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The geodesic dispersion phenomenon in random fields dynamics

2024/01/25 by Alexandre L. M. Levada, Levada, Alexandre L. M.
Earth and Planetary Sciences · #Aeolian processes and effects #Computational Physics (physics.comp-ph) #FOS: Computer and information sciences #FOS: Physical sciences #Geology and Paleoclimatology Research #Information Theory (cs.IT) #Marine and environmental studies #Mathematical Physics (math-ph)

paper · pdf · doi:10.48550/arxiv.2401.14482

openalex publication_date 2024/01/25 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/29

Abstract

Random fields are ubiquitous mathematical structures in physics, with applications ranging from thermodynamics and statistical physics to quantum field theory and cosmology. Recent works on information geometry of Gaussian random fields proposed mathematical expressions for the components of the metric tensor of the underlying parametric space, allowing the computation of the curvature in each point of the manifold. In this study, our hypothesis is that time irreversibility in Gaussian random fields dynamics is a direct consequence of intrinsic geometric properties (curvature) of their parametric space. In order to validate this hypothesis, we compute the components of the metric tensor and derive the twenty seven Christoffel symbols of the metric to define the Euler-Lagrange equations, a system of partial differential equations that are used to build geodesic curves in Riemannian manifolds. After that, by the application of the fourth-order Runge-Kutta method and Markov Chain Monte Carlo simulation, we numerically build geodesic curves starting from an arbitrary initial point in the manifold. The obtained results show that, when the system undergoes phase transitions, the geodesic curve obtained by time reversing the computational simulation diverges from the original curve, showing a strange effect that we called the geodesic dispersion phenomenon, which suggests that time irreversibility in random fields is related to the intrinsic geometry of their parametric space.

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