Fourier transform with complex variables

In summary, the conversation discusses a formula found in a paper, referred to as the Fourier transform of D. The interlocutors have not seen this notation before and are unsure of its common usage. They discuss its connection to the standard notations and how it can be interpreted as a 2D Fourier transform. They also mention its use in calculating the Wigner function of a density matrix. One of the interlocutors asks for clarification on the relationship between the Wigner function and the density matrix.
  • #1
naima
Gold Member
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I found this formula in a paper:
[tex]\int exp( \frac{x1 + i x2}{ \sqrt 2} \eta^* - \frac{x1 - i x2}{ \sqrt 2}
\eta) D(\eta)/ \pi d^2 \eta[/tex]
the author calls it the Fourier transform of D.
It is the first time thar i see this formula.
How common is this notation? Can we use it without problem?
 
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  • #2
I've not seen this notation before.

I tend to stick with the standard notations.
 
  • #3
I haven't seen this either - could you give us a reference?
 
  • #4
This part is especially confusing to me: ##D(\eta)/ \pi d^2 \eta##. I have no idea what it means.
 
  • #5
the link is here (eq 40):
http://arxiv.org/abs/quant-ph/0112110

I can follow a part of the calculus.with ##\eta = (q + ip)/ \sqrt 2##
we get ##\int \int exp(i (x_2 q - x_1 p)) D(q,p) dq dp##
So it would be twice a Fourier transform?
 
  • #6
When you define
$$
Z = \frac{x_1 + i x_2}{ \sqrt 2} \eta^*
$$
you can write
$$
\exp( \frac{x_1 + i x_2}{ \sqrt 2} \eta^* - \frac{x_1 - i x_2}{ \sqrt 2}\eta) = \exp( Z-Z^*) = \exp( 2i\Im[Z]) = \exp( 2i(-x_1\xi_2+x_2\xi_1)/\sqrt{2})
$$
justifying the calling of Fourier transform. In other words, it's just mathematical manipulation of the exponent
naima said:
So it would be twice a Fourier transform?
It's a 2D Fourier transform.
.
 
Last edited:
  • #7
I see here:
http://arxiv.org/abs/1510.02746
that the wigner function of a density matrix (with a Fourier transfom) can be written
##W_\rho(\alpha) = Tr [ \rho U(\alpha)]##
We will retrieve the density matrix with an inverse Fourier transform.
But i do not see why we have
##\rho = \int W(\alpha) U(\alpha) d \alpha## up to a ##2 \pi## coefficient
could you help me?
the second formula is in
http://arxiv.org/abs/quant-ph/0112110
 

Related to Fourier transform with complex variables

What is the Fourier transform with complex variables?

The Fourier transform with complex variables is a mathematical tool used to represent a function as a combination of complex exponential functions. It is an extension of the traditional Fourier transform, which represents a function as a combination of sine and cosine waves.

Why is the Fourier transform with complex variables important?

The Fourier transform with complex variables is important because it allows us to analyze and understand the frequency components of a complex function. It is used in many fields such as signal processing, image processing, and quantum mechanics.

How is the Fourier transform with complex variables different from the traditional Fourier transform?

The main difference between the two is that the Fourier transform with complex variables uses complex exponential functions while the traditional Fourier transform uses only real sine and cosine functions. This allows the complex Fourier transform to capture both amplitude and phase information of a function.

What are some applications of the Fourier transform with complex variables?

The Fourier transform with complex variables has many applications in science and engineering. It is used in signal processing to analyze and filter signals, in image processing to enhance and compress images, in quantum mechanics to describe the wave nature of particles, and in many other fields.

What are some important properties of the Fourier transform with complex variables?

Some important properties of the Fourier transform with complex variables include linearity, time and frequency shifting, convolution, and modulation. These properties allow for efficient and accurate analysis and manipulation of functions.

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