Solution to the Week's Problem: Opalg

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SUMMARY

The natural embedding operator \( J: X \rightarrow X^{\ast\ast} \) defined by \( J(x)[\psi] = \psi(x) \) for all \( x \in X \) and \( \psi \in X^{\ast} \) is proven to be an isometry. Opalg provided a comprehensive solution demonstrating that the operator preserves the norm, thereby confirming that \( \|J(x)\| = \|x\| \) for all \( x \in X \). This conclusion is essential for understanding the relationship between a normed linear space and its double dual.

PREREQUISITES
  • Understanding of normed linear spaces
  • Familiarity with dual spaces and dual operators
  • Knowledge of isometric mappings
  • Basic concepts of functional analysis
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  • Study the properties of dual spaces in functional analysis
  • Explore the concept of isometries in normed spaces
  • Learn about the Hahn-Banach theorem and its implications
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Mathematicians, students of functional analysis, and anyone studying the properties of normed linear spaces and their duals will benefit from this discussion.

Chris L T521
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Here's this week's problem.

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Background Info: Let $X$ be a normed linear space. The linear operator $J:X\rightarrow X^{\ast\ast}$ defined by
\[J(x)[\psi] = \psi(x) \text{ for all $x\in X$, $\psi\in X^{\ast}$}\]
is called the natural embedding of $X$ into $X^{\ast\ast}$.

Problem: Let $X$ be a normed linear space. Show that the natural embedding $J:X\rightarrow X^{\ast\ast}$ is an isometry.

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This week's problem was correctly answered by Opalg. You can his solution below.

This result is essentially a consequence of the Hahn–Banach theorem. If $x\in X$ then we can define a linear functional $\phi$ on the one-dimensional subspace of $X$ spanned by $x$ by $\phi(\lambda x) = \lambda\|x\|.$ Then $\phi$ is bounded, with $\|\phi\| = 1$, and $\phi(x) = \|x\|.$ By the H–B theorem, $\phi$ extends to a linear functional (still called $\phi$) on the whole of $X^*$, with $\|\phi\| = 1$.

Denote by $X^*_1$ the unit ball of $X^*$. Then $\psi \in X^*_1\;\Rightarrow\; |\psi(x)| \leqslant \|\psi\|\|x\| \leqslant \|x\|$. It follows that $$\sup_{\psi\in X^*_1}|\psi(x)| \leqslant \|x\|.$$ On the other hand, $$\sup_{\psi\in X^*_1}|\psi(x)| \geqslant |\phi(x)| = \|x\|.$$ Therefore $$\sup_{\psi\in X^*_1}|\psi(x)| = \|x\|.$$

Then $$\|J(x)\| = \sup_{\psi\in X^*_1}|J(x)[\psi]| = \sup_{\psi\in X^*_1}|\psi(x)| = \|x\|.$$
 

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