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The scattering of light impacts sensing and communication technologies throughout the electromagnetic spectrum. Overcoming the effects of time-varying scattering media is particularly challenging. In this article we introduce a new way to…

We have discovered long-lived waves in two sets of numerical models of fast (marginally bound or unbound) flyby galaxy collisions, carried out independently with two different codes. In neither simulation set are the spirals the result of a…

Cosmology and Nongalactic Astrophysics · Physics 2011-05-16 Curtis Struck , Clare L. Dobbs , Jeong-Sun Hwang

Tidal interactions shape the evolution of close-in giant planets and internal gravity-wave breaking offers an efficient pathway for dynamical-tide dissipation, although its population-wide impact remains poorly constrained. We aim to…

Earth and Planetary Astrophysics · Physics 2026-03-31 J. Golonka , G. Maciejewski

This paper analyses the Hamiltonian model of drift waves which describes the chaotic transport of particles in the plasma confinement. With one drift wave the system is integrable and it presents stable orbits. When one wave is added the…

Modeling wave energy converters (WECs) to accurately predict their hydrodynamic behavior has been a challenge for the wave energy field. Often, this results in either low-fidelity, linear models that break down in energetic seas, or…

Fluid Dynamics · Physics 2023-06-07 Brittany Lydon , Brian Polagye , Steven Brunton

Temporal or spatial structures are readily extracted from complex data by modal decompositions like Proper Orthogonal Decomposition (POD) or Dynamic Mode Decomposition (DMD). Subspaces of such decompositions serve as reduced order models…

Fluid Dynamics · Physics 2019-02-25 Jörn Sesterhenn , Amir Shahirpour

Modal decomposition techniques are showing a fast growth in popularity for their good properties as data-driven tools. There are several modal decomposition techniques, yet Proper Orthogonal Decomposition (POD) and Dynamic Mode…

Forward uncertainty quantification in dynamical systems is challenging due to non-smooth or locally oscillating nonlinear behaviors. Spline dimensional decomposition (SDD) addresses such nonlinearity by partitioning input coordinates via…

Machine Learning · Statistics 2025-06-18 Yeonsu Kim , Junhan Lee , Bingran Wang , John T. Hwang , Dongjin Lee

Spiral waves are investigated in oscillatory media exhibiting period-doubling bifurcations. In the period-doubled and chaotic regimes, the rotational symmetry of the spiral wave is broken. The loss of symmetry takes the form of…

chao-dyn · Physics 2009-10-30 Andrei Goryachev , Hugues Chate , Raymond Kapral

Dynamic mode decomposition (DMD) is a data-driven technique widely used to analyze and model fluid problems including transonic buffet flows. Despite its strengths, DMD is known to suffer from sensitivities to the selected settings and the…

Fluid Dynamics · Physics 2023-05-09 Andre Weiner , Richard Semaan

The identification of coherent structures from experimental or numerical data is an essential task when conducting research in fluid dynamics. This typically involves the construction of an empirical mode base that appropriately captures…

Fluid Dynamics · Physics 2016-04-20 Moritz Sieber , Kilian Oberleithner , Christian Oliver Paschereit

We employ two different atomistic methods to investigate solute-defect interactions in nanosized palladium-hydrogen (Pd-H) systems across multiple time scales. The first method, referred to as Diffusive Molecular Dynamics (DMD), focuses on…

Materials Science · Physics 2023-10-06 Xingsheng Sun

After the final stage of the merger of two black holes, the ringdown signal takes an important role on providing information about the gravitational dynamics in strong field. We introduce a novel time-domain (TD) approach, predicated on the…

General Relativity and Quantum Cosmology · Physics 2024-10-31 Hai-Tian Wang , Garvin Yim , Xian Chen , Lijing Shao

Originally introduced in the fluid mechanics community, dynamic mode decomposition (DMD) has emerged as a powerful tool for analyzing the dynamics of nonlinear systems. However, existing DMD theory deals primarily with sequential time…

Numerical Analysis · Mathematics 2014-12-17 Jonathan H. Tu , Clarence W. Rowley , Dirk M. Luchtenburg , Steven L. Brunton , J. Nathan Kutz

We perform an information-theoretic mode decomposition for separated aerodynamic flows. The current data-driven approach based on a neural network referred to as deep sigmoidal flow enables the extraction of an informative component from a…

Fluid Dynamics · Physics 2025-08-08 Kai Fukami , Ryo Araki

Diffusion models have demonstrated powerful data generation capabilities in various research fields such as image generation. However, in the field of vibration signal generation, the criteria for evaluating the quality of the generated…

Machine Learning · Computer Science 2024-07-02 Haiming Yi , Lei Hou , Yuhong Jin , Nasser A. Saeed , Ali Kandil , Hao Duan

Spiral waves are observed in many natural phenomena. They have been extensively represented by the mathematical FitzHugh-Nagumo (FHN) model [Barkley et al., Phys. Rev. A 42, 2489 (1990)] of excitable media. In incompressible fluid…

Plasma Physics · Physics 2018-04-03 Sandeep Kumar , Bhavesh Patel , Amita Das

We introduce a computationally efficient method for the automation of inverse design in science and engineering. Based on simple least-square regression, the underlying dynamic mode decomposition algorithm can be used to construct a…

Machine Learning · Computer Science 2025-02-14 Yunpeng Zhu , Liangliang Cheng , Anping Jing , Hanyu Huo , Ziqiang Lang , Bo Zhang , J. Nathan Kutz

We identify a new type of pattern formation in spatially distributed active systems. We simulate one-dimensional two-component systems with predator-prey local interaction and pursuit-evasion taxis between the components. In a sufficiently…

Pattern Formation and Solitons · Physics 2013-05-29 V. N. Biktashev , M. A. Tsyganov

This paper explores the design of constant modulus Matched-Illumination (MI) waveforms using the Multi-Tone Sinusoidal Frequency Modulation (MTSFM) waveform model. MI waveforms are optimized for detecting targets in known noise and clutter…

Signal Processing · Electrical Eng. & Systems 2021-05-26 Kaushallya Adhikari , David A. Hague