological entropy. A key to the proofs and of independent interest is a crossing energy theorem for gradient flow lines of the energy functional.

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Publication Details

Journal
Journal of the European Mathematical Society
Published
2024-12-13
DOI
https://doi.org/10.4171/jems/1572
Citations
4
Primary Topic
Metaheuristic Optimization Algorithms Research
Type
article
Field-Weighted Citation Impact
1.39
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article

Barcode entropy of geodesic flows

Başak Z. Gürel, Viktor L. Ginzburg, Marco Mazzucchelli
4 citations
Journal of the European Mathematical Society
Metaheuristic Optimization Algorithms Research
1.39
article

Barcode entropy of geodesic flows

Başak Z. Gürel, Viktor L. Ginzburg, Marco Mazzucchelli
article en
4 citations

Abstract

We introduce and study the barcode entropy for geodesic flows of closed Riemannian manifolds, which measures the exponential growth rate of the number of not-too-short bars in the Morse-theoretic barcode of the energy functional. We prove that the barcode entropy bounds from below the topological entropy of the geodesic flow and, conversely, bounds from above the topological entropy of any hyperbolic compact invariant set. As a consequence, for Riemannian metrics on surfaces, the barcode entropy is equal to the topological entropy. A key to the proofs and of independent interest is a crossing energy theorem for gradient flow lines of the energy functional.

Journal of the European Mathematical Society
University of Central Florida (US), École Normale Supérieure de Lyon (FR), University of California, Santa Cruz (US)
Affordable and clean energy
Openalex Percentile: Top 15%
Metaheuristic Optimization Algorithms Research
1.39
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