Approximate solutions to Kuramoto synchronization model

In summary, the Kuramoto Model, which describes the synchronization of oscillators, has governing equations that can be rewritten using a transformation. This transformation can also be used to assume a stationary solution and gain information about the system's behavior. The transformation into a rotating reference frame can simplify the equations and allow for the assumption that the average phase is always zero. However, this may be a limiting assumption and it may be beneficial to transform all angular variables to have an average of zero.
  • #1
Danny Boy
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According to the wiki entry 'Kuramoto Model', if we consider the ##N=2## case then the governing equations are $$\frac{d \theta_1}{dt} = \omega_i + \frac{K}{2}\sin(\theta_2 - \theta_1)~~~\text{and}~~~\frac{d \theta_2}{dt} = \omega_i + \frac{K}{2}\sin(\theta_1 - \theta_2),$$
where ##\theta_i## are the phases of the oscillator, ##\omega_i## are the natural frequencies and $K$ is the coupling constant.

To find solutions I then propose (as in the wiki entry) using the transformation ##re^{i \psi} = \frac{1}{2}(e^{i \theta_1} + e^{i \theta_2})##. Thus allowing us to rewrite the coupled equations as $$\frac{d \theta_i}{dt} = \omega_i + Kr\sin(\psi - \theta_i)~~~~~~~\text{for }i = 1,2~~~~~~~~(1)$$
If we further assume the statistical averages of phases is zero (i.e. ##\psi = 0##), the governing equations then become $$\frac{d \theta_i}{dt} = \omega_i -Kr \sin(\theta_i).~~~~~~~~~~~~~~~~~~(2)$$

Questions:

- Am I correct in stating that ##\psi=0## assumption is quite limiting in that as ##\psi## is also a function of time ##t##, hence even if ##\psi(0) = 0## it does not necessarily imply that ##\psi(t) = 0##?

- What would be a feasible recommended approximation method to attempt to solve the type of ODE in (1)?

Thanks for any assistance.
 
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  • #2
Yes, setting ##\psi(t)=0## without any other changes seems pretty limiting to me. However, I think it might be more reasonable to transform all of the angular variables (i.e., the ##\theta_i##'s and ##\psi##) in such a way that they all start at zero, and such that the sum/average of the ##\omega_i##'s is zero. Since ##\psi## is sort of an average of the angular variables, ##\psi(t)=0## might not be such a bad approximation after such a transformation.

I think that looking for stationary solutions and then expanding about them in configuration or phase space is typically a good way to gain some information on the behavior of a non-linear system of ODEs.
 
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Likes Danny Boy
  • #3
@IsometricPion Thanks for your response and recommendations. I think the ##\psi(t) = 0## follows from transforming into a rotating reference frame where it rotates such that the average phase is always zero. Hence I think part of my misunderstanding was that I was still thinking in terms of the non-rotating inertial reference frame. It is interesting how little the equations change after the transformation into a rotating reference frame (it goes from ##\frac{d \theta_i}{dt} = \omega_i + Kr\sin(\psi - \theta_i)## to ##\frac{d \theta_i}{dt} = \omega_i -Kr \sin(\theta_i)##).
 

1. What is the Kuramoto synchronization model?

The Kuramoto synchronization model is a mathematical model used to study synchronization in a network of coupled oscillators. It was proposed by Yoshiki Kuramoto in 1975 and has since been widely studied in various fields such as physics, biology, and engineering.

2. What are approximate solutions to the Kuramoto synchronization model?

Approximate solutions to the Kuramoto synchronization model are mathematical approximations that aim to describe the behavior of the system without solving the full equations. These solutions are often simpler and easier to analyze, making them useful for understanding the dynamics of synchronization in complex systems.

3. How are approximate solutions to the Kuramoto synchronization model derived?

Approximate solutions to the Kuramoto synchronization model are derived using various mathematical techniques such as perturbation theory, mean-field approximation, and numerical simulations. These methods involve simplifying the equations and making assumptions about the system to obtain an approximate solution.

4. What are the limitations of approximate solutions to the Kuramoto synchronization model?

Approximate solutions to the Kuramoto synchronization model are based on simplifications and assumptions, which may not accurately reflect the behavior of the actual system. Therefore, these solutions may have limitations in predicting the dynamics of synchronization in real-world systems.

5. How are approximate solutions to the Kuramoto synchronization model useful in research?

Approximate solutions to the Kuramoto synchronization model are useful in research as they provide insights into the behavior of complex systems. They can also serve as a starting point for further analysis and can help researchers understand the underlying mechanisms of synchronization in various fields.

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