Fourier transform of integration measure (Peskin and Schroeder)

In summary, the author is considering only k^0_n > 0 as independent variables because of the Fourier transformation being a change of basis, and the unitarity of the transformation ensures that the two measures are equivalent.
  • #1
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At page 285 in Peskin and Schroeder's Introduction to quantum field theory the author defines the integration measure [itex]D\phi = \Pi_i d\phi(x_i)[/itex] where space-time is being discretised into a square lattice of volume L^4. He proceeds by Fourier-transforming

[tex] \phi(k_n) = \frac{1}{V} \sum_n e^{-i k_n \cdot x_i} \phi(k_n)[/tex]

and considering only [itex]k^0_n >0[/itex] as independent variables he concludes that since the Fourier transformation is unitary, the measure [itex]D\phi = \Pi_i d\phi(x_i)[/itex] can equivalently be expressed as (equation 9.22)

[tex] D\phi = \Pi_{k_n^0 > 0} d Re \phi(k_n) d I am \phi(k_n).[/tex]

Why is he only considering [itex]k^0_n >0[/itex] and how does he arrive at this conclusion? What is the relevance of the Fourier transform being unitary?
 
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  • #2
The author is considering only k^0_n > 0 because they are the independent variables. In order to understand why, it is helpful to look at the Fourier transformation as a change of basis from the x_i space to the k_n space. In this change of basis, some of the k_n may become dependent on each other, meaning that not all of them are independent variables. By considering only k^0_n > 0, the author is ensuring that he is only working with the independent variables.The relevance of the Fourier transform being unitary is that it ensures that the measure D\phi = \Pi_i d\phi(x_i) is equivalent to the measure D\phi = \Pi_{k_n^0 > 0} d Re \phi(k_n) d I am \phi(k_n). This is because the unitarity of the Fourier transformation means that the inverse transformation is the same as the forward transformation, which means that the two measures are equivalent.
 

1. What is the Fourier transform of an integration measure?

The Fourier transform of an integration measure is a mathematical tool that allows us to express a function in terms of its frequency components. It converts a function from its original representation in the time or spatial domain to a representation in the frequency domain.

2. How is the Fourier transform of an integration measure used in Peskin and Schroeder?

In Peskin and Schroeder, the Fourier transform of an integration measure is used to simplify the calculation of path integrals in quantum field theory. It allows us to express the path integral in terms of Fourier modes, making the calculations more manageable.

3. What are the key properties of the Fourier transform of an integration measure?

The key properties of the Fourier transform of an integration measure include linearity, translation, scaling, convolution, and inversion. These properties allow us to manipulate and simplify expressions involving Fourier transforms.

4. How does the Fourier transform of an integration measure relate to other mathematical concepts?

The Fourier transform of an integration measure is closely related to other mathematical concepts such as Fourier series, Fourier transforms of functions, and the Laplace transform. It is also connected to concepts in probability theory, such as characteristic functions and moment generating functions.

5. What are some applications of the Fourier transform of an integration measure?

The Fourier transform of an integration measure has various applications in physics, engineering, and mathematics. It is commonly used in signal processing, image processing, and data compression. It also has applications in quantum mechanics, optics, and electromagnetic theory.

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