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Check that if \(f_{n}\) converges to \(f\) pointwise a.e. and if \(\sup _{n} \geqslant 1\left|f_{n}\right|^{2}\) is summable, then \(f_{n}\) also converges to \(f\) in \(\mathrm{L}^{2}(Q)\). Hint: Use dominated convergence. Step 3 (concluded): The proof of completeness can now be made. The problem is to check that if \(\left\|f_{n}-f_{m}\right\|\) tends to 0 as \(n\) and \(m \uparrow \infty\), then there is an actual function \(f \in \mathrm{L}^{2}(Q)\) such that $$ \lim _{n \dagger \infty}\left\|f_{n}-f\right\|=0 . $$ PROOF. The proof is a little more elaborate than the preceding one. The first take is to produce a plausible candidate for \(f\). Pick \(n_{1}

Short Answer

Expert verified
By the Dominated Convergence Theorem, \(f_n\) converges to \(f\) in \(L^2(Q)\).

Step by step solution

01

Setup the Problem

We need to prove that if a sequence of functions \(f_n\) converges pointwise almost everywhere to a function \(f\), and the supremum of \( |f_n|^2 \) is summable, then \(f_n\) converges to \(f\) in the \(L^2(Q)\) norm.
02

Apply the Dominated Convergence Theorem

To use the Dominated Convergence Theorem, identify a dominating function. In this case, \( g(x) = \sup_{n \geq 1} |f_n(x)|^2 \) is hypothesized to be summable given that it is independent of \( n \) and sums over the domain. Since \( g(x) \) is integrable over \(Q\), we can apply the theorem.
03

Ensure Convergence in \(L^2(Q)\)

Now, according to the Dominated Convergence Theorem, because \(f_n\) converges pointwise almost everywhere to \(f\) and \(g\) dominates \(|f_n|^2\), it follows that \[ \int_Q |f_n - f|^2 o 0 \]as \(n \to \infty\). Hence, \(f_n\) converges to \(f\) in the \(L^2(Q)\) norm.

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Key Concepts

These are the key concepts you need to understand to accurately answer the question.

Convergence of Functions
In mathematical analysis, understanding the concept of the convergence of functions is crucial. When we talk about convergence of a sequence of functions, we generally mean that as we consider more terms from the sequence, they increasingly resemble a particular function. Often, this involves approaching a specific value or shape, in terms of their properties, like continuity or integrability.

Convergence can happen in multiple ways depending on the context:
  • Pointwise Convergence: This is one of the simplest forms of convergence where each point individually converges to a finite value as the sequence progresses.
  • L2 Norm Convergence: This occurs when the functions get closer to each other in terms of energy or Euclidean global distance, specifically integrated-squared difference over the defined range.
Understanding these concepts is important in many fields such as engineering and physics. Convergence in different senses can tell us about the stability and accuracy of various engineered systems or mathematical models.
Pointwise Convergence
Pointwise convergence is a fundamental concept in calculus and analysis. It involves the convergence of functions at each individual point, as opposed to convergence over intervals or regions. When we say a sequence of functions \( f_n \) converges pointwise to a function \( f \), it means:
  • For every point \( x \) in the domain, as \( n \) increases, \( f_n(x) \) gets arbitrarily close to \( f(x) \).
An important distinction to understand is that pointwise convergence doesn't necessarily preserve properties like continuity or differentiability of the functions.

This convergence might lead to a limit function that lacks the original sequence's features, making it less smooth or more erratic.Thus, while useful, pointwise convergence necessitates understanding its limitations when analyzing the behavior of sequences.
L2 Space
The \(L^2(Q)\) space, also known as the space of square-integrable functions, is essential in functional analysis and quantum mechanics.It describes functions for which the square of the absolute value is integrable, meaning:
  • The integral \( \int_Q |f(x)|^2 \, dx \) is finite over the domain \( Q \).
This space is particularly important because the \(L^2\) norm provides a natural measure of the 'size' of a function, connecting directly to the concept of energy in physics.

