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Let \(X\) be a Banach space. Show that all closed hyperplanes of \(X\) are mutually isomorphic. By induction, we get that given \(k \in \mathbf{N}\), all closed subspaces of \(X\) of codimension \(k\) are isomorphic. Hint: Let \(N_{f}=f^{-1}(0)\) and \(N_{g}=g^{-1}(0) .\) Assume \(N_{f} \neq N_{g} .\) Then \(N=\) \(N_{f} \cap N_{g}\) is 1 -codimensional in \(N_{g}\), so \(N_{g}=N \oplus \operatorname{span}\left\\{x_{g}\right\\}\) (algebraic sum). Since \(N_{f} \neq N_{g}\), we have \(x_{g} \notin N_{f}\) and there is \(x_{f} \in N_{f}\) such that \(X=\) \(N \oplus \operatorname{span}\left\\{x_{g}\right\\} \oplus \operatorname{span}\left\\{x_{f}\right\\} .\) Assume that \(f\left(x_{g}\right)=1=g\left(x_{f}\right)\) and define \(T(x)=x+(f(x)-g(x)) x_{f}+(g(x)-f(x)) x_{g} .\) Then \(T\) is a bounded linear operator on \(X\). For \(y \in N, \alpha, \beta \in \mathbf{K}\), we have \(T\left(y+\alpha x_{f}+\beta x_{g}\right)=y+\beta x_{f}+\alpha x_{g}\), so in particular \(\left.T\right|_{N_{f}}\) is one-to-one and onto \(N_{g}\), hence an isomorphism by Corollary \(2.25 .\)

Short Answer

Expert verified
All closed hyperplanes in a Banach space are mutually isomorphic.

Step by step solution

01

Define the Closed Hyperplanes

Define closed hyperplanes in a Banach space. Suppose we have two closed hyperplanes: \(N_f = f^{-1}(0)\) and \(N_g = g^{-1}(0)\).
02

Intersection of Hyperplanes

Consider that \(N_f eq N_g\). Then \(N = N_f \cap N_g\) is 1-codimensional in \(N_g\). Thus, \(N_g\) can be written as \(N_g = N \oplus \text{span}\{x_g\}\), where the sum is algebraic.
03

Decomposition of the Banach Space

Since \(N_f eq N_g\), it implies \(x_g otin N_f\). Therefore, there exists \(x_f \in N_f\) such that the entire Banach space \(X\) can be written as \(X = N \oplus \text{span}\{x_g\} \oplus \text{span}\{x_f\}\).
04

Functional Values Assumption

Assume that \(f(x_g) = 1\) and \(g(x_f) = 1\). These assumptions are used to define the bounded linear operator that will demonstrate the isomorphism.
05

Define the Bounded Linear Operator

Define the operator \(T(x) = x + (f(x) - g(x)) x_f + (g(x) - f(x)) x_g\). This operator is bounded and linear on \(X\).
06

Verification of Isomorphism

For \(y \in N\) and \(\alpha, \beta \in \mathbf{K}\), evaluate \(T(y + \alpha x_f + \beta x_g) = y + \beta x_f + \alpha x_g\). This shows that the operator \(T\) restricted to \(N_f\) maps it one-to-one and onto \(N_g\). By Corollary 2.25, \(T|_{N_f}\) is an isomorphism.

