Characterization of Invertible Bounded Linear Transformations
Theorem
Let $\struct {U, \norm \cdot_U}$ and $\struct {V, \norm \cdot_V}$ be normed vector spaces.
Let $A : V \to U$ be a linear transformation with inverse $A^{-1} : U \to V$.
Then $A^{-1}$ is a bounded linear transformation if and only if:
- there exists a real number $c > 0$ such that $\norm {A x}_U \ge c \norm x_V$ for all $x \in V$.
That is, $A$ is invertible as a bounded linear transformation if and only if:
- there exists a real number $c > 0$ such that $\norm {A x}_U \ge c \norm x_V$ for all $x \in V$.
Proof
From Inverse of Linear Transformation is Linear Transformation, we have:
- $A^{-1}$ is a linear transformation.
So we are interested in determining when $A^{-1}$ is bounded.
Necessary Condition
Suppose that $A^{-1}$ was bounded.
Then:
- there exists a real number $M > 0$ such that $\norm {A^{-1} y}_V \le M \norm y_U$ for all $y \in U$.
Let $x \in V$ and set $y = A x \in U$.
Then:
- $\norm {A^{-1} y}_V \le M \norm y_U$
We have:
\(\ds \norm {A^{-1} y}_V\) | \(=\) | \(\ds \norm {A^{-1} A x}_V\) | ||||||||||||
\(\ds \) | \(=\) | \(\ds \norm x_V\) |
and:
- $\norm y_U = \norm {A x}_U$
giving:
- $\norm x_V \le M \norm {A x}_U$
So, we have:
- $\norm {A x}_U \ge \dfrac 1 M \norm x_V$
for all $x \in V$.
Then, setting $c = 1/M$, we have that:
- there exists a real number $c > 0$ such that $\norm {A x}_U \ge c \norm x_V$ for all $x \in V$.
$\Box$
Sufficient Condition
Suppose that:
- there exists a real number $c > 0$ such that $\norm {A x}_U \ge c \norm x_V$ for all $x \in V$.
Let $y \in U$ and let $x = A^{-1} y \in V$.
Then:
- $\norm {A x}_U \ge c \norm x_V$
We have:
\(\ds \norm {A x}_U\) | \(=\) | \(\ds \norm {A A^{-1} y}_U\) | ||||||||||||
\(\ds \) | \(=\) | \(\ds \norm y_U\) |
and:
- $\norm x_V = \norm {A^{-1} y}_V$
so:
- $\norm y_U \ge c \norm {A^{-1} y}_V$
So, we have:
- $\norm {A^{-1} y}_V \le \dfrac 1 c \norm y_U$
for all $y \in U$.
So:
- $A^{-1}$ is bounded.
$\blacksquare$