Fourier transform field solutions

In summary: So, in this case, instead of just having one solution (\phi \left(x\right)) that depends on x, we have two solutions (\phi \left(x_1\right) and \phi \left(x_2\right)) that are both depending on x_1 and x_2.
  • #1
zwoodrow
34
0
I am learning about adv quantum and field theory and i have run across something unfamiliar mathematically. In several instances the author simpy expands the field or a wave function as a Fourier transform. that is they assume the field or wave function is simply the transform of two other functions. I took pde and Fourier analysis and this type of assumption never came up. I know it is a fact that non pathological functions can always be represented as a transform however It sounds like when ever you model any sort of wave trains in field theory the SOP is to just assume the field or wave function is the Fourier transform of two other functions. one function traveling in one direction and the other tranveling in the other direction. Can anyone point me to a quick overview of this type ot thinking. it makes sense to me i just have never seen it done. Also is there a deeper reason for doing this it seems like just an added complication to me.
 
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  • #2
When describing em radiation (light, etc.), it can be considered as a function of time. Taking the Fourier transform gives the frequency spectrum.
 
  • #3
mathman said:
When describing em radiation (light, etc.), it can be considered as a function of time. Taking the Fourier transform gives the frequency spectrum.

I'm not really sure that's what he's asking.

Pages 20-21 of Peskin and Schroeder go through this for the Klein-Gordon equation. The deeper reason is that the field, such as:
[TEX]
\phi \left(x\right) = \int \frac{d^3 p}{\left(2 \pi\right)^3} \frac{1}{\sqrt{2 \omega_p}} \left(a_p e^{i px} + a^{\dag}_p e^{-i px}] \right)
[/TEX]

I think he's asking why there are two terms, one for the positive solutions, one for the negative. The answer I believe is that instead of each solution existing by itself, we write it as an "independent oscillator" which contains its own creation and annihilation operators for creating and destroying states, and is a linear combination of the two separate states.

Remember back in differential equations that if two solutions to the same differential eq. are sin(kx) and cos(kx), we write the FULL solution as the linear combination of those two.
 

What is a Fourier transform field solution?

A Fourier transform field solution is a mathematical technique used to decompose a function into its individual frequency components. It is commonly used in signal processing, image analysis, and other scientific fields to analyze and manipulate data.

How does a Fourier transform field solution work?

A Fourier transform field solution works by breaking down a function into a sum of sinusoidal functions with different frequencies. This allows for the analysis of a function in terms of its frequency components, rather than just its amplitude over time.

What are the benefits of using a Fourier transform field solution?

Using a Fourier transform field solution allows for the simplification of complex functions, making them easier to analyze and manipulate. It also allows for the identification of specific frequency components within a function, which can be useful in understanding the underlying patterns and behaviors of the data.

What are some applications of Fourier transform field solutions?

Fourier transform field solutions are commonly used in fields such as signal processing, image analysis, and data compression. They are also used in physics, engineering, and other scientific fields to analyze and manipulate data.

Are there any limitations to using Fourier transform field solutions?

While Fourier transform field solutions are a powerful tool in data analysis, they do have some limitations. They assume that the function being analyzed is periodic and infinite, which may not always be the case in real-world data. Additionally, they may not accurately capture sudden changes or discontinuities in the data.

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