scholarly journals Partially Phase-Locked Solutions to the Kuramoto Model

2021 ◽  
Vol 183 (3) ◽  
Author(s):  
Jared C. Bronski ◽  
Lan Wang
Keyword(s):  
Kuramoto Model ◽  
The Kuramoto Model

scholarly journals Emulating the local Kuramoto model with an injection-locked photonic crystal laser array

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Naotomo Takemura ◽  
Kenta Takata ◽  
Masato Takiguchi ◽  
Masaya Notomi
Keyword(s):  
Photonic Crystal ◽  
Nearest Neighbor ◽  
Multiple Quantum Well ◽  
Kuramoto Model ◽  
Multiple Quantum ◽  
Laser Array ◽  
Novel Strategy ◽  
A Chain ◽  
The One ◽  
The Kuramoto Model

AbstractThe Kuramoto model is a mathematical model for describing the collective synchronization phenomena of coupled oscillators. We theoretically demonstrate that an array of coupled photonic crystal lasers emulates the Kuramoto model with non-delayed nearest-neighbor coupling (the local Kuramoto model). Our novel strategy employs indirect coupling between lasers via additional cold cavities. By installing cold cavities between laser cavities, we avoid the strong coupling of lasers and realize ideal mutual injection-locking with effective non-delayed dissipative coupling. First, after discussing the limit cycle interpretation of laser oscillation, we demonstrate the synchronization of two indirectly coupled lasers by numerically simulating coupled-mode equations. Second, by performing a phase reduction analysis, we show that laser dynamics in the proposed device can be mapped to the local Kuramoto model. Finally, we briefly demonstrate that a chain of indirectly coupled photonic crystal lasers actually emulates the one-dimensional local Kuramoto chain. We also argue that our proposed structure, which consists of periodically aligned cold cavities and laser cavities, will best be realized by using state-of-the-art buried multiple quantum well photonic crystals.

scholarly journals Emergent synchronous beating behavior in spontaneous beating cardiomyocyte clusters

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kazufumi Sakamoto ◽  
Yoshitsune Hondo ◽  
Naoki Takahashi ◽  
Yuhei Tanaka ◽  
Rikuto Sekine ◽  
...  
Keyword(s):  
Stem Cell ◽  
Embryonic Stem Cell ◽  
Human Embryonic Stem Cell ◽  
Single Cells ◽  
Embryonic Stem ◽  
Kuramoto Model ◽  
Distribution Analysis ◽  
Cell Clusters ◽  
Overdrive Suppression ◽  
The Kuramoto Model

AbstractWe investigated the dominant rule determining synchronization of beating intervals of cardiomyocytes after the clustering of mouse primary and human embryonic-stem-cell (hES)-derived cardiomyocytes. Cardiomyocyte clusters were formed in concave agarose cultivation chambers and their beating intervals were compared with those of dispersed isolated single cells. Distribution analysis revealed that the clusters’ synchronized interbeat intervals (IBIs) were longer than the majority of those of isolated single cells, which is against the conventional faster firing regulation or “overdrive suppression.” IBI distribution of the isolated individual cardiomyocytes acquired from the beating clusters also confirmed that the clusters’ IBI was longer than those of the majority of constituent cardiomyocytes. In the complementary experiment in which cell clusters were connected together and then separated again, two cardiomyocyte clusters having different IBIs were attached and synchronized to the longer IBIs than those of the two clusters’ original IBIs, and recovered to shorter IBIs after their separation. This is not only against overdrive suppression but also mathematical synchronization models, such as the Kuramoto model, in which synchronized beating becomes intermediate between the two clusters’ IBIs. These results suggest that emergent slower synchronous beating occurred in homogeneous cardiomyocyte clusters as a community effect of spontaneously beating cells.

scholarly journals Investigation of Preferred Orientations in Planar Polycrystals

2008 ◽  
Vol 75 (5) ◽  
Author(s):  
M. R. Tonks ◽  
A. J. Beaudoin ◽  
F. Schilder ◽  
D. A. Tortorelli
Keyword(s):  
Texture Evolution ◽  
Mean Field ◽  
Homogenization Method ◽  
Process Models ◽  
Kuramoto Model ◽  
Taylor Model ◽  
Crystal Plasticity Finite Element ◽  
Polycrystal Plasticity ◽  
Taylor Hypothesis ◽  
The Kuramoto Model

