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We study analytically and numerically the problem of a nonlinear mechanical oscillator with additive noise in the absence of damping. We show that the amplitude, the velocity and the energy of the oscillator grow algebraically with time.…

Statistical Mechanics · Physics 2009-11-07 K. Mallick , P. Marcq

We propose a natural, parameter-free, discrete-variable formulation of Feynman path integrals. We show that for discrete-variable quantum systems, Feynman path integrals take the form of walks on the graph whose weighted adjacency matrix is…

Quantum Physics · Physics 2025-12-08 Amir Kalev , Itay Hen

Systems living in complex non equilibrated environments often exhibit subdiffusion characterized by a sublinear power-law scaling of the mean square displacement. One of the most common models to describe such subdiffusive dynamics is the…

Statistical Mechanics · Physics 2015-07-03 Andrea Cairoli , Adrian Baule

We present recent results on noise-induced transitions in a nonlinear oscillator with randomly modulated frequency. The presence of stochastic perturbations drastically alters the dynamical behaviour of the oscillator: noise can wash out a…

Chaotic Dynamics · Physics 2009-11-13 Sebastien Aumaitre , Francois Petrelis , Kirone Mallick

In this paper we show that stationary and non-stationary multivariate continuous-time ARMA (MCARMA) processes have the representation as a sum of multivariate complex-valued Ornstein-Uhlenbeck processes under some mild assumptions. The…

Statistics Theory · Mathematics 2021-02-24 Vicky Fasen-Hartmann , Markus Scholz

This paper studies Langevin equation with random damping due to multiplicative noise and its solution. Two types of multiplicative noise, namely the dichotomous noise and fractional Gaussian noise are considered. Their solutions are…

Statistical Mechanics · Physics 2017-11-30 Chai Hok Eab , S. C. Lim

We introduce modifications to Monte Carlo simulations of the Feynman path integral that improve sampling of localised interactions. The new algorithms generate trajectories in simple background potentials designed to concentrate them about…

Quantum Physics · Physics 2025-08-06 Ivan Ahumada , James P. Edwards

Langevin simulation provides an effective way to study collisional effects in beams by reducing the six-dimensional Fokker-Planck equation to a group of stochastic ordinary differential equations. These resulting equations usually have…

Accelerator Physics · Physics 2007-05-23 Ji Qiang , Salman Habib

We describe spatio-temporal random processes using linear mixed models. We show how many commonly used models can be viewed as special cases of this general framework and pay close attention to models with separable or product-sum…

Methodology · Statistics 2021-06-01 Michael Dumelle , Jay M. Ver Hoef , Claudio Fuentes , Alix Gitelman

Pre-asymptotic transport of a scalar quantity passively advected by a velocity field formed by a large-scale component superimposed to a small-scale fluctuation is investigated both analytically and by means of numerical simulations.…

Chaotic Dynamics · Physics 2007-05-23 A. Mazzino , S. Musacchio , A. Vulpiani

We consider the solution of a stochastic differential equation with additive multidimensional fractional noise. In the case $\frac14<H<\frac12$, we compute the Onsager-Machlup functional (with respect to the driving fractional Brownian…

Probability · Mathematics 2017-05-26 Yohaï Maayan

We study Langevin dynamics with stochastic diffusivity arising from fluctuations of the surrounding medium. The diffusivity is modeled as Ornstein-Uhlenbeck process driven by symmetric dichotomous noise, which confines it to a finite…

Statistical Mechanics · Physics 2026-04-14 Dongho Lee , Jae-Hyung Jeon , Pascal Viot , Gleb Oshanin

For a model nonlinear dynamical system, we show how one may obtain its bifurcation behavior by introducing noise into the dynamics and then studying the resulting Langevin dynamics in the weak-noise limit. A suitable quantity to capture the…

Adaptation and Self-Organizing Systems · Physics 2019-02-06 Debraj Das , Sayan Roy , Shamik Gupta

The derivation of path integrals is reconsidered. It is shown that the expression for the discretized action is not unique, and the path integration domain can be deformed so that at least Gaussian path integrals become probabillistic. This…

Quantum Physics · Physics 2016-10-28 Evgeny A. Polyakov , Alexey N. Rubtsov

We introduce a Markov Chain Monte Carlo (MCMC) algorithm that dramatically accelerates the simulation of quantum many-body systems, a grand challenge in computational science. State-of-the-art methods for these problems are severely limited…

Strongly Correlated Electrons · Physics 2025-10-17 Deqian Kong , Shi Feng , Jianwen Xie , Ying Nian Wu

This paper studies the fundamental problem of learning deep generative models that consist of multiple layers of latent variables organized in top-down architectures. Such models have high expressivity and allow for learning hierarchical…

Machine Learning · Statistics 2020-07-21 Erik Nijkamp , Bo Pang , Tian Han , Linqi Zhou , Song-Chun Zhu , Ying Nian Wu

We construct path integral representations for the evolution operator of q-oscillators with root of unity values of q-parameter using Bargmann-Fock representations with commuting and non-commuting variables, the differential calculi being…

q-alg · Mathematics 2009-10-28 M. Chaichian , A. P. Demichev

We present a numerical path-integral iteration scheme for the low dimensional reduced density matrix of a time-dependent quantum dissipative system. Our approach simultaneously accounts for the combined action of a microscopically modelled…

Quantum Physics · Physics 2016-10-12 A. M. Barth , A. Vagov , V. M. Axt

We consider a simple model of a classical harmonic oscillator coupled to a field. In standard approaches Langevin-type equations for {\it bare} particles are derived from Hamiltonian dynamics. These equations contain memory terms and are…

Statistical Mechanics · Physics 2009-11-07 Sungyun Kim , Gonzalo Ordonez

The Lamperti transform offers a powerful bridge between self-similar processes and stationary dynamics, making it especially useful for analyzing anomalous diffusion models that lack stationary increments. In this paper we examine the…

Probability · Mathematics 2026-01-07 Foad Shokrollahi , Saeed Vahdati
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