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Key Concepts

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

hyperplanes
In a Banach space, hyperplanes are crucial geometric structures. To understand them, visualize a flat, infinitely extending surface in a higher-dimensional space. A closed hyperplane in a Banach space \(X\) can be defined as a set of points satisfying \(N_f = f^{-1}(0)\) for some continuous linear functional \(f\). This means that all elements in the hyperplane are mapped to zero by \(f\). We use the notation \(N_f\) to denote this hyperplane. If you encounter two different linear functionals \(f\) and \(g\), their corresponding hyperplanes \(N_f\) and \(N_g\) can be visualized as distinct surfaces, which might intersect along a line or subspace, forming another hyperplane.
isomorphism
Isomorphisms are fundamental in functional analysis, as they show how different structures can be viewed as essentially the same through a 'shape-preserving' mapping. When we say that two hyperplanes are isomorphic, we mean there is a bijective (one-to-one and onto) linear mapping \(T\) between them that also preserves distances and vector operations. In our problem, if \(N_f\) and \(N_g\) are two different hyperplanes, the operator \(T\) we construct demonstrates this isomorphism by mapping elements from \(N_f\) to \(N_g\) perfectly, without distortion. The fact that \(T\) is bounded ensures that it does not drastically alter distances, maintaining the geometric properties of the space.
bounded linear operator
A bounded linear operator is a core concept in the study of Banach spaces. Such an operator \(T: X \to X\) satisfies two main properties: linearity and boundedness. Linearity means that the operator tacks on the property \(T(ax + by) = aT(x) + bT(y)\) for any scalars \(a, b\) and vectors \(x, y\). Boundedness means there exists a constant \(C \textgreater 0\) such that \(||T(x)|| \textless C ||x||\) for all \(x \textin X\). This implies that \(T\) does not 'blow up' vectors too much. In our exercise, the operator \(T(x) = x + (f(x) - g(x)) x_f + (g(x) - f(x)) x_g\) is crafted to show an isomorphism between \(N_f\) and \(N_g\) while maintaining these properties.
codimensional subspaces
Codimension refers to the difference in dimensions between a space and a subspace within it. For instance, if \(N\) is a subspace of codimension 1 in \(N_g\), it means \(N\) has one dimension less than \(N_g\). This is essential in our exercise, where we need to understand how intersecting hyperplanes form a lower-dimensional subspace. Here, \(N = N_f \textcap N_g\) is a subspace of codimension 1 within \(N_g\). We can then express \(N_g\) as the direct sum of \(N\) and the span of some vector \(x_g\), written as \(N_g = N \textoplus \text{span}\{x_g\}\). This decomposition helps us navigate the relationships between different hyperplanes and subspaces, leading towards establishing isomorphisms among them.

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Most popular questions from this chapter

