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Simulating the time evolution of Partial Differential Equations (PDEs) of large-scale systems is crucial in many scientific and engineering domains such as fluid dynamics, weather forecasting and their inverse optimization problems.…

Machine Learning · Computer Science 2022-10-13 Tailin Wu , Takashi Maruyama , Jure Leskovec

The evolution equations mentioned in the title of this paper read as follows: x~n = P(n)(x1; x2) , n = 1, 2 , where l is the "discrete-time" independent variable taking integer values (l =0, 1, 2, ...), xn = xn (l) are the 2 dependent…

Mathematical Physics · Physics 2019-04-05 Francesco Calogero , Farrin Payandeh

Establishing appropriate mathematical models for complex systems in natural phenomena not only helps deepen our understanding of nature but can also be used for state estimation and prediction. However, the extreme complexity of natural…

Machine Learning · Computer Science 2024-03-27 Cheng Fang , Jinqiao Duan

A general scheme for construction of dynamical systems able to learn generation of the desired kinds of dynamics through adjustment of their internal structure is proposed. The scheme involves intrinsic time-delayed feedback to steer the…

Adaptation and Self-Organizing Systems · Physics 2015-06-22 Pablo Kaluza , Alexander S. Mikhailov

This short survey article stems from recent progress on critical cases of stochastic evolution equations in variational formulation with additive, multiplicative or gradient noises. Typical examples appear as the limit cases of the…

Probability · Mathematics 2025-10-24 Ioana Ciotir , Dan Goreac , Jonas M. Tölle

We develop a general criterion about coarsening for a class of nonlinear evolution equations describing one dimensional pattern-forming systems. This criterion allows one to discriminate between the situation where a coarsening process…

Statistical Mechanics · Physics 2007-05-23 Paolo Politi , Chaouqi Misbah

The coarsening exponents describing the growth of long-range order in systems quenched from a disordered to an ordered phase are discussed in terms of the decay rate, omega(k), for the relaxation of a distortion of wavevector k applied to a…

Statistical Mechanics · Physics 2009-10-31 A. J. Bray

Model-free reinforcement learning attempts to find an optimal control action for an unknown dynamical system by directly searching over the parameter space of controllers. The convergence behavior and statistical properties of these…

Optimization and Control · Mathematics 2021-03-17 Hesameddin Mohammadi , Armin Zare , Mahdi Soltanolkotabi , Mihailo R. Jovanović

Starting from the classical Saltzman 2D convection equations, we derive via a severe spectral truncation a minimal 10 ODE system which includes the thermal effect of viscous dissipation. Neglecting this process leads to a dynamical system…

Chaotic Dynamics · Physics 2011-10-11 Valerio Lucarini , Klaus Fraedrich

Recent progress of symbolic dynamics of one- and especially two-dimensional maps has enabled us to construct symbolic dynamics for systems of ordinary differential equations (ODEs). Numerical study under the guidance of symbolic dynamics is…

chao-dyn · Physics 2009-10-30 Bai-lin Hao , Jun-xian Liu , Wei-mou Zheng

We show that accelerated gradient descent, averaged gradient descent and the heavy-ball method for non-strongly-convex problems may be reformulated as constant parameter second-order difference equation algorithms, where stability of the…

Machine Learning · Statistics 2015-04-08 Nicolas Flammarion , Francis Bach

A pure frequency domain method for the computation of periodic solutions of nonlinear ordinary differential equations (ODEs) is proposed in this study. The method is particularly suitable for the analysis of systems that feature distinct…

Numerical Analysis · Mathematics 2021-01-07 Malte Krack , Lars Panning-von Scheidt , Jörg Wallaschek

Rectified flow and reflow procedures have significantly advanced fast generation by progressively straightening ordinary differential equation (ODE) flows. They operate under the assumption that image and noise pairs, known as couplings,…

Machine Learning · Computer Science 2024-11-04 Dogyun Park , Sojin Lee , Sihyeon Kim , Taehoon Lee , Youngjoon Hong , Hyunwoo J. Kim

Surface growth models may give rise to unstable growth with mound formation whose tipical linear size L increases in time. In one dimensional systems coarsening is generally driven by an attractive interaction between domain walls or kinks.…

Statistical Mechanics · Physics 2007-05-23 Alessandro Torcini , Paolo Politi

We introduce a two-dimensional discrete-time dynamical system which represents the evolution of an angle and angular velocity. While the angle evolves by a fixed amount in every step, the evolution of the angular velocity is governed by a…

Dynamical Systems · Mathematics 2024-12-20 Aakash Khandelwal , Ranjan Mukherjee

Boolean Delay Equations (BDEs) are semi-discrete dynamical models with Boolean-valued variables that evolve in continuous time. Systems of BDEs can be classified into conservative or dissipative, in a manner that parallels the…

Cellular Automata and Lattice Gases · Physics 2015-06-26 Michael Ghil , Ilya Zaliapin , Barbara Coluzzi

In [1], we have presented the theoretical background for finding the Elementary Invariants for a 3D system of first order rational differential equations (1ODEs). We have also provided an algorithm to find such Invariants. Here we introduce…

Mathematical Physics · Physics 2017-08-30 L. G. S. Duarte , J. P. C. Eiras , L. A. C. P. da Mota

We study numerically the coarsening dynamics of the Ising model on a regular lattice with random bonds and on deterministic fractal substrates. We propose a unifying interpretation of the phase-ordering processes based on two classes of…

Statistical Mechanics · Physics 2015-06-24 Federico Corberi , Eugenio Lippiello , Raffaella Burioni , Alessandro Vezzani , Marco Zannetti

In data-driven modeling of spatiotemporal phenomena careful consideration often needs to be made in capturing the dynamics of the high wavenumbers. This problem becomes especially challenging when the system of interest exhibits shocks or…

Machine Learning · Computer Science 2022-12-28 Alec J. Linot , Joshua W. Burby , Qi Tang , Prasanna Balaprakash , Michael D. Graham , Romit Maulik

We design a class of variable metric evolution strategies well suited for high-dimensional problems. We target problems with many variables, not (necessarily) with many objectives. The construction combines two independent developments:…

Neural and Evolutionary Computing · Computer Science 2024-12-23 Tobias Glasmachers