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A recurrent Neural Network (RNN) is trained to predict sound samples based on audio input augmented by control parameter information for pitch, volume, and instrument identification. During the generative phase following training, audio…

Sound · Computer Science 2019-03-27 Lonce Wyse , Muhammad Huzaifah

We examine the behavior of a one-dimensional superconducting wire exposed to an applied electric current. We use the time-dependent Ginzburg-Landau model to describe the system and retain temperature and applied current as parameters.…

Superconductivity · Physics 2009-11-13 J. rubinstein , P. Sternberg , Q. Ma

Swimming and flying animals demonstrate remarkable adaptations to diverse flow conditions in their environments. In this study, we aim to advance the fundamental understanding of the interaction between flexible bodies and heterogeneous…

Fluid Dynamics · Physics 2025-12-16 Abdur Rehman , Daniel Floryan

Disorders of voice production have severe effects on the quality of life of the affected individuals. A simulation approach is used to investigate the cause-effect chain in voice production showing typical characteristics of voice such as…

Sound · Computer Science 2022-07-20 Florian Kraxberger , Andreas Wurzinger , Stefan Schoder

The effects of second harmonics of the density and temperature perturbations on the linear Geodesic Acoustic Mode (GAM) frequency and non-linear generation of the GAM are investigated, using a fluid model. We show that the second harmonics…

Plasma Physics · Physics 2014-07-31 Johan Anderson , Hans Nordman , Raghvendra Singh

Magneto-acoustic waves in partially ionized plasmas are damped due to elastic collisions between charged and neutral particles. Here, we use a linearized two-fluid model to describe the influence of this collisional interaction on the…

Plasma Physics · Physics 2025-10-17 David Martínez-Gómez

Resonant activation is one of classical effects demonstrating constructive role of noise. In resonant activation cooperative action of barrier modulation process and noise lead to the optimal escape kinetics as measured by the mean first…

Statistical Mechanics · Physics 2020-03-16 Krzysztof Szczepaniec , Bartlomiej Dybiec

Many nonlinear systems are described by eigenmodes with amplitude-dependent frequencies, interacting strongly whenever the frequencies become commensurate at internal resonances. Fast energy exchange via the resonances holds the key to rich…

Chaotic Dynamics · Physics 2022-12-07 Mingkang Wang , Diego J. Perez-Morelo , Daniel Lopez , Vladimir A. Aksyuk

We present a high harmonic generation theory which generalizes the strong-field approximation to the resonant case, when the harmonic frequency is close to that of the transition from the ground to an autoionizing state of the generating…

Atomic Physics · Physics 2015-06-16 V. V. Strelkov , M. A. Khokhlova , N. Yu. Shubin

Neurons in the main center of convergence in the auditory midbrain, the central nucleus of the inferior colliculus (ICC) have been shown to display either linear significant receptive fields, or both, linear and nonlinear significant…

Neurons and Cognition · Quantitative Biology 2020-05-06 Dominika Lyzwa , Chen Chen , Monty A. Escabi , Heather L. Read

The 2D second-mode is a potent instability in hypersonic boundary layers (HBLs). We study its linear and nonlinear evolution, followed by its role in transition and eventual breakdown of the HBL into a fully turbulent state. Linear…

Fluid Dynamics · Physics 2020-12-02 S. Unnikrishnan , Datta V. Gaitonde

Graph Neural Networks (GNNs) typically operate by message-passing, where the state of a node is updated based on the information received from its neighbours. Most message-passing models act as graph convolutions, where features are mixed…

In the present paper we study the long wavelength and slow time scale behavior of a coasting beam in a resonator adopting a broad-band impedance model. Based on the renormalization group approach we derive a set of coupled evolution…

Accelerator Physics · Physics 2007-05-23 Stephan I. Tzenov

Stochastic resonance is a general phenomenon usually observed in one-dimensional, amplitude modulated, bistable systems.We show experimentally the emergence of phase stochastic resonance in the bidimensional response of a forced…

Parameters of a high frequency capacitive discharge in argon in axially symmetric chambers of different geometries are studied in experiments and by means of two-dimensional kinetic modeling by the Particle-in-Cell method. It is…

Plasma Physics · Physics 2015-05-19 I. V. Schweigert , D. A. Ariskin , T. V. Chernoiziumskaya , A. S. Smirnov

The transmission probability and phase through a few-electron quantum dot are studied within a resonance theory for the strong coupling regime to the conducting leads. We find that the interaction between overlapping resonances leads to…

Mesoscale and Nanoscale Physics · Physics 2011-05-09 E. R. Racec

We propose a semiparametric model for dyadic link formations in directed networks. The model contains a set of degree parameters that measure different effects of popularity or outgoingness across nodes, a regression parameter vector that…

Methodology · Statistics 2025-02-21 Lianqiang Qu , Lu Chen , Ting Yan , Yuguo Chen

Parametrically-excited surface waves, forced by a periodic sequence of delta-function impulses, are considered within the framework of the Zhang-Vi\~nals model (J. Fluid Mech. 1997). The exact impulsive-forcing results, in the linear and…

Pattern Formation and Solitons · Physics 2009-11-11 Anne Catlla , Jeff Porter , Mary Silber

We present a spatiotemporal gain-loss framework for eigenmode steering in coupled acoustic resonators. A cross-coupled gain-loss coefficient links the gain of one resonator to the intensity of its partner, creating nonlinear feedback that…

Applied Physics · Physics 2025-11-11 Wai Chun Wong , Greggory Chaplain , Jensen Li

AI training datasets will inevitably contain AI-generated examples, leading to ``feedback'' in which the output of one model impacts the training of another. It is known that such iterative feedback can lead to model collapse, yet the…

Machine Learning · Computer Science 2026-02-24 Vibhas Kumar Vats , David J. Crandall , Samuel Goree
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