Let \(X, Y\) be Banach spaces and \(T \in \mathcal{B}(X, Y)\). Show that: (i) \(T^{*}\) is onto if and only if \(T\) is an isomorphism into \(Y\). (ii) \(T\) is onto if and only if \(T^{*}\) is an isomorphism into \(X^{*}\). (iii) \(T(X)\) is closed in \(Y\) if and only if \(T^{*}\left(Y^{*}\right)\) is closed in \(X^{*}\). Hint: (i): If \(T^{*}\) is onto, it is an open map (Theorem 2.24), and by Exercise \(2.29\), there is \(\delta>0\) so that \(\delta B_{X} * \subset T^{*}\left(B_{Y}\right)\). Then $$ \begin{aligned} \|T(x)\|_{Y} &=\sup _{y^{*} \in B_{Y} .} y^{*}(T(x))=\sup _{y^{*} \in B_{Y} *} T^{*}\left(y^{*}\right)(x)=\sup _{x^{*} \in T^{*}\left(B_{\gamma} *\right)}\left(x^{*}(x)\right) \\ & \geq \sup _{x^{*} \in \delta B_{x} *}\left(x^{*}(x)\right)=\delta\|x\|_{X} \end{aligned} $$ and use Exercise \(1.27\). If \(T\) is an isomorphism into, then \(T^{-1}\) is a bounded linear operator from \(T(X)\) into \(X\). Given \(x^{*} \in X^{*}\), define \(y^{*}\) on \(T(X)\) by \(y^{*}(y)=x^{*}\left(T^{-1}(y)\right)\). Clearly, \(y^{*} \in T(X)^{*}\); extend it to a functional in \(Y^{*}\). Then \(T^{*}\left(y^{*}\right)=x^{*}\). (ii): If \(T\) is onto, as in (i) we find \(\delta>0\) such that \(\delta B_{Y} \subset T\left(B_{X}\right)\); then \(\left\|T^{*}\left(y^{*}\right)\right\|_{X *} \geq \delta\left\|y^{*}\right\|_{Y *}\) and use Exercise \(1.27\). Assume \(T^{*}\) is an isomorphism into. By Exercise \(2.29\) and Lemma \(2.23\), it is enough to find \(\delta>0\) so that \(\delta B_{Y} \subset \overline{T\left(B_{X}\right)}\). Assume by contradiction that no such \(\delta\) exists. Then find \(y_{n} \rightarrow 0\) such that \(y_{n} \notin \overline{T\left(B_{X}\right)}\). The set is closed, so \(d_{n}=\operatorname{dist}\left(y_{n}, \overline{T\left(B_{X}\right)}\right)>0 .\) Fix \(n_{1}\) and set \(V_{n}=\bigcup_{y \in T\left(B_{x}\right)}\left(y+B_{Y}^{O}\left(\frac{d_{n}}{2}\right)\right)\). Then \(V_{n}\) is an open convex set and \(y_{n} \notin V_{n}\), so by Corollary \(2.13\) there is \(y^{*} \in Y^{*}\) such that \(\left|y^{*}\right|<1\) on \(V_{n}\) and \(y^{*}\left(y_{n}\right)=1\). Since \(T\left(B_{X}\right) \subset V_{n}\), we get $$ \left\|T^{*}\left(y^{*}\right)\right\|=\sup _{x \in B_{X}} T^{*}\left(y^{*}\right)(x)=\sup _{x \in B_{X}} y^{*}(T(x))=\sup _{y \in T\left(B_{X}\right)}\left(y^{*}(y)\right) \leq 1, $$ so \(\left\|y^{*}\right\| \leq\left\|\left(T^{*}\right)^{-1}\right\|\left\|T^{*}\left(y^{*}\right)\right\| \leq\left\|\left(T^{*}\right)^{-1}\right\|, 1=y^{*}\left(y_{n}\right) \leq\left\|\left(T^{*}\right)^{-1}\right\|\left\|y_{n}\right\|\). This shows that \(\left\|y_{n}\right\| \geq 1 /\left\|\left(T^{*}\right)^{-1}\right\|\) for every \(n\), contradicting \(y_{n} \rightarrow 0\). (iii): If \(T(X)\) is closed, then \(\widehat{T}\) is an operator from \(X / \operatorname{Ker}(T)\) onto a Banach space \(T(X)\), hence by (ii), \(\widehat{T}^{*}\) is an isomorphism into, and in particular \(\widehat{T}^{*}\left(Y^{*} / \operatorname{Ker}\left(T^{*}\right)\right)\) is closed. By Exercise \(2.35, \widehat{T^{*}}\left(Y^{*} / \operatorname{Ker}\left(T^{*}\right)\right)=T^{*}\left(Y^{*}\right)\) is closed. If \(T^{*}\left(Y^{*}\right)\) is closed, consider \(\widehat{T}: X \rightarrow \overline{T(X)}\). Then \(\widehat{T}^{*}\left(Y^{*} / \operatorname{Ker}\left(T^{*}\right)\right)=\) \(\widehat{T^{*}}\left(Y^{*} / \operatorname{Ker}\left(T^{*}\right)\right)=T^{*}\left(Y^{*}\right)\) is closed and \(\widehat{T}^{*}\) is one-to-one; hence it is an isomorphism into. By (ii), \(\widehat{T}\) must be onto, that is, \(T(X)=\overline{T(X)}\)

Let \(f\) be a linear functional on a Banach space \(X\). Show that \(f\) is continuous if and only if \(f^{-1}(0)\) is closed. Show that if \(f\) is not continuous, then \(f^{-1}(0)\) is dense in \(X\).

