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A supersymmetric path integral representation is developed for stochastic processes whose Langevin equation contains any number N of time derivatives, thus generalizing the Langevin equation with inertia studied by Kramers, where N=2. The…

Quantum Physics · Physics 2009-10-30 Hagen Kleinert , Sergei V. Shabanov

We define the time-continuous spin coherent-state path integral in a way that is free from inconsistencies. The proposed definition is used to reproduce known exact results. Such a formalism opens new possibilities for applying…

Other Condensed Matter · Physics 2016-05-24 G. Kordas , D. Kalantzis , A. I. Karanikas

We use a path integral approach for solving the stochastic equations underlying the financial markets, and we show the equivalence between the path integral and the usual SDE and PDE methods. We analyze both the one-dimensional and the…

Statistical Mechanics · Physics 2008-12-10 Marco Rosa-Clot , Stefano Taddei

In this paper we develop a general formalism of a path approach for non-equilibrium statistical mechanics. Firstly, we consider the classical Gibbs approach for states and find that this formalism is ineffective for non-equilibrium…

Statistical Mechanics · Physics 2009-08-24 S. G. Abaimov

By revisiting the path-integral formulation of the Hubbard model, we propose a theoretical approach based on a semiclassical approximation employing an unconventional coherent-state representation. Within this framework, a subset of the…

Strongly Correlated Electrons · Physics 2026-04-06 Yuki Yamasaki , Hidemaro Suwa , Cristian D. Batista , Shintaro Hoshino

We study a stochastic process describing the onset of spreading dynamics of an epidemic in a population composed by individuals of three classes: susceptible (S), infected (I), and recovered (R). The stochastic process is defined by local…

Statistical Mechanics · Physics 2015-05-13 David R. de Souza , Tânia Tomé

We generalize and extend the stochastic path integral formalism and action principle for continuous quantum measurement introduced in [A. Chantasri, J. Dressel and A. N. Jordan, Phys. Rev. A {\bf 88}, 042110 (2013)], where the optimal…

Quantum Physics · Physics 2015-09-23 Areeya Chantasri , Andrew N. Jordan

We introduce a path sampling method for obtaining statistical properties of an arbitrary stochastic dynamics. The method works by decomposing a trajectory in time, estimating the probability of satisfying a progress constraint, modifying…

Statistical Mechanics · Physics 2015-06-04 Nicholas Guttenberg , Aaron R. Dinner , Jonathan Weare

The aim of this paper is to present an elementary computable theory of probability, random variables and stochastic processes. The probability theory is baed on existing approaches using valuations and lower integrals. Various approaches to…

Probability · Mathematics 2015-10-14 Pieter Collins

I review the generating function for quantum-statistical mechanics, known as the Feynman-Vernon influence functional, the decoherence functional, or the Schwinger-Keldysh path integral. I describe a probability-conserving $i\varepsilon$…

High Energy Physics - Theory · Physics 2021-02-10 Yoni BenTov

The manner in which probability amplitudes of paths sum up to form wave functions of a harmonic oscillator, as well as other, simple 1-dimensional problems, is described. Using known, closed-form, path-based propagators for each problem, an…

Quantum Physics · Physics 2025-11-18 Randall M. Feenstra

A continuously measured quantum system with multiple jump channels gives rise to a stochastic process described by random jump times and random emitted symbols, representing each jump channel. While much is known about the waiting time…

Quantum Physics · Physics 2023-06-21 Gabriel T. Landi

We present a functional formalism to derive a generating functional for correlation functions of a multiplicative stochastic process represented by a Langevin equation. We deduce a path integral over a set of fermionic and bosonic variables…

Statistical Mechanics · Physics 2010-05-13 Zochil González Arenas , Daniel G. Barci

In Part 1, we introduced a stochastic model of an infectious disease, based on the BDI (birth and death with immigration) process. We showed that random processes defined by this model can capture the essence of the stochastic, often…

Populations and Evolution · Quantitative Biology 2021-01-28 Hisashi Kobayashi

We develop a geometric representation for the ground state of the spin-1/2 quantum XXZ ferromagnetic chain in terms of suitably weighted random walks in a two-dimensional lattice. The path integral model so obtained admits a genuine…

Mathematical Physics · Physics 2009-10-31 Oscar Bolina , Pierluigi Contucci , Bruno Nachtergaele

We study the application of the coherent-state path integral as a numerical tool for wave-packet propagation. The numerical evaluation of path integrals is reduced to a matrix-vector multiplication scheme. Together with a split-operator…

Quantum Physics · Physics 2007-05-23 Bernd Burghardt , Joachim Stolze

We suggest a generalization of the Feynman path integral to an integral over random surfaces. The proposed action is proportional to the linear size of the random surfaces and is called gonihedric. The convergence and the properties of the…

High Energy Physics - Theory · Physics 2016-12-13 George Savvidy

In this work, we study a protein synthesis degradation process by defining a general mathematical model. Using generating function technique we present a method that allows exact calculation of joint probability distribution of protein…

Quantitative Methods · Quantitative Biology 2013-11-11 Diana David-Rus

The coherent state path integral formulation of certain many particle systems allows for their non perturbative study by the techniques of lattice field theory. In this paper we exploit this strategy by simulating the explicit example of…

Condensed Matter · Physics 2009-10-28 M. Beccaria , B. Alles , F. Farchioni

The complex dynamics of an increasing number of systems is attributed to the emergence of a rugged energy landscape with an exponential number of metastable states. To develop this picture into a predictive dynamical theory I discuss how to…

Disordered Systems and Neural Networks · Physics 2021-09-15 Tommaso Rizzo