On pointwise convergence of Fourier series

In summary, the paper discusses the concept of pointwise convergence of Fourier series, examining the conditions under which the Fourier series of a function converges to the function itself at individual points. It highlights the significance of Dirichlet conditions, the role of continuity, and the implications of the Riemann-Lebesgue lemma. The document also explores examples and counterexamples to illustrate the nuances of convergence, ultimately emphasizing the importance of understanding the behavior of Fourier series in various contexts of mathematical analysis.
  • #1
psie
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Homework Statement
Compute the Fourier series of $$f(t)=\begin{cases} t+\pi &-\pi <t<0\\ 0&0\le t\le \pi. \end{cases}$$ and find the sum of ##\sum_{n=1}^\infty \frac1{(2n-1)^2}##.
Relevant Equations
There is the following theorem in this section of the book; suppose that ##f## has period ##2\pi##, and suppose that ##t_0## is a point where ##f## has one-sided limiting values and (generalized) one-sided derivatives. Then the Fourier series of ##f## converges for ##t=t_0## to the mean value ##\frac12(f(t_0+)+f(t_0-))##. In particular, if ##f## is continuous at ##t_0##, the sum of the series equals ##f(t_0)##.
So, the function is piecewise continuous (and differentiable), with (generalized) one-sided derivatives existing at the points of discontinuity. Hence I conclude from the theorem that the series converges pointwise for all ##t## to the function ##f##.

I've double checked with WolframAlpha that the coefficients are \begin{align} c_0&=\frac{\pi}{4} \nonumber \\ c_{2n}&=\frac{i}{4n}, \ n\neq0 \nonumber \\ c_{2n+1}&=\frac{i}{2(2n+1)}+\frac{1}{\pi(2n+1)^2}. \nonumber \end{align} Now, we have ##\sum_{n\in\mathbb Z} c_ne^{int}##, and I proceed with the following computation \begin{align} \sum_{n\in\mathbb Z} c_ne^{int}&=c_0+\sum_{\substack{n\in\mathbb Z \\ n\neq0}} c_{2n}e^{i2nt}+\sum_{n\in\mathbb Z}c_{2n+1}e^{i(2n+1)t} \tag1 \\ &=\frac{\pi}{4}+\sum_{\substack{n\in\mathbb Z \\ n\neq0}} \frac{i}{4n}e^{i2nt}+\sum_{n\in\mathbb Z } \left(\frac{i}{2(2n+1)}+\frac{1}{\pi(2n+1)^2}\right)e^{i(2n+1)t} \nonumber \\ &=\frac{\pi}{4}-\sum_{n=1}^\infty\frac{\sin(2n)t}{2n}-\sum_{n=0}^\infty \frac{\sin(2n+1)t}{2n+1}+\frac{2}{\pi}\sum_{n=0}^\infty\frac{\cos(2n+1)t}{(2n+1)^2}\nonumber \\ &= \frac{\pi}{4}-\sum_{n=1}^\infty\frac{\sin nt}{n}+\frac{2}{\pi}\sum_{n=1}^\infty\frac{\cos(2n-1)t}{(2n-1)^2}\nonumber. \end{align} To evaluate the sum in the problem, I set ##t=0## and keep in mind that this is a discontinuous point. I get $$\frac12(f(0+)-f(0-))=\frac{\pi}{2}=\frac{\pi}{4}+\frac{2}{\pi}\sum_{k=1}^\infty \frac1{(2n-1)^2},$$ i.e. ##\sum_{k=1}^\infty \frac1{(2n-1)^2}=\frac{\pi^2}{8}##.

I'm doubting my own computation though. The equality in ##(1)##, when we split the sum into even and odd indexed sums, doesn't this require absolute convergence of the series?
 
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  • #2
What does you text tell you about how to take the double limit [tex]\sum_{n \in \mathbb{Z}} c_ne^{inx} =
\lim_{M \to \infty}\lim_{N \to \infty} \sum_{n=-M}^{N} c_{n}e^{inx}?[/tex] If you are to assume [itex]M = N[/itex] then this procedure is justified: all the necessary terms appear in the partial sum.
 
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  • #3
pasmith said:
What does you text tell you about how to take the double limit [tex]\sum_{n \in \mathbb{Z}} c_ne^{inx} =
\lim_{M \to \infty}\lim_{N \to \infty} \sum_{n=-M}^{N} c_{n}e^{inx}?[/tex] If you are to assume [itex]M = N[/itex] then this procedure is justified: all the necessary terms appear in the partial sum.
Yes, ##M=N## is the definition in my book. Are you saying that if the right-hand side converges (at least pointwise) in $$\sum_{n=-N}^{N}c_ne^{inx}=c_0+\sum_{\substack{n=-N \\ n \text{ even}}}^N c_{n}e^{inx}+\sum_{\substack{n=-N \\ n \text{ odd}}}^N c_{n}e^{inx},$$ then we can split the sum (technically rearrange it) into sums of even and odd indexed terms? I know it holds for positive series indexed by ##\mathbb N##, but I'm not sure if it holds for alternating, possibly complex, series indexed by ##\mathbb Z##.

