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We study discrete time linear constrained switching systems with additive disturbances, in which the switching may be on the system matrices, the disturbance sets, the state constraint sets or a combination of the above. In our general…

Systems and Control · Computer Science 2017-02-03 Nikolaos Athanasopoulos , Konstantinos Smpoukis , Raphael M. Jungers

We propose an approach for learning the causal structure in stochastic dynamical systems with a $1$-step functional dependency in the presence of latent variables. We propose an information-theoretic approach that allows us to recover the…

Information Theory · Computer Science 2017-01-25 Saber Salehkaleybar , Jalal Etesami , Negar Kiyavash

The theory of covariance control and covariance steering (CS) deals with controlling the dispersion of trajectories of a dynamical system, under the implicit assumption that accurate prior knowledge of the system being controlled is…

Systems and Control · Electrical Eng. & Systems 2024-05-21 Joshua Pilipovsky , Panagiotis Tsiotras

We prove a general existence result in stochastic optimal control in discrete time where controls take values in conditional metric spaces, and depend on the current state and the information of past decisions through the evolution of a…

Optimization and Control · Mathematics 2018-12-19 Asgar Jamneshan , Michael Kupper , José Miguel Zapata

The consistent histories formalism can be used to describe histories comprised of events across many systems, times, and places, plausibly rich enough to describe our experiences of the classical world; however, many consistent history sets…

Quantum Physics · Physics 2026-05-11 Nick Ormrod , Tein van der Lugt , Yìlè Yīng , Jarosław K. Korbicz

Our recent interest is focused on establishing the necessary and sufficient conditions that guarantee a long-term stable evolution of both natural and artificial systems. Two necessary conditions, called global and local boundedness, are…

Statistical Mechanics · Physics 2007-05-23 Maria K. Koleva , L. A. Petrov

Evolutionary game theory has been successfully used to investigate the dynamics of systems, in which many entities have competitive interactions. From a physics point of view, it is interesting to study conditions under which a coordination…

Physics and Society · Physics 2015-05-14 Dirk Helbing , Anders Johansson

We develop a generalized stability framework for stochastic discrete-time systems, where the generality pertains to the ways in which the distribution of the state energy can be characterized. We use tools from finance and operations…

Systems and Control · Electrical Eng. & Systems 2022-11-23 Margaret P. Chapman , Dionysios S. Kalogerias

Modern learning systems increasingly interact with data that evolve over time and depend on hidden internal state. We ask a basic question: when is such a dynamical system learnable from observations alone? This paper proposes a research…

Machine Learning · Computer Science 2025-12-23 Elad Hazan , Shai Shalev Shwartz , Nathan Srebro

We derive stochastic master equations for a quantum system interacting with a Bose field prepared in a superposition of continuous-mode coherent states. To determine a conditional evolution of the quantum system we use a collision model…

Quantum Physics · Physics 2020-02-11 Anita Dabrowska

All previously derived thermodynamic fluctuation theorems (FTs) that concern multiple co-evolving systems have required that each system can only change its state during an associated pre-fixed, limited set of time intervals. However, in…

Statistical Mechanics · Physics 2021-04-16 David H. Wolpert

Switching dynamical systems provide a powerful, interpretable modeling framework for inference in time-series data in, e.g., the natural sciences or engineering applications. Since many areas, such as biology or discrete-event systems, are…

Machine Learning · Computer Science 2021-09-30 Lukas Köhs , Bastian Alt , Heinz Koeppl

In complex systems, the interplay between nonlinear and stochastic dynamics, e.g., J. Monod's necessity and chance, gives rise to an evolutionary process in Darwinian sense, in terms of discrete jumps among attractors, with punctuated…

Adaptation and Self-Organizing Systems · Physics 2013-03-18 Hong Qian

Given an autonomous system of ordinary differential equations (ODE), we consider developing practical models for the deterministic, slow/coarse behavior of the ODE system. Two types of coarse variables are considered. The first type…

Dynamical Systems · Mathematics 2015-06-05 Likun Tan , Amit Acharya , Kaushik Dayal

We introduce a notion of emergence for coarse-grained macroscopic variables associated with highly-multivariate microscopic dynamical processes, in the context of a coupled dynamical environment. Dynamical independence instantiates the…

Adaptation and Self-Organizing Systems · Physics 2023-07-26 Lionel Barnett , Anil K. Seth

We present a stochastic constrained output-feedback data-driven predictive control scheme for linear time-invariant systems subject to bounded additive disturbances. The approach uses data-driven predictors based on an extension of Willems'…

Systems and Control · Electrical Eng. & Systems 2025-10-07 Johannes Teutsch , Sebastian Kerz , Dirk Wollherr , Marion Leibold

This paper considers systems subject to nonholonomic constraints which are not uniform on the whole configuration manifold. When the constraints change, the system undergoes a transition in order to comply with the new imposed conditions.…

Differential Geometry · Mathematics 2007-05-23 Jorge Cortes , Alexandre M. Vinogradov

Considering deterministic classical lattice systems with continuous variables, we show that, if the initial conditions are sampled according to a probability distribution in which the dynamical variables are statistically independent, the…

Statistical Mechanics · Physics 2025-10-29 Nicolas Nessi , Peter Reimann

A quantum spin system is discussed, where a heat flow between infinite reservoirs takes place in a finite region. A time dependent force may also be acting. Our analysis is based on a simple technical assumption concerning the time…

Mathematical Physics · Physics 2007-05-23 David Ruelle

We propose a method for learning dynamical systems from high-dimensional empirical data that combines variational autoencoders and (spatio-)temporal attention within a framework designed to enforce certain scientifically-motivated…

Machine Learning · Computer Science 2023-06-22 Kai Lagemann , Christian Lagemann , Sach Mukherjee