Generalisation of Parseval's Theorem via Convolution Theorem

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The discussion focuses on the generalization of Parseval's theorem through the convolution theorem in the context of Fourier coefficients. The user explores the validity of expressing the integral of the fourth power of a function in terms of its Fourier coefficients, specifically questioning the application of convolution for powers of functions. They clarify that the manipulation is correct under convergence conditions and seek confirmation on whether to use discrete or continuous convolution. It is concluded that discrete convolution is equivalent to continuous convolution restricted to integers. The user appreciates any further insights on their initial manipulation.
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Homework Statement


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Suppose we have a 2\pi-periodic, integrable function f: \mathbb{R} \rightarrow \mathbb{C} whose Fourier coefficients are known. Parseval's theorem tells us that:

\sum_{n = -\infty}^{\infty}|\widehat{f(n)}|^2 = \frac{1}{2\pi}\int_{-\pi}^{\pi}|f(x)|^{2}dx,

where \widehat{f(n)} are the Fourier coefficients of f.

Suppose we instead want to replace f(x) with f(x)^{q}, say: then it would suffice to determine the Fourier coefficients of the q-th power of f. Is repeated application of the convolution theorem the usual way of finding powers of the Fourier coefficients of functions, where the Fourier coefficients of the original function are already known?

Homework Equations


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f \ast g denotes the convolution of f and g, given by (f \ast g)(t) := \int_{-\infty}^{\infty} f(\tau)g(t - \tau)d\tau, and \widehat{f \ast g} = \hat{f} \cdot \hat{g} is the convolution theorem for the Fourier transforms of f and g.

The Attempt at a Solution


Suppose that we are interested in \int_{-\pi}^{\pi}|f(x)|^{4} dx. I would like to know if it is valid to say the following:

\frac{1}{2\pi}\int_{-\pi}^{\pi}|f(x)|^{4}dx = \frac{1}{2\pi}\int_{-\pi}^{\pi}|(f(x))^{2}|^{2}dx = \sum_{n = -\infty}^{\infty} |\widehat{f(n)^{2}}|^{2} = \sum_{n = -\infty}^{\infty} | (\hat{f} \ast \hat{f})(n)|^{2}.

The reason I am interested in this is because I'm working on bounding a class of L^{p}-norms using the asymptotics of Fourier coefficients, and hoping to modify this slightly to integrate functions over a d-cube [0,2\pi)^d. This seems to be a complicated procedure however, since additional conditions need to be imposed on the functions to guarantee the convergence of the integral in \mathbb{R}^d.
 
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Thanks for the automated response. I posted the same question on MathSE, and was told that the manipulation is correct as long as everything converges, although one should note that the convolution is on \mathbb{Z} rather than on \mathbb{R}. The only question I have left is whether that means I should be using the discrete convolution, or if I should still be using the continuous convolution restricted to \mathbb{Z} (if such a thing exists).

EDIT: I've just realized that the discrete convolution is precisely the continuous convolution restricted to the integers, so the question for this post has been answered. However, if anyone has any comments about the manipulation in post #1, I would greatly appreciate hearing them.
 
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Question: A clock's minute hand has length 4 and its hour hand has length 3. What is the distance between the tips at the moment when it is increasing most rapidly?(Putnam Exam Question) Answer: Making assumption that both the hands moves at constant angular velocities, the answer is ## \sqrt{7} .## But don't you think this assumption is somewhat doubtful and wrong?

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