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We propose a data-driven method to learn the time-dependent probability density of a multivariate stochastic process from sample paths, assuming that the initial probability density is known and can be evaluated. Our method uses a novel…

Machine Learning · Statistics 2025-06-19 Agnimitra Dasgupta , Javier Murgoitio-Esandi , Ali Fardisi , Assad A Oberai

We propose a method to construct the stochastic integral simultaneously under a non-dominated family of probability measures. Path-by-path, and without referring to a probability measure, we construct a sequence of Lebesgue-Stieltjes…

Probability · Mathematics 2012-06-21 Marcel Nutz

We to define a Path Integral in Lorentzian time by restricting the relevant domain of integration on $C([0,1],M)$ over a Riemannian configuration manifold $(M,g)$ and considering the dynamics of a particle evolving between to fixed…

Probability · Mathematics 2026-01-13 Timur Obolenskiy

Stochastic mechanics---the study of classical stochastic systems governed by things like master equations and Fokker-Planck equations---exhibits striking mathematical parallels to quantum mechanics. In this article, we make those parallels…

Statistical Mechanics · Physics 2019-10-01 John J. Vastola , William R. Holmes

We review some of the techniques used to study the dynamics of disordered systems subject to both quenched and fast (thermal) noise. Starting from the Martin-Siggia-Rose path integral formalism for a single variable stochastic dynamics, we…

Disordered Systems and Neural Networks · Physics 2017-01-26 John A. Hertz , Yasser Roudi , Peter Sollich

The path probability of a particle undergoing stochastic motion is studied by the use of functional technique, and the general formula is derived for the path probability distribution functional. The probability of finding paths inside a…

Statistical Mechanics · Physics 2016-02-16 Masayuki Hattori , Sumiyoshi Abe

A discrete formulation of the real-time path integral as the expectation value of a functional of paths with respect to a complex probability on a sample space of discrete valued paths is explored. The formulation in terms of complex…

Quantum Physics · Physics 2024-06-06 Wayne Polyzou

We review the analytical methods of solving the stochastic equations for barrier-type dynamical behavior in plasma systems. The path-integral approach is examined as a particularly efficient method of determination of the statistical…

Plasma Physics · Physics 2007-05-23 F. Spineanu , M. Vlad , K. Itoh , S. -I. Itoh

We derive a stochastic path integral representation of counting statistics in semi-classical systems. The formalism is introduced on the simple case of a single chaotic cavity with two quantum point contacts, and then further generalized to…

Mesoscale and Nanoscale Physics · Physics 2009-11-07 S. Pilgram , A. N. Jordan , E. V. Sukhorukov , M. Buttiker

We propose an algebraic method for proving estimates on moments of stochastic integrals. The method uses qualitative properties of roots of algebraic polynomials from certain general classes. As an application, we give a new proof of a…

Probability · Mathematics 2013-12-02 Mikhail A. Langovoy

Introducing a perturbative definition, phase space path integrals can be calculated without slicing. This leads to a short-time expansion of the quantum-mechanical path amplitude, or a high-temperature expansion of the unnormalized density…

Quantum Physics · Physics 2011-07-05 Michael Bachmann

We propose a formalism to analyze discrete stochastic processes with finite-state-level N. By using an (N+1)-dimensional representation of su(2) Lie algebra, we re-express the master equation to a time-evolution equation for the state…

Statistical Mechanics · Physics 2015-10-27 Takashi Arai

We demonstrate that parastatistics can be quantized using path integrals by calculating the generating functionals for time-ordered products of both free and interacting parabose and parafermi fields in terms of path integrals. We also give…

Mathematical Physics · Physics 2011-08-12 O. W. Greenberg , A. K. Mishra

The technique of stochastic solutions, previously used for deterministic equations, is here proposed as a solution method for partial differential equations driven by distribution-valued noises.

Probability · Mathematics 2024-08-22 R. Vilela Mendes

We address the calculation of transition probabilities in multiplicative noise stochastic differential equations using a path integral approach. We show the equivalence between the conditional probability and the propagator of a quantum…

Statistical Mechanics · Physics 2019-03-27 Miguel V. Moreno , Daniel G. Barci , Zochil González Arenas

Stochastic models are often used to help understand the behavior of intracellular biochemical processes. The most common such models are continuous time Markov chains (CTMCs). Parametric sensitivities, which are derivatives of expectations…

Numerical Analysis · Mathematics 2014-11-19 Elizabeth Skubak Wolf , David F. Anderson

Several different methods exist for efficient approximation of paths in multiscale stochastic chemical systems. Another approach is to use bursts of stochastic simulation to estimate the parameters of a stochastic differential equation…

Numerical Analysis · Mathematics 2014-12-19 Simon Cotter , Radek Erban

We formulate Bayesian updates in Markov processes by means of path integral techniques and derive the imaginary-time Schr\"{o}dinger equation with likelihood to direct the inference incorporated as a potential for the posterior probability…

Statistics Theory · Mathematics 2017-10-24 Toshiyuki Fujii , Noriyuki Hatakenaka

The semiclassical approximation of the worldline path integral is a powerful tool to study nonperturbative electron-positron pair creation in spacetime-dependent background fields. Finding solutions of the classical equations of motion,…

High Energy Physics - Theory · Physics 2018-10-17 Christian Schneider , Greger Torgrimsson , Ralf Schützhold

These lectures are intended as an introduction to the technique of path integrals and their applications in physics. The audience is mainly first-year graduate students, and it is assumed that the reader has a good foundation in quantum…

Quantum Physics · Physics 2007-05-23 Richard MacKenzie