Partial Integro-Differential Equation

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In summary, the conversation discusses solving a complex equation involving partial derivatives and distribution functions. The solution must also be normalizable and meet certain boundary conditions, such as 100% specular reflection. Specific constants and functions are given for the equation.
  • #1
NeoDevin
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I need a little help solving an equation here, I don't really know where to start. If anyone has any advice on solving (or even simplifying) such a beast, it would be much appreciated.

[tex]\frac{\partial}{\partial t}N + \frac{1}{\tau}N = -a(t)\frac{\partial}{\partial u}N - u\frac{\partial}{\partial x}N -v\frac{\partial}{\partial y}N + \frac{1}{\tau}D(u,v)\int_{-\infty}^\infty\int_{-\infty}^\infty Ndudv[/tex]
Where
[tex]N = N(u,v,x,y,t)[/tex]

[itex]D(u,v)[/itex] Is a given normalized distribution function. I get to choose this, if you need a particular example, use:
[tex]D(u,v) = \frac{1}{2\pi v_{th}^2}e^{-(u^2+v^2)/2v_{th}^2}[/tex]

[tex]a(t) = A_0\cos(\omega t)[/tex]

[itex]A_0[/itex], [itex]v_{th}[/itex], and [itex]\tau[/itex] are all positive real constants.

And the solution [itex]N[/itex] must be normalizable over [itex]u[/itex] and [itex]v[/itex]
 
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  • #2
What would be the boundary conditions to model a boundary with 100% specular reflection?
 

1. What is a Partial Integro-Differential Equation (PIDE)?

A PIDE is a type of mathematical equation that combines elements of both partial differential equations (PDEs) and integral equations. It involves a function that depends on both the values of the function itself and its integral over a certain domain.

2. How is a PIDE different from a regular PDE?

A PIDE is different from a regular PDE because it also includes an integral term in addition to the usual partial derivatives. This makes it a more complex and challenging type of equation to solve, requiring specialized techniques and tools.

3. What are some real-world applications of PIDEs?

PIDEs have a wide range of applications in fields such as physics, engineering, and finance. They are commonly used to model diffusion processes, option pricing in financial markets, and population dynamics.

4. What are the challenges in solving PIDEs?

Solving PIDEs can be challenging because they often do not have analytical solutions and require numerical methods to approximate the solution. These methods can be computationally intensive and may not always provide accurate results.

5. How are PIDEs relevant to scientific research?

PIDEs are relevant to scientific research because they provide a more accurate and realistic way to model complex systems and phenomena. They allow scientists to take into account both local and global effects, making them a powerful tool in studying various natural and physical processes.

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