Criticality in conserved dynamical systems: Experimental observation vs. exact properties

TL;DR

This paper investigates conserved dynamical systems, revealing that while they are inherently critical, their observed properties under stochastic sampling often exhibit power-law scaling rather than true scale invariance.

Contribution

The study provides a rigorous analysis of critical routing models, highlighting the difference between intrinsic properties and observed behavior under stochastic sampling.

Findings

Log corrections to power-law scaling for cycle lengths in complete graphs.

Sub-polynomial growth in the total number of cycles.

Power-law scaling of attractor lengths when sampled randomly.

Abstract

Conserved dynamical systems are generally considered to be critical. We study a class of critical routing models, equivalent to random maps, which can be solved rigorously in the thermodynamic limit. The information flow is conserved for these routing models and governed by cyclic attractors. We consider two classes of information flow, Markovian routing without memory and vertex routing involving a one-step routing memory. Investigating the respective cycle length distributions for complete graphs we find log corrections to power-law scaling for the mean cycle length, as a function of the number of vertices, and a sub-polynomial growth for the overall number of cycles. When observing experimentally a real-world dynamical system one normally samples stochastically its phase space. The number and the length of the attractors are then weighted by the size of their respective basins of attraction. This situation is equivalent to `on the fly' generation of routing tables for which we find power law scaling for the weighted average length of attractors, for both conserved routing models. These results show that critical dynamical systems are generically not scale-invariant, but may show power-law scaling when sampled stochastically. It is hence important to distinguish between intrinsic properties of a critical dynamical system and its behavior that one would observe when randomly probing its phase space.