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This work aims to improve generalization and interpretability of dynamical systems by recovering the underlying lower-dimensional latent states and their time evolutions. Previous work on disentangled representation learning within the…

Machine Learning · Computer Science 2024-06-07 Çağlar Hızlı , Çağatay Yıldız , Matthias Bethge , ST John , Pekka Marttinen

We consider reaction-diffusion systems and other related dissipative systems on unbounded domains which would have a Liapunov function (and gradient structure) when posed on a finite domain. In this situation, the system may reach local…

Analysis of PDEs · Mathematics 2023-02-02 Alexander Mielke , Stefanie Schindler

For a single particle, relaxation into different ground states is governed by fixed branching ratios determined by the transition matrix element and the environment. Here, we show that in many-body open quantum systems the occupation…

In this paper, we present a framework for Stability Analysis of Systems of Coupled Linear Partial-Differential Equations. The class of PDE systems considered in this paper includes parabolic, elliptic and hyperbolic systems with Dirichelet,…

Optimization and Control · Mathematics 2018-03-28 Matthew M. Peet

Dynamical systems with large state-spaces are often expensive to thoroughly explore experimentally. Coarse-graining methods aim to define simpler systems which are more amenable to analysis and exploration; most current methods, however,…

Systems and Control · Computer Science 2016-11-01 Michalis Michaelides , Dimitrios Milios , Jane Hillston , Guido Sanguinetti

We consider the problem of learning stabilizable systems governed by nonlinear state equation $h_{t+1}=\phi(h_t,u_t;\theta)+w_t$. Here $\theta$ is the unknown system dynamics, $h_t $ is the state, $u_t$ is the input and $w_t$ is the…

Machine Learning · Computer Science 2021-11-22 Yahya Sattar , Samet Oymak

Constrained quantum dynamics is used to propose a nonlinear dynamical equation for pure states of a generalized coarse-grained system. The relevant constraint is given either by the generalized purity or by the generalized invariant…

Quantum Physics · Physics 2015-05-19 Nikola Buric

State-dependent gauge principle invoked to realize the relativity to a measuring device, has been proposed. Self-consistent global (cosmic) potential forms the state space of the fundamental field and its connection, agreed with…

General Relativity and Quantum Cosmology · Physics 2007-05-23 P. Leifer

We study the existence of almost periodic solutions for semi-linear abstract parabolic evolution equations with impulse action at state-dependent moments. In particular, we present conditions excluding the beating phenomenon in these…

Dynamical Systems · Mathematics 2016-10-07 Robert Hakl , Manuel Pinto , Viktor Tkachenko , Sergei Trofimchuk

The automated construction of coarse-grained models represents a pivotal component in computer simulation of physical systems and is a key enabler in various analysis and design tasks related to uncertainty quantification. Pertinent methods…

Machine Learning · Statistics 2019-09-11 Constantin Grigo , Phaedon-Stelios Koutsourelakis

We study theoretically continuous-variable entanglement between the motional degrees of freedom of optically trapped massive particles coupled via the Coulomb interaction, in the presence of a feedback control scheme. We perform a detailed…

Quantum Physics · Physics 2025-10-22 Gad Horovitz , Alexander N. Poddubny

The mean-field pictures based on the standard time-dependent variational approach have widely been used in the study of nonlinear many-boson systems such as the Bose-Hubbard model. The mean-field schemes relevant to Gutzwiller-like trial…

Mathematical Physics · Physics 2008-11-26 P. Buonsante , V. Penna

Reliable preparation of many-body ground states is an essential task in quantum computing, with applications spanning areas from chemistry and materials modeling to quantum optimization and benchmarking. A variety of approaches have been…

Quantum Physics · Physics 2026-02-09 Ricard Puig , Berta Casas , Alba Cervera-Lierta , Zoë Holmes , Adrián Pérez-Salinas

Harnessing data to discover the underlying governing laws or equations that describe the behavior of complex physical systems can significantly advance our modeling, simulation and understanding of such systems in various science and…

Machine Learning · Computer Science 2021-11-17 Zhao Chen , Yang Liu , Hao Sun

We consider a nonlinear parabolic model that forces solutions to stay on a $L^2$-sphere through a nonlocal term in the equation. We study the local and global well-posedness on a bounded domain and the whole Euclidean space in the energy…

Analysis of PDEs · Mathematics 2024-11-28 Boris Shakarov

In this paper we discuss the optimal control of a quasilinear parabolic state equation. Its form is leaned on the kind of problems arising for example when controlling the anisotropic Allen-Cahn equation as a model for crystal growth.…

Optimization and Control · Mathematics 2025-08-06 Luise Blank , Johannes Meisinger

Large deviations of conservative interacting particle systems, such as the zero range process, about their hydrodynamic limit and their respective rate functions lead to the analysis of the skeleton equation; a degenerate…

Probability · Mathematics 2022-03-16 Benjamin Fehrman , Benjamin Gess

We present an abstract framework for treating the theory of well-posedness of solutions to abstract parabolic partial differential equations on evolving Hilbert spaces. This theory is applicable to variational formulations of PDEs on…

Analysis of PDEs · Mathematics 2015-07-13 Amal Alphonse , Charles M. Elliott , Björn Stinner

A dynamical system is defined in terms of the gradient of a payoff function. Dynamical variables are of two types, ascent and descent. The ascent variables move in the direction of the gradient, while the descent variables move in the…

Optimization and Control · Mathematics 2019-03-07 H. Sebastian Seung

Inference and prediction under partial knowledge of a physical system is challenging, particularly when multiple confounding sources influence the measured response. Explicitly accounting for these influences in physics-based models is…

Machine Learning · Statistics 2026-01-14 Ioannis Christoforos Koune , Alice Cicirello
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