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Related papers: A hidden variables model for interference phenomen…

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A general stochastic model is developed for the total interference in wideband systems, denoted as the PNSC(alpha) Interference Model. It allows one to obtain, analytic representations in situations where (a) interferers are distributed…

Applications · Statistics 2012-07-09 Gareth W. Peters , Ido Nevat , Francois Septier , Laurent Clavier

We consider stochastic systems of interacting particles or agents, with dynamics determined by an interaction kernel which only depends on pairwise distances. We study the problem of inferring this interaction kernel from observations of…

Statistics Theory · Mathematics 2020-07-31 Fei Lu , Mauro Maggioni , Sui Tang

Recent research has provided a wealth of evidence highlighting the pivotal role of high-order interdependencies in supporting the information-processing capabilities of distributed complex systems. These findings may suggest that high-order…

Adaptation and Self-Organizing Systems · Physics 2023-05-24 Patricio Orio , Pedro A. M. Mediano , Fernando E. Rosas

Dynamical systems across many disciplines are modeled as interacting particles or agents, with interaction rules that depend on a very small number of variables (e.g. pairwise distances, pairwise differences of phases, etc...), functions of…

Machine Learning · Computer Science 2022-08-05 Jinchao Feng , Mauro Maggioni , Patrick Martin , Ming Zhong

In exploring the simulation of human rhythmic perception and synchronization capabilities, this study introduces a computational model inspired by the physical and biological processes underlying rhythm processing. Utilizing a reservoir…

Neurons and Cognition · Quantitative Biology 2025-03-28 Zhongju Yuan , Wannes Van Ransbeeck , Geraint Wiggins , Dick Botteldooren

Classical sequential models employed in time-series prediction rely on learning the mappings from the past to the future instances by way of a hidden state. The Hidden states characterise the historical information and encode the required…

Machine Learning · Computer Science 2023-02-14 Vignesh Gopakumar , Stanislas Pamela , Lorenzo Zanisi

In this paper, we study the stochastic resonance (SR) effect in an optomechanical system driven by a strong coupling field and two weak signals in both semiclassical and quantum frameworks. In the semiclassical description, the SR phenomena…

Optics · Physics 2018-11-21 Min Xie , Bixuan Fan , Xiaoli He , Qingqing Chen

We consider a particle in one dimension submitted to amplitude and phase disorder. It can be mapped onto the complex Burgers equation, and provides a toy model for problems with interplay of interferences and disorder, such as the NSS model…

Disordered Systems and Neural Networks · Physics 2015-03-17 Alexander Dobrinevski , Pierre Le Doussal , Kay Jörg Wiese

Quantum theory of interference phenomena does not take the diameter of the particle into account, since particles were much smaller than the width of the slits in early observations. In recent experiments with large molecules, the diameter…

Quantum Physics · Physics 2007-05-23 Mirjana Bozic , Dusan Arsenovic , Lepsa Vuskovic

In classical mechanics and electromagnetism, interference occurs when two or more waves overlap at the same point in spacetime. However, the advent of quantum electrodynamics (QED) and its remarkable success in describing light-matter…

Quantum Physics · Physics 2025-08-15 Alan C. Santos , Celso J. Villas-Boas

Time-varying linear state-space models are powerful tools for obtaining mathematically interpretable representations of neural signals. For example, switching and decomposed models describe complex systems using latent variables that evolve…

This paper deals with the noise identification of a linear time-varying stochastic dynamic system described by the state-space model. In particular, the stress is laid on the design of the correlation measurement difference method for…

Signal Processing · Electrical Eng. & Systems 2025-09-12 Oliver Kost , Jindrich Dunik , Ivo Puncochar , Ondrej Straka

This paper considers physical systems described by hidden states and indirectly observed through repeated measurements corrupted by unmodeled nuisance parameters. A network-based representation learns to disentangle the coherent information…

Computational Physics · Physics 2022-02-08 Pawan Bharadwaj , Matthew Li , Laurent Demanet

Time evolution in several classes of quantum devices is generated through the application of quantum gates. Resetting is a critical technological feature in these systems allowing for mid-circuit measurement and complete or partial qubit…

Quantum Physics · Physics 2025-05-14 Sascha Wald , Louie Hong Yao , Thierry Platini , Chris Hooley , Federico Carollo

We discuss stochastic resonance (SR) effects in driven coupled quantum systems. We construct dynamical and information theoretic measures of the system's response that exhibit a non-monotonic behaviour as a function of the noise strength.…

Quantum Physics · Physics 2013-05-29 Susana Huelga , Martin Plenio

In this work we develop a general formalism that categorizes the action of broken scale invariance on the non-equilibrium dynamics of non-relativistic quantum systems. This approach is equally applicable to both strongly and weakly…

Quantum Gases · Physics 2018-07-11 Jeff Maki , Li-Ming Zhao , Fei Zhou

We carry out a detailed numerical investigation of stochastic resonance in underdamped systems in the non-perturbative regime. We point out that an important distinction between stochastic resonance in overdamped and underdamped systems…

Pattern Formation and Solitons · Physics 2009-11-11 Rajarshi Ray , Supratim Sengupta

Stochastic forces in natural systems are rarely isotropic. From hydrodynamically coupled colloids to chemical reaction networks, noise contributions are inherently correlated. Together with internal interactions and changing environments,…

Statistical Mechanics · Physics 2026-05-14 Andrea Marchetti , Daniel Maria Busiello , Giorgio Nicoletti

We study the impact of stochastic perturbations to deterministic dynamical systems using the formalism of the Ruelle response theory and explore how stochastic noise can be used to explore the properties of the underlying deterministic…

Statistical Mechanics · Physics 2015-05-27 Valerio Lucarini

In this work we determine a process-level Large Deviation Principle (LDP) for a model of interacting particles indexed by a lattice $\mathbb{Z}^d$. The connections are random, sparse and unscaled, so that the system converges in the large…

Probability · Mathematics 2024-10-01 James MacLaurin