Temporal Forcing of Traveling Wave Patterns

1996 ◽  
Vol 6 (11) ◽  
pp. 1417-1434 ◽  
Author(s):  
Joceline Lega ◽  
Jean-Marc Vince
Keyword(s):  
Traveling Wave ◽  
Wave Patterns

Phase Drift in Networks of Coupled Colpitts Oscillators

2021 ◽  
Vol 31 (04) ◽  
pp. 2130010
Author(s):  
Lourdes Coria ◽  
Horacio Lopez ◽  
Antonio Palacios ◽  
Visarath In ◽  
Patrick Longhini
Keyword(s):  
Collective Behavior ◽  
Traveling Wave ◽  
Scaling Law ◽  
Industrial Applications ◽  
Basins Of Attraction ◽  
Navigation Systems ◽  
Negative Effects ◽  
Phase Drift ◽  
Wide Range ◽  
Wave Patterns

In modern times, satellite-based global positioning and navigation systems, such as the GPS, include precise time-keeping devices, e.g. atomic clocks, which are crucial for navigation and for a wide range of economic and industrial applications. However, precise timing might not be available when the environment renders satellite equipment inoperable. In response to this critical need, we have been carrying out, over the past three years, theory and preliminary experiments [Buono et al., 2018a; Buono et al., 2018b; Palacios et al., 2020], towards developing a novel and inexpensive precision timing device that can function independently of GPS availability. The fundamental idea is to exploit collective behavior generated by networks of coupled nonlinear oscillators. Common sense may suggest that synchronized oscillations may lead to higher accuracy. Previous works show, however, that it is not synchronization but rather, traveling wave patterns, in which consecutive oscillators are out of phase by a constant amount, that can better reduce the negative effects of noise and material imperfections which cause phase drift. In this work we advance the state-of-art in the network-based concept by studying, mainly computationally, collective behavior in networks of Colpitts oscillators. These type of oscillators are chosen because they offer a wide range of advantages (such as the ability to tune up the oscillations over a broad frequency range). The results highlight the regions of parameter space, including coupling strength, where traveling wave patterns have the largest basins of attraction and the ability to reduce phase drift by a [Formula: see text] scaling law, where [Formula: see text] is the number of oscillators in the network. The results should also provide guidelines for follow-up design and fabrication tasks of a network-based technology for precision timing.

scholarly journals Thalamocortical network connectivity controls spatiotemporal dynamics of cortical and thalamic traveling waves

2019 ◽  
Author(s):  
Sayak Bhattacharya ◽  
Matthieu B. Le Cauchois ◽  
Pablo A. Iglesias ◽  
Zhe S. Chen
Keyword(s):  
Computational Model ◽  
Traveling Waves ◽  
Neural Activity ◽  
Traveling Wave ◽  
Network Connectivity ◽  
Wave Characteristics ◽  
Wave Patterns ◽  
Thalamocortical Network ◽  
Theoretical Insight ◽  
Insight Into

AbstractPropagation of neural activity in spatially structured neuronal networks has been observed in awake, anesthetized and sleeping brains. However, it remains unclear how traveling waves are coordinated temporally across recurrently connected brain structures, and how network connectivity affects spatiotemporal neural activity. Here we develop a computational model of a two-dimensional thalamocortical network that enables us to investigate traveling wave characteristics in space-time. We show that thalamocortical and intracortical network connectivity, excitation/inhibition balance, thalamocortical/corticothalamic delay can independently or jointly change the spatiotemporal patterns (radial, planar and rotating waves) and characteristics (speed, direction and frequency) of cortical and thalamic traveling waves. Simulations of our model further predict that increased thalamic inhibition induces slower cortical wave frequency, and enhanced cortical excitation increases cortical wave speed and oscillation frequencies. Overall, the model study provides not only theoretical insight into the basis for spatiotemporal wave patterns, but also experimental predictions that potentially control these dynamics.Author SummaryCognition or sensorimotor control requires the coordination of neural activity across widespread brain circuits. Propagating waves of oscillatory neural activities have been observed at both macroscopic and mesoscopic levels, with various frequencies, spatial coverage, and modalities. However, a complete understanding how thalamocortical traveling waves are originated and temporally coordinated in the thalamus and cortex are still unclear. Furthermore, it remains unknown how the network connectivity, excitation/inhibition balance, thalamocortical or corticothalamic delay determine the spatiotemporal wave patterns and characteristics of cortical and thalamic traveling waves. Here we develop a computational model of a two-dimensional thalamocortical network to investigate the thalamic and neocortical traveling wave characteristics in space-time, which allows us to quantitatively assess the impact of thalamocortical network properties on the formation and maintenance of complex traveling wave patterns. Our computational model provides strong theoretical insight into the basis of spatiotemporal wave propagation, as well as experimental predictions that control these wave dynamics.

