Dual Operator is Bounded Linear Transformation

Theorem
Let $\GF \in \set {\R, \C}$.

Let $X$ and $Y$ be normed vector spaces over $\GF$.

Let $T : X \to Y$ be a bounded linear transformation.

Let $X^\ast$ and $Y^\ast$ be the normed duals of $X$ and $Y$ respectively.

Then the dual operator $T^\ast : Y^\ast \to X^\ast$ is a bounded linear transformation.

Further:


 * $\norm {T^\ast}_{\map B {Y^\ast, X^\ast} } = \norm T_{\map B {X, Y} }$

Proof
Let $f, g \in Y^\ast$ and $\alpha, \beta \in \GF$.

Then we have, for each $x \in X$:

So we have:


 * $\map {T^\ast} {\alpha f + \beta g} = \alpha T^\ast f + \beta T^\ast g$

In Dual Operator is Well-Defined, it was shown that for each $f \in Y^\ast$ and $x \in X$ we have:


 * $\cmod {\map {\paren {T^\ast f} } x} \le \norm f_{Y^\ast} \norm T_{\map B {X, Y} } \norm x_X$

So we have:


 * $\norm {T^\ast f}_{X^\ast} \le \norm T_{\map B {X, Y} } \norm f_{Y^\ast}$

for $f \in Y^\ast$.

Hence:


 * $\norm {T^\ast}_{\map B {Y^\ast, X^\ast} } \le \norm T_{\map B {X, Y} }$

We finally need to show that $\norm {T^\ast}_{\map B {Y^\ast, X^\ast} } = \norm T_{\map B {X, Y} }$.

Pick a sequence $\sequence {x_n}_{n \in \N}$ such that $\norm {x_n}_X = 1$ and:


 * $\ds \norm T_{\map B {X, Y} } - \frac 1 n \le \norm {T x_n}_Y \le \norm T_{\map B {X, Y} }$

so that:


 * $\norm {T x_n}_Y \to \norm T_{\map B {X, Y} }$

For each $n \in \N$, let $f_n \in Y^\ast$ be a support functional for $T x_n$.

Then we have:


 * $\map {\paren {T^\ast f_n} } {x_n} = \map {f_n} {T x_n} = \norm {T x_n}_Y$

so that:


 * $\ds \cmod {\map {\paren {T^\ast f_n} } {x_n} } \ge \paren {\norm T_{\map B {X, Y} } - \frac 1 n} \norm {x_n}_X$

We therefore have:


 * $\ds \paren {\norm T_{\map B {X, Y} } - \frac 1 n} \norm {f_n}_{Y^\ast} \le \norm {T^\ast f_n}_{X^\ast}$

so that:


 * $\ds \norm {T^\ast}_{\map B {Y^\ast, X^\ast} } \ge \norm T_{\map B {X, Y} } - \frac 1 n$

for each $n \in \N$.

Then:


 * $\norm {T^\ast}_{\map B {Y^\ast, X^\ast} } \ge \norm T_{\map B {X, Y} }$

With that, we obtain:


 * $\norm {T^\ast}_{\map B {Y^\ast, X^\ast} } = \norm T_{\map B {X, Y} }$