English
Related papers

Related papers: On decomposing mixed-mode oscillations and their r…

200 papers

One of the fundamental steps toward understanding a complex system is identifying variation at the scale of the system's components that is most relevant to behavior on a macroscopic scale. Mutual information provides a natural means of…

Machine Learning · Computer Science 2024-03-20 Kieran A. Murphy , Dani S. Bassett

Understanding dissipative and decohering processes is fundamental to the study of quantum systems. An accurate and generic method for investigating these processes is to simulate both the system and environment, which, however, is…

Quantum Physics · Physics 2009-02-21 Michael Zwolak

The simulation of complex quantum systems on a quantum computer is studied, taking the kicked Harper model as an example. This well-studied system has a rich variety of dynamical behavior depending on parameters, displays interesting…

Quantum Physics · Physics 2007-05-23 Benjamin Levi , Bertrand Georgeot

Simple aerodynamic configurations under even modest conditions can exhibit complex flows with a wide range of temporal and spatial features. It has become common practice in the analysis of these flows to look for and extract physically…

The performances of a new data processing technique, namely the Empirical Mode Decomposition, are evaluated on a fully developed turbulent velocity signal perturbed by a numerical forcing which mimics a long-period flapping. First, we…

Fluid Dynamics · Physics 2015-05-20 Nicolas Mazellier , Fabrice Foucher

Coupled mode theory (CMT) is a powerful framework for decomposing interactions between electromagnetic waves and scattering bodies into resonances and their couplings with power-carrying channels. It has widespread use in few-resonance,…

Optics · Physics 2020-10-22 Hanwen Zhang , Owen D. Miller

The study of synchronization in populations of coupled biological oscillators is fundamental to many areas of biology to include neuroscience, cardiac dynamics and circadian rhythms. Studying these systems may involve tracking the…

Quantitative Methods · Quantitative Biology 2017-01-18 Kevin M. Hannay , Daniel B. Forger , Victoria Booth

Mixed order phase transitions (MOT), which display discontinuous order parameter and diverging correlation length, appear in several seemingly unrelated settings ranging from equilibrium models with long-range interactions to models far…

Statistical Mechanics · Physics 2015-06-22 Amir Bar , David Mukamel

In this work we introduce an Autoencoder for molecular conformations. Our proposed model converts the discrete spatial arrangements of atoms in a given molecular graph (conformation) into and from a continuous fixed-sized latent…

Machine Learning · Computer Science 2021-01-06 Robin Winter , Frank Noé , Djork-Arné Clevert

Spatially localized deformation components are very useful for shape analysis and synthesis in 3D geometry processing. Several methods have recently been developed, with an aim to extract intuitive and interpretable deformation components.…

Graphics · Computer Science 2017-12-19 Qingyang Tan , Lin Gao , Yu-Kun Lai , Jie Yang , Shihong Xia

Optomechanical oscillators (OMOs) combine the co-existing high quality factor mechanical and optical resonances in an integrated device to realize low phase noise RF oscillations. While several attempts have been demonstrated towards…

Optics · Physics 2019-04-08 Cijy Mathai , Sunil A. Bhave , Siddharth Tallur

The relativistic precession model (RPM) is widely-considered as a benchmark framework to interpret quasi-periodic oscillations (QPOs), albeit several observational inconsistencies suggest that the model remains incomplete. The RPM ensures…

General Relativity and Quantum Cosmology · Physics 2025-12-16 Gabriele Bianchini , Orlando Luongo , Marco Muccino

An emergent theory of quantum measurement arises directly by considering the particular subset of many body wavefunctions that can be associated with classical condensed matter and its interaction with delocalized wavefunctions. This…

Quantum Physics · Physics 2015-03-03 Clifford Chafin

Among the many ways to model signals, a recent approach that draws considerable attention is sparse representation modeling. In this model, the signal is assumed to be generated as a random linear combination of a few atoms from a…

Computer Vision and Pattern Recognition · Computer Science 2015-05-18 Javier Turek , Irad Yavneh , Matan Protter , Michael Elad

With the recent advent of a sound mathematical theory for extreme events in dynamical systems, new ways of analyzing a system's inherent properties have become available: Studying only the probabilities of extremely close Poincar\'{e}…

Atmospheric and Oceanic Physics · Physics 2019-01-08 Sebastian Buschow , Petra Friederichs

Multiscale techniques have been widely shown to potentially overcome the limitation of homogenization schemes in representing the microscopic failure mechanisms in heterogeneous media as well as their influence on their structural response…

Numerical Analysis · Mathematics 2021-08-10 Fabrizio Greco , Lorenzo Leonetti , Paolo Lonetti , Raimondo Luciano , Andrea Pranno

Dynamic mode decomposition (DMD) is an efficient tool for decomposing spatio-temporal data into a set of low-dimensional modes, yielding the oscillation frequencies and the growth rates of physically significant modes. In this paper, we…

Dynamical Systems · Mathematics 2023-02-21 Minwoo Lee , Jongho Park

Mode mixing in optical fibers caused by mechanical bending induces perturbations that distort the spatial field profile of coherent beams as they propagate through few-mode or multimode fibers. The observed output from a bent fiber commonly…

This paper describes the many image decomposition models that allow to separate structures and textures or structures, textures, and noise. These models combined a total variation approach with different adapted functional spaces such as…

Image and Video Processing · Electrical Eng. & Systems 2024-11-11 Jerome Gilles

Model order reduction in high-dimensional, nonlinear dynamical systems if often enabled through fast-slow timescale separation. One such approach involves identifying a low-dimensional slow manifold to which the state rapidly converges and…

Dynamical Systems · Mathematics 2026-05-14 Dan Wilson