Fourier Transform of propagators

Delta-1}}\right)Integrating over x_0 using the residue theorem, we obtain the final result:In summary, the spectral density of a QFT can be computed by taking the Fourier transform of the given expression and using the residue theorem to perform the necessary integrations. For the case of \Delta = 1, the result is \rho(p) \propto \delta(p^2) \theta(p_0). For \Delta \neq 1, the result is given by the complicated expression involving the sum and the gamma function. However
  • #1
L0r3n20
36
2
I've been assigned the following homework:
I have to compute the spectral density of a QFT and in order to do so I have to compute Fourier tranform of the following quantity (in Minkowsky signature, mostly minus)

[itex]\rho\left(p\right) = \int \frac{1}{\left(-x^2 + i \epsilon x_0\right)^{\Delta}} e^{i p \cdot x} d^4 x [/itex]

Using residual theorem I've been able to compute exactly the case for [itex]\Delta = 1[/itex] and it turns out to be [itex] \rho(p) \propto \delta(p^2) \theta(p_0) [/itex] .
For the case [itex]\Delta \neq 1[/itex] it's a bit tricky but I managed to perform the integration over [itex]x_0[/itex] using the residual once again and I found ([itex] r^2 = x_i x^i [/itex])

[itex]\sum_{k=0}^{\Delta -1} {\Delta-1 \choose k} (i p_0)^k \frac{\Gamma(\Delta -1 - k)}{\Gamma(\Delta)^2} \frac{1}{(2 r)^{2 \Delta+1-k}} \left(e^{i p_0 r} + (-1)^{2 \Delta -1 - k} e^{-i p_0 r}\right)[/itex]

Probably something is wrong since when I perform the remaining integrations (in spherical coordinates) I do not recover the following result:

[itex] \rho\left(p\right) = \frac{\Delta -1}{4^{\Delta} \Gamma(\Delta)^2} \theta(p_0) \delta(p^2) (p^2)^{\Delta -2} [/itex]
Any help would be great.
 
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  • #2
To compute the Fourier transform of the given expression, use the following equation:F[\rho(p)] = \int_{-\infty}^{\infty} \frac{1}{\left(-x^2 + i \epsilon x_0\right)^{\Delta}} e^{i p \cdot x} d^4 x Using integration by parts, we can rewrite the equation as:F[\rho(p)] = -\frac{i}{2\pi} \int_{-\infty}^{\infty} \frac{d^4 x}{\left(-x^2 + i \epsilon x_0\right)^{\Delta-1}} \partial_\mu e^{i p \cdot x} d^4 x Substituting in the definition of the Fourier transform, we obtain:F[\rho(p)] = -\frac{i}{2\pi} \int_{-\infty}^{\infty} \partial_\mu F[e^{i p \cdot x}] d^4 x Using integration by parts once again, we obtain:F[\rho(p)] = \frac{1}{2\pi} \int_{-\infty}^{\infty} F[e^{i p \cdot x}] \partial_\mu \left(\frac{1}{\left(-x^2 + i \epsilon x_0\right)^{\Delta-1}}\right) d^4 x The Fourier transform of the exponential is well known and can be computed as follows:F[e^{i p \cdot x}] = (2\pi)^4 \delta(p^2) \theta(p_0)Substituting this into our expression for the Fourier transform of \rho(p), we obtain:F[\rho(p)] = \frac{1}{2\pi} (2\pi)^4 \delta(p^2) \
 

Related to Fourier Transform of propagators

1. What is a Fourier Transform of propagators?

The Fourier Transform of propagators is a mathematical operation that transforms a function of time into a function of frequency. It is commonly used in physics and engineering to analyze and understand the behavior of waves and signals.

2. What is the significance of Fourier Transform of propagators?

The significance of Fourier Transform of propagators lies in its ability to break down a complex function into its individual frequency components, providing insight into the underlying behavior of the system. It is also used in various applications such as signal processing, image analysis, and quantum mechanics.

3. How is the Fourier Transform of propagators calculated?

The Fourier Transform of propagators is calculated by using a mathematical formula that involves integrating the function over all time and multiplying it by a complex exponential function. This process can be done analytically or numerically using various software tools.

4. What are some applications of Fourier Transform of propagators in science?

The Fourier Transform of propagators has numerous applications in science, including signal processing, image analysis, quantum mechanics, and more. In quantum mechanics, it is used to study the behavior of particles and systems, while in signal processing, it is used to extract useful information from signals. It is also used in various imaging techniques such as MRI and CT scans.

5. Are there any limitations to using Fourier Transform of propagators?

While Fourier Transform of propagators is a powerful tool, it does have some limitations. It assumes that the function being transformed is continuous and infinite, which may not always be the case in real-world applications. Additionally, it requires a good understanding of mathematical concepts and may be challenging for those without a strong mathematical background.

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