More accurate manufacturing process models come from better understanding of texture evolution and preferred orientations. We investigate the texture evolution in the simplified physical framework of a planar polycrystal with two slip systems used by Prantil et al. (1993, “An Analysis of Texture and Plastic Spin for Planar Polycrystal,” J. Mech. Phys. Solids, 41(8), pp. 1357–1382). In the planar polycrystal, the crystal orientations behave in a manner similar to that of a system of coupled oscillators represented by the Kuramoto model. The crystal plasticity finite element method and the stochastic Taylor model (STM), a stochastic method for mean-field polycrystal plasticity, predict the development of a steady-state texture not shown when employing the Taylor hypothesis. From this analysis, the STM appears to be a useful homogenization method when using representative standard deviations.

scholarly journals The Kuramoto model: A simple paradigm for synchronization phenomena

2005 ◽  
Vol 77 (1) ◽  
pp. 137-185 ◽  
Author(s):  
Juan A. Acebrón ◽  
L. L. Bonilla ◽  
Conrad J. Pérez Vicente ◽  
Félix Ritort ◽  
Renato Spigler
Keyword(s):  
Kuramoto Model ◽  
The Kuramoto Model

Dynamics of the Kuramoto Model with Bimodal Frequency Distribution on Complex Networks

2014 ◽  
Vol 31 (8) ◽  
pp. 080503
Author(s):  
Yue-E Feng ◽  
Hai-Hong Li ◽  
Jun-Zhong Yang
Keyword(s):  
Complex Networks ◽  
Frequency Distribution ◽  
Kuramoto Model ◽  
The Kuramoto Model

Volume Bounds for the Phase-Locking Region in the Kuramoto Model

2018 ◽  
Vol 17 (1) ◽  
pp. 128-156 ◽  
Author(s):  
Jared C. Bronski ◽  
Timothy Ferguson
Keyword(s):  
Phase Locking ◽  
Kuramoto Model ◽  
The Kuramoto Model

Epistemological Aspects of Simulation Models for Decision Support

2013 ◽  
Vol 5 (2) ◽  
pp. 55-77 ◽  
Author(s):  
Anthony H. Dekker
Keyword(s):  
Coupled Oscillators ◽  
True Belief ◽  
Simulation Models ◽  
Decision Makers ◽  
Kuramoto Model ◽  
Model Parameters ◽  
Theoretical Construct ◽  
Formal Definitions ◽  
Complex Models ◽  
The Kuramoto Model

In this paper, the author explores epistemological aspects of simulation with a particular focus on using simulations to provide recommendations to managers and other decision-makers. The author presents formal definitions of knowledge (as justified true belief) and of simulation. The author shows that a simple model, the Kuramoto model of coupled-oscillators, satisfies the simulation definition (and therefore generates knowledge) through a justified mapping from the real world. The author argues that, for more complex models, such a justified mapping requires three techniques: using an appropriate and justified theoretical construct; using appropriate and justified values for model parameters; and testing or other verification processes to ensure that the mapping is correctly defined. The author illustrates these three techniques with experiments and models from the literature, including the Long House Valley model of Axtell et al., the SAFTE model of sleep, and the Segregation model of Wilensky.

scholarly journals Critical synchronization dynamics of the Kuramoto model on connectome and small world graphs

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Géza Ódor ◽  
Jeffrey Kelling
Keyword(s):  
Control Parameter ◽  
Mean Field ◽  
Small World ◽  
Kuramoto Model ◽  
Crossover Point ◽  
Small World Graphs ◽  
Synchronization Phase ◽  
Experimental Values ◽  
The Kuramoto Model ◽  
Parameter Dependent

AbstractThe hypothesis, that cortical dynamics operates near criticality also suggests, that it exhibits universal critical exponents which marks the Kuramoto equation, a fundamental model for synchronization, as a prime candidate for an underlying universal model. Here, we determined the synchronization behavior of this model by solving it numerically on a large, weighted human connectome network, containing 836733 nodes, in an assumed homeostatic state. Since this graph has a topological dimension d < 4, a real synchronization phase transition is not possible in the thermodynamic limit, still we could locate a transition between partially synchronized and desynchronized states. At this crossover point we observe power-law–tailed synchronization durations, with τt ≃ 1.2(1), away from experimental values for the brain. For comparison, on a large two-dimensional lattice, having additional random, long-range links, we obtain a mean-field value: τt ≃ 1.6(1). However, below the transition of the connectome we found global coupling control-parameter dependent exponents 1 < τt ≤ 2, overlapping with the range of human brain experiments. We also studied the effects of random flipping of a small portion of link weights, mimicking a network with inhibitory interactions, and found similar results. The control-parameter dependent exponent suggests extended dynamical criticality below the transition point.

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