One of the central properties in this space is the Hilbert Space structure, which equips it with properties such as completeness and orthogonality. Completeness here means that every Cauchy sequence in \(L^2\) has a limit that is also within \(L^2\).This feature is particularly useful because it guarantees that techniques like the Dominated Convergence Theorem (used in our exercise) can be applied effectively, ensuring convergence in a robust, precise manner over the space \(Q\).

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Most popular questions from this chapter

\( Check that if \)x \in Q-B\(, then \)f_{n j}(x)\( converges to a finite limit as \)j \uparrow \infty\(. Hint: \)\quad x \in Q-B\( means that \)\left|f_{n_{j+1}}(x)-f_{n j}(x)\right|<2^{-j / 3}\( for all sufficiently large \)j\(. By the Chebyshev inequality [Exercise 1.1.12], $$ m\left(A_{j}\right) \leqslant 2^{2 j / 3}\left\|f_{n_{j+1}}-f_{n_{j}}\right\|^{2} \leqslant 2^{-j / 3}, $$ and since this is the general term of a convergent sum, the Borel-Cantelli lemma, just before Exercise \)1.1 .11\( tells you that $$ m(B)=m\left(A_{j} \quad \text { i.o. }\right)=0 . $$ Therefore, $$ C=\left(x: f_{n j}(x) \text { fails to converge as } j \uparrow \infty\right) \subset B $$ is of measure 0 , too [see Exercise 10], and you can define a measurable function \)f\( by the rule $$ f(x)= \begin{cases}0 & \text { if } x \in C \\ \lim _{j \uparrow \infty} f_{n_{j}}(x) & \text { otherwise }\end{cases} $$ The claim is that \)f_{n}\( converges to this function \)f\( in \)\mathrm{L}^{2}(Q)\(. Because \)m(C)=0\(, \)f_{n}\(, converges to \)f\( pointwise a.e., and by Fatou's lemma $$ \begin{aligned} \left\|f_{n}-f\right\|^{2} &=\int_{Q} \lim _{j \uparrow \infty}\left|f_{n}-f_{n j}\right|^{2} \leqslant \liminf _{j \uparrow \infty} \int_{Q}\left|f_{n}-f_{n j}\right|^{2} \\ &=\liminf _{j \uparrow \infty}\left\|f_{n}-f_{n j}\right\|^{2} \leqslant 2^{-i} \quad \text { if } \quad n \geqslant n_{i} \end{aligned} $$ From this you learn two things: first, that \)f \in \mathrm{L}^{2}(Q)\(, since $$ \|f\| \leqslant\left\|f_{n_{1}}\right\|+\left\|f_{n_{1}}-f\right\| \leqslant\left\|f_{n_{1}}\right\|+2^{-1 / 2}<\infty, $$and second, that \)f_{n}\( approaches \)f\( in \)\mathrm{L}^{2}(Q)\( since \)2^{-i} \downarrow 0\( as \)i \uparrow \infty\(. The proof is finished. Step 4: Verify that \)\mathrm{L}^{2}(Q)\( is separable. This will finish the proof that it is a Hilbert space. The problem is to show that you can come as close as you please to any function \)f \in \mathrm{L}^{2}(Q)\( by functions from a fixed countable family \)K \subset L^{2}(Q)\(. Clearly, it suffices to deal with real functions. For any such function \)f\(, any integral \)i, j\(, and \)k \geqslant 1\(, let $$ \begin{aligned} &f_{1}=\left\\{\begin{array}{lll} f & \text { if } & |x| \leqslant i \\ 0 & \text { if } & |x|>i \end{array}\right. \\ &f_{2}= \begin{cases}f_{1} & \text { if }\left|f_{1}\right| \leqslant j \\ 0 & \text { if }\left|f_{1}\right|>j\end{cases} \end{aligned} $$ and $$ f_{3}=k^{-1}\left[k f_{2}\right], $$ in which \)[f]\( stands for the largest integer \)\leqslant f\(. Each of these functions is measurable and $$ \begin{aligned} \left\|f-f_{1}\right\|^{2} &=\int_{Q \cap(x ;|x|>i)}|f|^{2}, \\ \left\|f_{1}-f_{2}\right\|^{2} &=\int_{Q \cap\left(x:\left|f_{1}\right|>j\right)}\left|f_{1}\right|^{2} \leqslant \int_{Q \cap(x|| f \mid>j)}|f|^{2}, \\ \left\|f_{2}-f_{3}\right\|^{2} & \leqslant \int_{Q \cap(x:|x| \leqslant i)} k^{-2} \leqslant 2 i k^{-2}, \end{aligned} $$ so that you can make $$ \left\|f-f_{3}\right\| \leqslant\left\|f-f_{1}\right\|+\left\|f_{1}-f_{2}\right\|+\left\|f_{2}-f_{3}\right\| $$ as small as you like by taking \)i, j\(, and \)k\( large, in that order. Bring in the family \)K\( of piecewise constant functions \)f\(, which vanish far out, take rational values only, and jump only at a finite number of rational points. \)K\( is a countable subfamily of \)L^{2}(Q)\( and is closed under finite sums with rational coefficients. Now \)f_{3}=l / k\( on the set $$ A=Q \cap(x:|x| \leqslant i) \cap\left(x: l / k \leqslant f_{2}(x)<(l+1) / k\right), $$ so \)f_{3}\( is the sum (with coefficients \)l / k\( ) of indicator functions \)1_{A}\( of sets of measure \)\leqslant 2 i<\infty\(. Therefore, to finish the proof, you only have to check that such an indicator function can be well approximated by a function from \)K\(. By the recipe for Lebesgue measure of Section 1.1, you can cover such a set \)A\( by a countable family of intervals \)I_{k}\(, so closely as to make $$ 0 \leqslant \sum_{k=1}^{\infty} m\left(I_{k}\right)-m(A) $$ as small as you please. Especially, you can find a finite union \)B=\bigcup_{k=1}^{n} I_{k}\( so as to make $$ m(A-B)+m(B-A)=\int_{A-B} 1+\int_{B-A} 1=\left\|1_{A}-1_{B}\right\|^{2} $$ as small as you like, and you can even modify \)B\( to make the endpoints of the intervals rational, at the expense of a small change in \)\left\|1_{A}-1_{B}\right\| .\( But then \)1_{B} \in K$, and the proof is finished.