Let \(p \in(1, \infty)\) and \(X_{n}\) be Banach spaces for \(n \in \mathbf{N}\). By \(X=\left(\sum X_{n}\right)_{p}\) we denote the normed linear space of all sequences \(x=\left\\{x_{i}\right\\}_{i=1}^{\infty}, x_{i} \in X_{i}\) such that \(\sum\left\|x_{i}\right\|_{X_{2}}^{p}<\infty\), with the norm \(\|x\|=\left(\sum\left\|x_{i}\right\|_{X_{\imath}}^{p}\right)^{\frac{1}{p}}\) Show that \(X\) is a Banach space and that \(X^{*}\) is isometric to \(\left(\sum X_{i}^{*}\right)_{q}\) (where \(\frac{1}{p}+\frac{1}{q}=1\) ) in the following sense: to \(f \in X^{*}\) we assign \(\left\\{f_{i}\right\\}_{i=1}^{\infty}\) such that \(f_{i} \in X_{i}^{*}\) and \(f\left(\left\\{x_{i}\right\\}_{i=1}^{\infty}\right)=\sum f_{i}\left(x_{i}\right)\) Note: This direct sum is sometimes also denoted \(\bigoplus_{p} X_{i}\). Hint: Follow the proof for \(\ell_{p}\), which is the case of \(X_{i}=\mathbf{R}\).

Let \(X\) be a normed space with two norms \(\|\cdot\|_{1}\) and \(\|\cdot\|_{2}\) such that \(X\) in both of them is a complete space. Assume that \(\|\cdot\|_{1}\) is not equivalent to \(\|\cdot\|_{2}\). Let \(I_{1}\) be the identity map from \(\left(X,\|\cdot\|_{1}\right)\) onto \(\left(X,\|\cdot\|_{2}\right)\) and \(I_{2}\) be the identity map from \(\left(X,\|\cdot\|_{2}\right)\) onto \(\left(X,\|\cdot\|_{1}\right) .\) Show that neither \(I_{1}\) nor \(I_{2}\) are continuous. Hint: The Banach open mapping theorem.

Let \(X\) be a closed subspace of \(C[0,1]\) such that every element of \(X\) is a continuously differentiable function on \([0,1]\). Show that \(X\) is finitedimensional. Hint: Let \(T: X \rightarrow C[0,1]\) be defined for \(f \in X\) by \(T(f)=f^{\prime} .\) Show that the graph of \(T\) is closed: If \(f_{n} \rightarrow f\) uniformly and \(f_{n}^{\prime} \rightarrow g\) uniformly, then \(f^{\prime}=g .\) Therefore \(T\) is continuous by the closed graph theorem. Thus for some \(n \in \mathbf{N}\) we have \(\left\|f^{\prime}\right\|_{\infty} \leq n\) whenever \(f \in X\) satisfies \(\|f\|_{\infty} \leq 1\). Let \(x_{i}=\frac{i}{4 n}\) for \(i=0,1, \ldots, 4 n\). Define an operator \(S: X \rightarrow\) \(\mathbf{R}^{4 n+1}\) by \(S(f)=\left\\{f\left(x_{i}\right)\right\\} .\) We claim that \(S\) is one-to-one. It is enough to show that if \(\|f\|_{\infty}=1\), then for some \(i, S(f)\left(x_{i}\right) \neq 0 .\) Assume that this is not true. If \(f(x)=1\) and \(x \in\left(\frac{i}{4 n}, \frac{i+1}{4 n}\right)\), then by the Lagrange mean value theorem we have \(\left|f(x)-f\left(\frac{i}{4 n}\right)\right|=\left|f^{\prime}(\xi)\right|\left|x-\frac{i}{4 n}\right| \leq n \cdot \frac{1}{4 n}\), a contradiction. Therefore \(\operatorname{dim}(X) \leq 4 n+1\)

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