Uncountably many maximizing measures for a dense subset of continuous functions
Uncountably many maximizing measures for a dense subset of continuous functions
复制标题
连续函数密集子集的无数个最大化测度
DOI:
10.1088/1361-6544/aaaf47
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发表时间:
2018
期刊:
影响因子:
1.7
通讯作者:
M. Shinoda
中科院分区:
文献类型:
--
作者:
宮路智行;小川知之;関坂歩幹;M. Shinoda
Ergodic optimization aims to single out dynamically invariant Borel probability measures which maximize the integral of a given'performance'function. For a continuous self-map of a compact metric space and a dense set of continuous functions, we show the existence of uncountably many ergodic maximizing measures. We also show that, for a topologically mixing subshift of finite type and a dense set of continuous functions there exist uncountably many ergodic maximizing measures with full support and positive entropy.
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