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We recall our approach through discretizations for path integrals and its general results for representations of probability densities. It is shown that the result of Arnold [P. Arnold, Phys. Rev. E 61, 6099 (2000)] is a particular case of our work.

It results from recent works of Prigogine and collaborators that one can construct a nonunitary operator which realizes an “equivalence” between the positive actions of a reversible dynamical system and an irreversible Markov process going to equilibrium. We consider here this construction and we prove that (a) forK-shifts the transition probability of the associated Markov process is concentrated in the stable manifold of the transformed point by the shift with a point mass concentrated on the deterministic trajectory; and (b) for Bernoulli shifts the measures which go to equilibrium are the same for the deterministic system and the Markov process.

We study a method proposed recently that gives a unified view of the properties of stochastic fields determined by Langevin-type equations. The functional integrals involved are shown to need an additional prescription to be defined, this prescription being related to the relative order of noncommuting operators in the corresponding operator formalism which we characterize in detail. It is proved that the prescription is responsible for an additional term which has given rise to difficulties of interpretation in the Onsager-Machlup path probability density. We prove that all results are independent of this term. In particular in perturbation theory the cancellation mechanism of the prescription dependence is studied in detail.

We derive a new global characterization of the normal forms of amplitude equations describing the dynamics of competing order parameters in degenerate bifurcation problems. Using an appropriate scalar product in the space of homogeneous vector polynomials, we show that the resonant terms commute with the group generated by the adjoint of the original critical linear operator. This leads to a very efficient constructive method to compute both the nonlinear coefficients and the unfolding of the normal form. Explicit examples, and results obtained when there are additional symmetries, are also presented.

The Lagrangian which determines the most probable path for diffusion processes is obtained by a simple and intuitive technique based entirely on the use of path integrals.

We show how to compute in a covariant way the WKB-type expansion for the transition probability density of the Markovian processes generated by general multiplicative noise Langevin equations. The method uses phase space functional integrals and normal coordinates around the classical path. We compare with our earlier non-covariant methods and compute explicitly the first order correction to the WKB-approximation.

The steepest descent approximation is used in the functional integral representation of the solution of the Fokker-Planck equation. The calculation includes the Gaussian integrals of fluctuations around the classical solution. The problem of the prescription dependence of the functional integral is solved previously by transforming the representation to one involving a prescription independent functional integral.

A short derivation of the Feynman Lagrangian for general diffusion processes is given by a technique relying on the use of different discretisations which are related by equivalence relations under the n-dimensional integral whose limit is the path integral. In this way calculation of the differential equation satisfied by the path integral is avoided.

We study functional integral representations for the transition probability density of Markov processes defined by general nonlinear Langevin equations. We give a review of our work covering the definition through discretization, the relation to ordering problems in the operator formalism and the ambiguities of perturbation expansions. We also derive the functional integral representations directly from the stochastic differential equation without using an operator formalism.

Polynomial expansions for potentials of Markov processes describing macroscopic systems are discusssed together with conditions for their existence. We consider local expansions near instabilities and study two general situations where a complete analysis can be done.