TY - BOOK ID - 14224565 TI - Phenomenological Structure for the Large Deviation Principle in Time-Series Statistics : A method to control the rare events in non-equilibrium systems PY - 2016 SN - 9812878106 9812878114 PB - Singapore : Springer Singapore : Imprint: Springer, DB - UniCat KW - Atomic Physics KW - Physics KW - Physical Sciences & Mathematics KW - Time-series analysis. KW - Large deviations. KW - Deviations, Large KW - Analysis of time series KW - Limit theorems (Probability theory) KW - Statistics KW - Autocorrelation (Statistics) KW - Harmonic analysis KW - Mathematical statistics KW - Probabilities KW - Thermodynamics. KW - Statistical physics. KW - Complex Systems. KW - Mathematical Physics. KW - Statistical Physics and Dynamical Systems. KW - Chemistry, Physical and theoretical KW - Dynamics KW - Mechanics KW - Heat KW - Heat-engines KW - Quantum theory KW - Statistical methods KW - Dynamical systems. KW - Mathematical physics. KW - Physical mathematics KW - Dynamical systems KW - Kinetics KW - Mathematics KW - Mechanics, Analytic KW - Force and energy KW - Statics UR - https://www.unicat.be/uniCat?func=search&query=sysid:14224565 AB - This thesis describes a method to control rare events in non-equilibrium systems by applying physical forces to those systems but without relying on numerical simulation techniques, such as copying rare events. In order to study this method, the book draws on the mathematical structure of equilibrium statistical mechanics, which connects large deviation functions with experimentally measureable thermodynamic functions. Referring to this specific structure as the “phenomenological structure for the large deviation principle”, the author subsequently extends it to time-series statistics that can be used to describe non-equilibrium physics. The book features pedagogical explanations and also shows many open problems to which the proposed method can be applied only to a limited extent. Beyond highlighting these challenging problems as a point of departure, it especially offers an effective means of description for rare events, which could become the next paradigm of non-equilibrium statistical mechanics. ER -