Generalized dynamical entropies in weakly chaotic systems
By H. Beijeren. 2003
6 citations recorded by the source corpus.
A large class of technically non-chaotic systems, involving scatterings of light particles by flat surfaces with sharp boundaries, is nonetheless characterized by complex random looking motion in phase space. For these systems one may define a generalized, Tsallis-type dynamical entropy that increases linearly with time. It characterizes a maximal gain of information about the system that increases as a power of time. However, this entropy cannot be chosen independently from the choice of coarse-graining lengths and it assigns positive dynamical entropies also to fully integrable systems. By considering these dependencies in detail one usually will be able to distinguish weakly chaotic from fully integrable systems.
Subfields: Statistical and Nonlinear Physics
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In Statistical and Nonlinear Physics
- Yutian Chen
- Max Welling
- Feng Zhu
- Jiangpeng He
- Jure Leskovec
- L. Eon Bottou
- William L. Hamilton
- Jun Zhu
Citations in the corpus
- Statistical inference using weak chaos and infinite memory (2010, methodology): “By demanding that the Tsallis entropy grows linearly in time (Tsallis et al., 2006; van Beijeren, 2004) we can compute the exponent q.”