If the answer is yes, I assume this follow from the limit law, where ##s_n=a_n+b_n## and ##\lim_{n\to\infty} a_n, \ \lim_{n\to\infty} b_n## both exist, then $$\lim_{n\to\infty} s_n=\lim_{n\to\infty} (a_n+b_n)=\lim_{n\to\infty} a_n+\lim_{n\to\infty} b_n.$$
 
  • #4
psie said:
Yes, ##M=N## is the definition in my book. Are you saying that if the right-hand side converges (at least pointwise) in $$\sum_{n=-N}^{N}c_ne^{inx}=c_0+\sum_{\substack{n=-N \\ n \text{ even}}}^N c_{n}e^{inx}+\sum_{\substack{n=-N \\ n \text{ odd}}}^N c_{n}e^{inx},$$ then we can split the sum (technically rearrange it) into sums of even and odd indexed terms? I know it holds for positive series indexed by ##\mathbb N##, but I'm not sure if it holds for alternating, possibly complex, series indexed by ##\mathbb Z##.

You can't do [tex]
\lim_{N \to \infty} \sum_{n=-N}^N a_n = \lim_{N \to \infty} \sum_{\substack{n=-N \\ n \text{ odd}}}^N a_n + \lim_{N \to \infty} \sum_{\substack{n=-N \\ n \text{ even}}}^N a_n[/tex] because it involves taking all even terms before (or after) all odd terms, and that is only justified if the series is absolutely convergent. You can, of course, omit from the sum any term which is zero.

(Take care when indexing odd and even terms separately. You need the index to be symmetric about zero, so taking the even term as [itex]n = 2k[/itex] is fine since [itex]-2k = 2(-k)[/itex], but taking the odd term as [itex]n = 2k+1[/itex] is not since [itex]-(2k+1) \neq 2(-k) + 1[/itex]. The index [itex]n = (-1)^k(2|k| - 1)[/itex] for [itex]|k| \geq 1[/itex] does have this property.)

If the answer is yes, I assume this follow from the limit law, where ##s_n=a_n+b_n## and ##\lim_{n\to\infty} a_n, \ \lim_{n\to\infty} b_n## both exist, then $$\lim_{n\to\infty} s_n=\lim_{n\to\infty} (a_n+b_n)=\lim_{n\to\infty} a_n+\lim_{n\to\infty} b_n.$$
This theorem only applies if [itex]\lim a_n[/itex] and [itex]\lim b_n[/itex] exist separately; here they do not.

What you can do is [tex]
\lim_{N \to \infty} \sum_{n=-N}^N c_ne^{int} = c_0 + \lim_{N \to \infty}\sum_{n=1}^N ((c_n + c_{-n})\cos nt + i(c_n - c_{-n})\sin nt).[/tex] Now if [itex]f[/itex] is real then [itex]c_n[/itex] and [itex]c_{-n}[/itex] are complex conjugates, so this reduces to [tex]
c_0 + \lim_{N \to \infty} \sum_{n=1}^N (2\Re(c_n) \cos nt - 2\Im(c_n)\sin nt).[/tex] Setting [itex]t = 0[/itex] makes the sine terms vanish, and [itex]\Re(c_n)[/itex] vanishes for even [itex]n[/itex] so we are justified in writing this as [tex]
\tfrac12 (f(0^{+}) + f(0^{-})) = c_0 + \lim_{K \to \infty} \sum_{k=1}^K 2\Re(c_{2k - 1}).[/tex]
 
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FAQ: On pointwise convergence of Fourier series

What is pointwise convergence of Fourier series?

Pointwise convergence of Fourier series refers to the property where the Fourier series of a function converges to the function itself at each individual point. Mathematically, for a function \( f(x) \) and its Fourier series \( S_N(x) \), pointwise convergence means \( \lim_{N \to \infty} S_N(x) = f(x) \) for each \( x \) in the domain of \( f \).

What conditions ensure the pointwise convergence of a Fourier series?

Several conditions can ensure the pointwise convergence of a Fourier series. One of the most well-known is the Dirichlet conditions, which state that if a function is periodic, piecewise continuous, and has a finite number of discontinuities and extrema in one period, then its Fourier series converges pointwise to the function at points of continuity and to the average of the left-hand and right-hand limits at points of discontinuity.

What is the difference between pointwise convergence and uniform convergence of Fourier series?

Pointwise convergence means that the Fourier series converges to the function at each individual point, whereas uniform convergence means that the Fourier series converges to the function uniformly over the entire domain. Uniform convergence implies pointwise convergence, but the converse is not necessarily true. For uniform convergence, the difference between the function and its Fourier series can be made arbitrarily small simultaneously for all points in the domain.

How does the Gibbs phenomenon relate to pointwise convergence of Fourier series?

The Gibbs phenomenon refers to the overshoot (or undershoot) that occurs near a jump discontinuity in the partial sums of the Fourier series of a function. Despite this overshoot, the Fourier series still converges pointwise to the function at most points, except exactly at the discontinuity where it converges to the average of the left-hand and right-hand limits. The Gibbs phenomenon is a manifestation of the pointwise convergence behavior near discontinuities.

Can a Fourier series converge pointwise to a function that is not continuous?

Yes, a Fourier series can converge pointwise to a function that is not continuous. The Fourier series of a piecewise continuous function with a finite number of discontinuities will converge pointwise to the function at points of continuity and to the average of the left-hand and right-hand limits at points of discontinuity. This is consistent with the Dirichlet conditions for pointwise convergence.

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