Coupled differential equations with convolution and correlation

In summary, the conversation discusses two equations involving partial derivatives and integrals, which represent the behavior of two fields (optical frequency and THz frequency components) in terms of propagation distance. The equations also involve parameters such as magnetic permeability and effective nonlinear optical coefficient. The individual is seeking help with solving the equations using the Runge-Kutta method.
  • #1
schulzy
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Homework Statement



I have two equations:
[tex]\frac{\partial}{\partial z}E_{L}\left(z,\omega \right) = i \frac{2 \mu d_{eff}(\omega+\omega_{0})^{2}}{k(\omega+\omega_{0})}\int E_{L}(z,\omega-\omega_{T})E_{T}(z,\omega_{T})d\omega_{T}[/tex]
[tex]\frac{\partial}{\partial z}E_{T}\left(z,\omega_{T} \right) = i \frac{\mu d_{eff}\omega_{T}^{2}}{2k(\omega_{T})}\int E_{L}(z,\omega+\omega_{T})E_{T}^{*}(z,\omega)d\omega[/tex]


Homework Equations


[tex]\mu[/tex] is the magnetic permeability
k is the real wave vectors at respective frequencies, which are determined by the dispersion relation
[tex]d_{eff}[/tex] is the effective nonlinear optical coefficient.
[tex]E_{L}(z,\omega)[/tex] optical frequency component [tex]E_{T}(z,\omega_{T})[/tex] THz frequency components.


The Attempt at a Solution



I tied solve this equations whit Runge- Kutta method, but I think, I ruined something. I attached my MATLAB solution.
Where I may have ruined it?
 

Attachments

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  • #2
§§ COMUpdateI added more information:I have two equations:\frac{\partial}{\partial z}E_{L}\left(z,\omega \right) = i \frac{2 \mu d_{eff}(\omega+\omega_{0})^{2}}{k(\omega+\omega_{0})}\int E_{L}(z,\omega-\omega_{T})E_{T}(z,\omega_{T})d\omega_{T} \frac{\partial}{\partial z}E_{T}\left(z,\omega_{T} \right) = i \frac{\mu d_{eff}\omega_{T}^{2}}{2k(\omega_{T})}\int E_{L}(z,\omega+\omega_{T})E_{T}^{*}(z,\omega)d\omega The parameters are: \mu is the magnetic permeabilityk is the real wave vectors at respective frequencies, which are determined by the dispersion relationd_{eff} is the effective nonlinear optical coefficient.E_{L}(z,\omega) optical frequency component E_{T}(z,\omega_{T}) THz frequency components.My goal is to solve these two coupled equations with initial conditions and boundary conditions. I want to solve the equations for the two fields E_{L}(z,\omega) and E_{T}(z,\omega_{T}) as a function of the propagation distance z. I tried to solve this equations with Runge- Kutta method, but I think, I ruined something. I attached my MATLAB solution. Where I may have ruined it?
 

1. What are coupled differential equations?

Coupled differential equations are a set of equations that are interconnected and have interdependent variables. This means that the solutions to the equations are dependent on each other and cannot be solved independently.

2. What is convolution in the context of differential equations?

In differential equations, convolution is a mathematical operation that combines two functions to create a third function. It is used to solve certain types of differential equations, particularly those involving impulse functions.

3. What is correlation in the context of differential equations?

Correlation in differential equations refers to the relationship between two variables, where changes in one variable affect the changes in the other variable. It is often used to study how one variable influences the behavior of another in a system described by differential equations.

4. How are convolution and correlation related in differential equations?

In differential equations, convolution and correlation are closely related as they both involve combining functions to solve equations. Convolution is often used to solve equations with impulse functions, while correlation is used to study the relationship between variables in a system described by differential equations.

5. What are some real-world applications of coupled differential equations with convolution and correlation?

Coupled differential equations with convolution and correlation have many practical applications, such as in physics, engineering, and biology. They can be used to model and analyze systems with interdependent variables, such as chemical reactions, electrical circuits, and population dynamics.

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