The dynamical variables $\psi$ of a classical system, undergoing stochastic stirring forces, satisfy equations of motion with noise terms. Hence, these dynamical variables show a stochastic evolution themselves. The probability of each possible realization of $\psi$ within a given time interval, arises from the interplay between the deterministic parts of dynamics and the statistics of noise terms. In this work, we discuss the construction of the stochastic Lagrangian out of the dynamical equations, that is a tool to calculate the realization probabilities of the dynamical variables as path integrals. In this formulation, the study of classical statistical dynamics can benefit from all the techniques developed in Quantum Mechanics of path integrals; moreover, as the path integral is expressed in terms of a Lagrangian, the invariance properties of the system become transparent. After a coincise review of the stochastic Lagrangian formalism, some applications of it to physically relevant cases are illustrated. Then, the advantages and maturity of this approach, and its expected future developments, are outlined.

Stochastic Lagrangians for noisy dynamics

Materassi M
2020

Abstract

The dynamical variables $\psi$ of a classical system, undergoing stochastic stirring forces, satisfy equations of motion with noise terms. Hence, these dynamical variables show a stochastic evolution themselves. The probability of each possible realization of $\psi$ within a given time interval, arises from the interplay between the deterministic parts of dynamics and the statistics of noise terms. In this work, we discuss the construction of the stochastic Lagrangian out of the dynamical equations, that is a tool to calculate the realization probabilities of the dynamical variables as path integrals. In this formulation, the study of classical statistical dynamics can benefit from all the techniques developed in Quantum Mechanics of path integrals; moreover, as the path integral is expressed in terms of a Lagrangian, the invariance properties of the system become transparent. After a coincise review of the stochastic Lagrangian formalism, some applications of it to physically relevant cases are illustrated. Then, the advantages and maturity of this approach, and its expected future developments, are outlined.
2020
Istituto dei Sistemi Complessi - ISC
Functional formalism
Noise
Path integrals
Stochastic dynamics
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/407352
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