Understanding scaling through history-dependent processes with collapsing sample space

  title={Understanding scaling through history-dependent processes with collapsing sample space},
  author={Bernat Corominas-Murtra and Rudolf Hanel and Stefan Thurner},
  journal={Proceedings of the National Academy of Sciences},
  pages={5348 - 5353}
Significance Many complex systems reduce their flexibility over time in the sense that the number of options (possible states) diminishes over time. We show that rank distributions of the visits to these states that emerge from such processes are exact power laws with an exponent −1 (Zipf’s law). When noise is added to such processes, meaning that from time to time they can also increase the number of their options, the rank distribution remains a power law, with an exponent that is related to… 

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