Show that any linear map \(l\) of \(L^{2}(Q)\) into the complex numbers which is bounded in the sense that $$ |l(f)| \leqslant \text { constant } \times\|f\| $$ where the constant is independent of \(f\), can be expressed as an inner product: $$ l(f)=(f, g) $$ for some \(g \in \mathrm{L}^{2}(Q)\). This is the so-called Riesz representation theorem. Hint. Suppose \(l \not \equiv 0\) and let \(\mathbf{A}=(f: l(f)=0)\). Check that \(\mathbf{B}=\mathbf{A}^{0}\) is of dimension 1 and find a function \(g \in L^{2}(Q)\) so that \(l(f)=0\) iff \((f, g)=0\). Then $$ l(f)=\|g\|^{-2} l(g)(f, g)=\text { constant } \times(f, g) $$ Why? There are many excellent books on Hilbert space; among the best at an advanced level are Akhiezer and Glazman [1961-1963] and Riesz and Sz.-Nagy \([1955] ;\) at an elementary level, Berberian \([1961]\) is recommended.

Check that if \(f_{1}, f_{2}, \ldots\) are real continuous functions on the line and if \(f=\lim _{n \uparrow \infty} f_{n}\) exists pointwise, then \((x: 0 \leqslant f(x)<1)\) is measurable. Hint: \((x: f(x)<1)=\bigcup_{k \geqslant 1} \bigcup_{m \geqslant 1} \bigcap_{n \geqslant m}\left(x: f_{n}(x) \leqslant 1-1 / k\right)\).

Check by example that the inclusion of \(L^{2}[0,1]\) in \({ }^{1}[0,1]\) is proper, that is, find a summable function \(f\) with \(\int_{0}^{1}|f|^{2}=\infty\).

Check that the space \(L^{1}(Q)\) is not a Hilbert space. Hint: In any Hilbert space \(\|\alpha+\beta\|^{2}+\|\alpha-\beta\|^{2}=2\|\alpha\|^{2}+2\|\beta\|^{2}\). Try this out for \(Q=[0,1], \alpha=1\), and \(\beta=x\). What happens? Try again.

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