Abstract

We explore the effect of different spatially periodic, deterministic forces on the information geometry of stochastic processes. The three forces considered are and , with chosen to be particularly flat (locally cubic) at the equilibrium point , and particularly flat at the unstable fixed point . We numerically solve the Fokker–Planck equation with an initial condition consisting of a periodically repeated Gaussian peak centred at , with in the range . The strength D of the stochastic noise is in the range –. We study the details of how these initial conditions evolve toward the final equilibrium solutions and elucidate the important consequences of the interplay between an initial PDF and a force. For initial positions close to the equilibrium point , the peaks largely maintain their shape while moving. In contrast, for initial positions sufficiently close to the unstable point , there is a tendency for the peak to slump in place and broaden considerably before reconstituting itself at the equilibrium point. A consequence of this is that the information length , the total number of statistically distinguishable states that the system evolves through, is smaller for initial positions closer to the unstable point than for more intermediate values. We find that as a function of initial position is qualitatively similar to the force, including the differences between and , illustrating the value of information length as a useful diagnostic of the underlying force in the system.

Highlights

  • It is of interest to apply the idea of a metric to problems involving stochastic processes, e.g., [1,2,3,4,5,6].Given a metric, the differences between different Probability Density Functions (PDFs) can be quantified, with different metrics focusing on a range of aspects, and most suitable for various applications

  • By extending the statistical distance in [8] to time-dependent situations, we recently introduced a way of quantifying information changes associated with time-varying PDFs [9,10,11,12,13,14,15,16]

  • The results presented here extend our previous work [12,15] to the deterministic forces that are periodic in space

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Summary

Introduction

It is of interest to apply the idea of a metric to problems involving stochastic processes, e.g., [1,2,3,4,5,6].Given a metric, the differences between different Probability Density Functions (PDFs) can be quantified, with different metrics focusing on a range of aspects, and most suitable for various applications. L∞ , the total information length over the entire evolution, is useful to quantify the proximity of any initial PDF to a final attractor of a dynamical system.

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