scholarly journals The patterns of traveling wave on shallow water modeled by Green-Naghdi equation

2022 ◽  
Vol 355 ◽  
pp. 02005
Author(s):  
Haitong Wei
Keyword(s):  
Shallow Water ◽  
Traveling Wave ◽  
Water Waves ◽  
Travelling Wave ◽  
Periodic Patterns ◽  
Shallow Water Waves ◽  
Trial Equation Method ◽  
Wave Patterns ◽  
First Time

The Green-Naghdi equations are a shallow water waves model which play important roles in nonlinear wave fields. By using the trial equation method and the Complete discrimination system for the polynomial we obtained the classification of travelling wave patterns. Among those patterns, new singular patterns and double periodic patterns are obtained in the first time. And we draw the graphs which help us to understand the dynamics behaviors of the Green-Naghdi model intuitionally.

Topological stability and patterns of traveling wave for a micro-polar non-Newtonian fluid model

2021 ◽  
pp. 2150237
Author(s):  
Xin Wang
Keyword(s):  
Newtonian Fluid ◽  
Traveling Wave ◽  
Fluid Model ◽  
Polynomial Method ◽  
Topological Stability ◽  
Intrinsic Parameters ◽  
Dynamical Behaviors ◽  
Wave Patterns ◽  
Complete Discrimination System

A nonlinear micro-polar non-Newtonian fluid model is investigated. By the complete discrimination system for polynomial method, we give the classification of the traveling wave patterns and analysis of topological stability and dynamical behaviors. We also discuss the physical realizations and the conditions of existence of these patterns. As a result, when some of parameters are not intrinsic parameters we show that in general only two stable patterns will be observed.

scholarly journals Traveling Wave Patterns Reproduced by a Simple Model for Oil/water Interface

2010 ◽  
Vol 17 (2) ◽  
pp. 115-119 ◽  
Author(s):  
Youichi MORIMUNE ◽  
Takahiko SUGIYAMA ◽  
Takahiko BAN ◽  
Akihisa SHIOI ◽  
Takahiko SUGIYAMA
Keyword(s):  
Simple Model ◽  
Traveling Wave ◽  
Water Interface ◽  
Wave Patterns ◽  
Oil Water

Differential-flow-induced transition of traveling wave patterns and wave splitting

2016 ◽  
Vol 94 (4) ◽  
Author(s):  
Shyamolina Ghosh ◽  
Shibashis Paul ◽  
Deb Shankar Ray
Keyword(s):  
Traveling Wave ◽  
Differential Flow ◽  
Wave Splitting ◽  
Wave Patterns

Multistability and confined traveling-wave patterns in a convecting binary mixture

1987 ◽  
Vol 35 (6) ◽  
pp. 2757-2760 ◽  
Author(s):  
Elisha Moses ◽  
Jay Fineberg ◽  
Victor Steinberg
Keyword(s):  
Binary Mixture ◽  
Traveling Wave ◽  
Wave Patterns
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