Chaotic thermalization in classical gauge theories

Abstract

State-by-state assignment of the bending spectrum of acetylene at 15000 cm1: A case study of quantum-classical correspondence The classical theory of intermittency developed for return maps assumes uniform density of points reinjected from the chaotic to laminar region. Though it works fine in some model systems, there exist a number of so-called pathological cases characterized by a significant deviation of main characteristics from the values predicted on the basis of the uniform distribution. Recently, we reported on how the reinjection probability density (RPD) can be generalized. Here, we extend this methodology and apply it to different dynamical systems exhibiting anomalous type-II and type-III intermittencies. Estimation of the universal RPD is based on fitting a linear function to experimental data and requires no a priori knowledge on the dynamical model behind. We provide special fitting procedure that enables robust estimation of the RPD from relatively short data sets (dozens of points). Thus, the method is applicable for a wide variety of data sets including numerical simulations and real-life experiments. Estimated RPD enables analytic evaluation of the length of the laminar phase of intermittent behaviors. We show that the method copes well with dynamical systems exhibiting significantly different statistics reported in the literature. We also derive and classify characteristic relations between the mean laminar length and main controlling parameter in perfect agreement with data provided by numerical simulations. V C 2013 AIP Publishing LLC. Intermittency is a particular route to the deterministic chaos characterized by spontaneous transitions between laminar and chaotic dynamics. It is observed in a variety of different dynamical systems in Physics, Neuroscience, and Economics. Frequently, there is no feasible mathematical model for the process under study. Then reliable quantification of main characteristics of the intermittent process (e.g., the length of laminar phase) from experimental data is a challenging problem. The classical theory of intermittency has significant pitfalls. Though it works fine in some model systems, there exist a number of so-called pathological cases that deviate significantly from the classical predictions. In this work, we address the problem of unification of anomalous and standard intermittencies under single framework. The unified model can be fitted to experimental or numerical data. We note that to accomplish this step no a priori knowledge is required. We propose a procedure that can cope with reduced data sets consisting of several dozens of points. This makes our methodology useful for real-life applications. Using the experimentally obtained measures , we can classify intermittent processes into different theoretical types. We thoroughly test our method on two particular but canonical cases of intermittency.