Fourier transformation on discrete function

In summary, the conversation is about the application of Fourier transformation in physics, specifically transforming a position-dependent function to a k-dependent function. The question is if it is possible to obtain a function in momentum, p, from a discrete function in k using the discrete Fourier transformation. The suggestion is to look into the discrete time Fourier transform.
  • #1
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Hi there,
I am reading a material on the application of Fourier transformation in physics. One application is to transform the position-dependent function to k-dependent function, i.e.## F(k) = FFT[f(x)]##

We know that the in physics, the wavenumber could be written in momentum as ##k=p/\hbar##. My question is if I have a discrete function

##f(x) = {f_0, f_1, ... f_{N-1}, f_N}##

which doesn't have close form but just given by a simulation. If I do the discrete Fourier transformation, I can have the discrete ##F(k)## but is that any way to obtain ##F(p)## from ##F(k)##?
 
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  • #2
Thanks for the post! Sorry you aren't generating responses at the moment. Do you have any further information, come to any new conclusions or is it possible to reword the post?
 
  • #3
It is possible to take a continuous FT of a function of a discrete variable. Look up the DTFT, "discrete time Fourier transform."
 

Related to Fourier transformation on discrete function

1. What is a Fourier transformation on discrete function?

A Fourier transformation on discrete function is a mathematical technique that decomposes a discrete function into its constituent frequencies. It is named after French mathematician Joseph Fourier and is commonly used in signal processing and data analysis.

2. How is a Fourier transformation on discrete function different from a Fourier transformation on continuous function?

A Fourier transformation on discrete function operates on a sequence of discrete data points, while a Fourier transformation on continuous function operates on a continuous function. This means that the input data in a discrete Fourier transformation is a set of numbers, while the input data in a continuous Fourier transformation is a mathematical function.

3. What is the purpose of using a Fourier transformation on discrete function?

The purpose of using a Fourier transformation on discrete function is to analyze the frequencies present in a given data set. This can help in identifying patterns, trends, and anomalies in the data, and is commonly used in fields such as signal processing, image processing, and data compression.

4. How does a computer perform a Fourier transformation on discrete function?

A computer performs a Fourier transformation on discrete function using an algorithm called the Fast Fourier Transform (FFT). This algorithm reduces the computational complexity of the transformation from O(n^2) to O(nlogn), making it more efficient and practical for real-world applications.

5. Can a Fourier transformation on discrete function be reversed?

Yes, a Fourier transformation on discrete function can be reversed using the inverse Fourier transformation. This operation reconstructs the original discrete function from its frequency components, and is used in applications such as data synthesis and noise filtering.

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