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Related papers: Non-Markovian Stochastic Resonance

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The theory of nonlinear response for Markov processes obeying a master equation is formulated in terms of time-dependent perturbation theory for the Green's functions and general expressions for the response functions up to third order in…

Soft Condensed Matter · Physics 2015-06-04 Gregor Diezemann

The exact stochastic decomposition of non-Markovian dissipative quantum dynamics is combined with the time-dependent semiclassical initial value formalism. It is shown that even in the challenging regime of moderate friction and low…

Statistical Mechanics · Physics 2011-09-30 Werner Koch , Frank Großmann , Jürgen T. Stockburger , Joachim Ankerhold

The solutions of SDEs with multiplicative noise are not Markovian. On a coarse-grained time scale they still are, but only in the "anti-Ito" case. This allows a simple computation of the most likely path. Any density peak moves along such a…

General Physics · Physics 2021-09-27 Dietrich Ryter

Stochastic resetting describes dynamics which are reinitialized to a reference state at random times. These protocols are attracting significant interest: they can stabilize nonequilibrium stationary states, generate correlations in…

Quantum Physics · Physics 2026-01-21 Federico Carollo , Sascha Wald

Stochastic point processes with refractoriness appear frequently in the quantitative analysis of physical and biological systems, such as the generation of action potentials by nerve cells, the release and reuptake of vesicles at a synapse,…

Probability · Mathematics 2015-07-28 Moritz Deger , Moritz Helias , Stefano Cardanobile , Fatihcan M. Atay , Stefan Rotter

In this work we theoretically investigate the stochastic resonance (SR) effect in an optomechanical membrane system subject to two weak signals (one optical field and one mechanical force). The quadratic optomechanical coupling allows us to…

Quantum Physics · Physics 2017-02-08 Bixuan Fan , Min Xie

We present a new approach for investigating the Markovian to non-Markovian transition in quantum aggregates strongly coupled to a vibrational bath through the analysis of linear absorption spectra. Utilizing hierarchical algebraic equations…

Quantum Physics · Physics 2025-12-05 Zeng-Zhao Li , Chi-Hang Lam , Cho-Tung Yip , Bo Li

A non-markovian stochastic model is shown to lead to a universal relationship between particle's energy, driven frequency and a frequency of interaction with the medium. It is briefly discussed the possible relevance of this general…

Classical Physics · Physics 2007-05-23 Mario J. Pinheiro

We study the dynamics of a nanomechanical resonator (NMR) subject to a measurement by a low transparency quantum point contact (QPC) or tunnel junction in the non-Markovian domain. We derive the non-Markovian number-resolved (conditional)…

Mesoscale and Nanoscale Physics · Physics 2011-03-30 Po-Wen Chen , Chung-Chin Jian , Hsi-Sheng Goan

We revisit the convergence analysis of constant stepsize stochastic approximation (SA) with decision-dependent Markovian noise, with a focus on characterizing the stationary bias against the root of the mean-field equation. We first…

Optimization and Control · Mathematics 2026-04-16 Hadi Hadavi , Wenlong Mou , Sergey Samsonov , Hoi-To Wai

Discrimination between non-stationarity and long-range dependency is a difficult and long-standing issue in modelling financial time series. This paper uses an adaptive spectral technique which jointly models the non-stationarity and…

Statistical Finance · Quantitative Finance 2019-02-12 Nick James , Roman Marchant , Richard Gerlach , Sally Cripps

The stochastic theory of non-relativistic quantum mechanics presented here relies heavily upon the theory of stochastic processes, with its definitions, theorems and specific vocabulary as well. Its main hypothesis states indeed that the…

Quantum Physics · Physics 2014-04-01 Maurice J. M. L. O. Godart

In this paper, we give a new covariation spectral representation of some non stationary symmetric $\alpha$-stable processes (S$\alpha$S). This representation is based on a weaker covariation pseudo additivity condition which is more general…

Probability · Mathematics 2008-02-22 Nourddine Azzaoui

Stochastic resonance (SR) could amplify weak electric-field signals in nonlinear systems by means of the externally injected noises. Here we propose and experimentally demonstrate a modified SR method, termed squeezing-induced SR,…

In the case of the discrete time coined quantum walk the reduced dynamics of the coin shows non-Markovian recurrence features due to information back-flow from the position degree of freedom. Here we study how this non-Markovian behavior is…

In this work, we investigate stochastic approximation (SA) with Markovian data and nonlinear updates under constant stepsize $\alpha>0$. Existing work has primarily focused on either i.i.d. data or linear update rules. We take a new…

Machine Learning · Statistics 2025-03-18 Dongyan Huo , Yixuan Zhang , Yudong Chen , Qiaomin Xie

We present embedding procedures for the non-Markovian stochastic Schr\"{o}dinger equations, arising from studies of quantum systems coupled with bath environments. By introducing auxiliary wave functions, it is demonstrated that the…

Computational Physics · Physics 2020-05-04 Xiantao Li

Some systems cannot be predicted by classical theories and it is required the development of combined deterministic and stochastic theories that make used of noise for dynamical prediction. Noise is not always an interfering signal which…

Adaptation and Self-Organizing Systems · Physics 2019-05-14 Alexandra Pinto Castellanos

We present the non-Markovian generalization of the widely used stochastic Schrodinger equation. Our result allows to describe open quantum systems in terms of stochastic state vectors rather than density operators, without approximation.…

Quantum Physics · Physics 2009-10-30 Lajos Diosi , Walter T. Strunz

We are interested in understanding stability (almost sure boundedness) of stochastic approximation algorithms (SAs) driven by a `controlled Markov' process. Analyzing this class of algorithms is important, since many reinforcement learning…

Systems and Control · Computer Science 2018-05-18 Arunselvan Ramaswamy , Shalabh Bhatnagar