Fourier transform equation question

In summary: Any function that goes to zero sufficiently fast at infinity is a valid function in the domain of the Fourier transform. In summary, the conversation discusses the solution to a QFT homework problem that involves proving a given integral identity. By using the fact that the integrand is a total derivative and assuming the function goes to zero sufficiently fast at infinity, it can be shown that the first term on the right-hand side of the second equation is equal to zero.
  • #1
Fosheimdet
15
2
In my QFT homework I was asked to prove that $$\int d^3x \int \frac{d^3k}{(2\pi)^3} e^{i\mathbf{k} \cdot (\mathbf{x} - \mathbf{y})} k_j f(\mathbf{x}) = i \frac{df}{dx_j}(\mathbf{y}) $$

Using ##\frac{\partial e^{i\mathbf{k} \cdot (\mathbf{x} - \mathbf{y})}}{\partial x^j} = i k_j e^{i\mathbf{k} \cdot (\mathbf{x} - \mathbf{y})}##, the solution is as follows

$$\int d^3x \int \frac{d^3k}{(2\pi)^3} e^{i\mathbf{k} \cdot (\mathbf{x} - \mathbf{y})} k_j f(\mathbf{x}) = -i \int d^3x \int \frac{d^3k}{(2\pi)^3} \frac{\partial e^{i\mathbf{k} \cdot (\mathbf{x} - \mathbf{y})}}{\partial x^j} f(\mathbf{x}) $$

$$ = -i \int d^3x \int \frac{d^3k}{(2\pi)^3} \left( \frac{\partial}{\partial x^j} (e^{i\mathbf{k} \cdot (\mathbf{x} - \mathbf{y})}f(\mathbf{x}) ) - \frac{\partial f(\mathbf x)}{\partial x^j} e^{i\mathbf k \cdot (\mathbf x - \mathbf y)}\right) $$

$$ = i \int d^3x \frac{\partial f(\mathbf x) }{\partial x^j} \int \frac{d^3k}{(2\pi)^3} e^{i\mathbf k \cdot (\mathbf x - \mathbf y)} $$

$$= i \int d^3x \frac{\partial f(\mathbf x)}{\partial x^j} \delta^{(3)}(\mathbf x - \mathbf y) = i \frac{\partial f(\mathbf x)}{\partial x^j} \bigg|_{\mathbf x = \mathbf y}$$

I don't understand what happened to the first term on the RHS of the second equation. Why is ##-i\int d^3x \int \frac{d^3k}{(2\pi)^3} \frac{\partial}{\partial x^j} (e^{i\mathbf{k} \cdot (\mathbf{x} - \mathbf{y})}f(\mathbf{x}))=0?##
 
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  • #2
It is a total derivative and the function is assumed to go to zero sufficiently fast at infinity.
 
  • #3
Orodruin said:
It is a total derivative and the function is assumed to go to zero sufficiently fast at infinity.
How is it a total derivative though? Isn't ##\frac {\partial}{\partial x^j}## a partial derivative? Also, why can you make the assumption that the function goes to zero at infinity?
 
  • #4
Being a total derivative does not prevent being a partial derivative. It just means that the integrand is a derivative of some function.

An assumption is an assumption. We typically choose to work with such functions. It is related to the domain of the Fourier transform.
 

1. What is the Fourier transform equation?

The Fourier transform equation is a mathematical formula that represents a signal or function in terms of its frequency components. It is used to convert a signal from its original domain (such as time or space) to a representation in the frequency domain.

2. How is the Fourier transform equation used in science?

The Fourier transform equation is used in various fields of science, including physics, engineering, and mathematics. It is particularly useful in analyzing and understanding complex signals and systems, such as in signal processing, image processing, and quantum mechanics.

3. What is the difference between the Fourier transform and the inverse Fourier transform?

The Fourier transform and the inverse Fourier transform are mathematical operations that are inverses of each other. The Fourier transform converts a signal from its original domain to the frequency domain, while the inverse Fourier transform converts it back to its original domain.

4. What are the applications of the Fourier transform equation?

The Fourier transform equation has many applications in science and engineering. It is used in image and signal processing, data compression, spectral analysis, and solving differential equations, among others.

5. Are there any limitations to the Fourier transform equation?

While the Fourier transform equation is a powerful tool, it does have some limitations. It assumes that the signal is periodic and infinite, which may not always be the case in real-world applications. It also cannot accurately represent signals with sharp discontinuities or sudden changes.

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