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Related papers: Modal Extraction in Spatially Extended Systems

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Modal decomposition methods are important for characterizing the low-dimensional dynamics of complex systems, including turbulent flows. Different methods have varying data requirements and produce modes with different properties. Spectral…

Fluid Dynamics · Physics 2025-08-28 Caroline Cardinale , Steven L. Brunton , Tim Colonius

A technique to simulate the spex-mixer/mill system as a macroscopic ensemble rather than a pure dynamical system is proposed. The treatment is suitable especially for comminution processes generating the nanomaterial up to nanometers scale…

Computational Physics · Physics 2010-07-08 Muhandis , F. Nurdiana , A. S. Wismogroho , N. T. Rochman , L. T. Handoko

In the field of structural engineering analysis, a common requirement is to calculate the modal frequencies of a structure that has undergone an update, either naturally (such as from material degradation), or due to man-made influences (by…

Optimization and Control · Mathematics 2020-08-25 P. Cheema , M. M. Alamdari , G. A. Vio

Transport-dominated phenomena provide a challenge for common mode-based model reduction approaches. We present a model reduction method, which is suited for these kind of systems. It extends the proper orthogonal decomposition (POD) by…

Numerical Analysis · Mathematics 2018-02-20 Julius Reiss , Philipp Schulze , Jörn Sesterhenn , Volker Mehrmann

A mass-conservative high-order unfitted finite element method for convection-diffusion equations in evolving domains is proposed. The space-time method presented in [P. Hansbo, M. G. Larson, S. Zahedi, Comput. Methods Appl. Mech. Engrg. 307…

Numerical Analysis · Mathematics 2024-05-01 Sebastian Myrbäck , Sara Zahedi

Stochastic computational models in the form of pure jump processes occur frequently in the description of chemical reactive processes, of ion channel dynamics, and of the spread of infections in populations. For spatially extended models,…

Numerical Analysis · Mathematics 2018-02-23 Augustin Chevallier , Stefan Engblom

In this work we investigate the presence of defect structures in models described by two real scalar fields. The coupling between the two fields is inspired on the equations for a multimode laser, and the minimum energy trivial…

Optics · Physics 2009-05-04 A. R. Gomes , D. Bazeia

A signal space approach is presented to study the Nyquist sampling, number of degrees of freedom and reconstruction of an electromagnetic field under arbitrary scattering conditions. Conventional signal processing tools, such as the…

Signal Processing · Electrical Eng. & Systems 2022-10-12 Andrea Pizzo , Andrea de Jesus Torres , Luca Sanguinetti , Thomas L. Marzetta

We propose to identify process zones in heterogeneous materials by tailored statistical tools. The process zone is redefined as the part of the structure where the random process cannot be correctly approximated in a low-dimensional…

Elastic systems that are spatially heterogeneous in their mechanical response pose special challenges for molecular simulations. Standard methods for sampling thermal fluctuations of a system's size and shape proceed through a series of…

Materials Science · Physics 2015-05-13 Sander Pronk , Phillip L. Geissler

We propose a novel method applied to extrasolar planetary dynamics to describe the system stability. The observations in this field serve the measurements mainly of radial velocity, transit time, and/or celestial position. These scalar time…

Earth and Planetary Astrophysics · Physics 2020-01-08 Tamas Kovacs

We extend the notions of multipole and subsystem symmetries to more general {\it spatially modulated} symmetries. We uncover two instances with exponential and (quasi)-periodic modulations, and provide simple microscopic models in one, two…

Statistical Mechanics · Physics 2021-10-19 Pablo Sala , Julius Lehmann , Tibor Rakovszky , Frank Pollmann

Four-dimensional spacetime, together with a natural generalisation to extra dimensions, is obtained through an analysis of the structures and symmetries deriving from possible arithmetic expressions for one-dimensional time. On taking the…

General Physics · Physics 2016-03-25 David J. Jackson

A valuable step in the modeling of multiscale dynamical systems in fields such as computational chemistry, biology, materials science and more, is the representative sampling of the phase space over long timescales of interest; this task is…

Machine Learning · Computer Science 2023-12-29 Ellis R. Crabtree , Juan M. Bello-Rivas , Ioannis G. Kevrekidis

Dynamic mode decomposition (DMD) represents an effective means for capturing the essential features of numerically or experimentally generated flow fields. In order to achieve a desirable tradeoff between the quality of approximation and…

Fluid Dynamics · Physics 2014-12-11 Mihailo R. Jovanović , Peter J. Schmid , Joseph W. Nichols

A quasimodal expansion method (QMEM) is developed to model and understand the scattering properties of arbitrary shaped two-dimensional (2-D) open structures. In contrast with the bounded case which have only discrete spectrum (real in the…

Piecewise smooth maps are known to exhibit a wide range of dynamical features including numerous types of periodic orbits. Predicting regions in parameter space where such periodic orbits might occur and determining their stability is…

Dynamical Systems · Mathematics 2016-07-07 Arindam Saha , Soumitro Banerjee

We measured the ensemble-averaged spectral correlation functions and statistical distributions of spectral spacing and intensity for lasing modes in weakly scattering systems, and compared them to those of the amplified spontaneous emission…

Optics · Physics 2009-11-13 Xiaohua Wu , Hui Cao

Coarse-graining or model reduction is a term describing a range of approaches used to extend the time-scale of molecular simulations by reducing the number of degrees of freedom. In the context of molecular simulation, standard…

Dynamical Systems · Mathematics 2023-11-14 Thomas Hudson , Xingjie Helen Li

In many environments, only a relatively small subset of the complete state space is necessary in order to accomplish a given task. We develop a simple technique using emergency stops (e-stops) to exploit this phenomenon. Using e-stops…

Machine Learning · Computer Science 2019-12-05 Samuel Ainsworth , Matt Barnes , Siddhartha Srinivasa