On ergodic least-squares estimators of the generalized diffusion coefficient for fractional Brownian motion

We analyse a class of estimators of the generalized diffusion coefficient for fractional Brownian motion Bt of known Hurst index H, based on weighted functionals of the single time square displacement. We show that for a certain choice of the weight function these functionals possess an ergodic property and thus provide the true, ensemble-averaged, generalized diffusion coefficient to any necessary precision from a single trajectory data, but at expense of a progressively higher experimental resolution. Convergence is fastest around H ? 0.30, a value in the subdiffusive regime.

A derivation of thermodynamic principles

A detailed macroscopic description as in continuum mechanics, and just the concept of microstate,have been used to derive thermodynamics from mechanics. In opposition to statistical physics, the derivation lays emphasis on a definite prescription for macrostates (and non-equilibrium entropy), and uses basic features of the macrostate concept: complementary descriptions, involving either conservative and additive quantities or densities;scale-free character; reference to finite velocities and regions distant in space, thus introducing time indirectly. On the other hand, the derivation keeps the particle substratum (limit of number of particles N taken at fixed densities), and makes no ergodic-type considerations.

Correlation Dimension of Complex Networks

We propose a new measure to characterize the dimension of complex networks based on the ergodic theory of dynamical systems. This measure is derived from the correlation sum of a trajectory generated by a random walker navigating the network, and extends the classical Grassberger-Procaccia algorithm to the context of complex networks. The method is validated with reliable results for both synthetic networks and real-world networks such as the world air-transportation network or urban networks, and provides a computationally fast way for estimating the dimensionality of networks which only relies on the local information provided by the walkers.