MHB Operator Norm for Linear Transformations: Browder Ch. 8, Section 8.1, Page 179

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The discussion centers on understanding the "operator norm" for linear transformations as described in Browder's "Mathematical Analysis: An Introduction." Participants seek clarification on the equivalence of two definitions of the operator norm and the proof of its finiteness. One key point is that if the inequality holds for all vectors with a norm less than or equal to one, it implies that the supremum of the transformation's output is also bounded by that constant. Additionally, the finiteness of the operator norm is established through the application of the Cauchy-Schwarz inequality and the properties of linear transformations. Overall, the thread emphasizes rigorous mathematical proofs and clarifications related to the operator norm.
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The "Operator Norm" for Linear Transfomations ... Browder, page 179, Section 8.1, Ch. 8 ... ...

I am reader Andrew Browder's book: "Mathematical Analysis: An Introduction" ... ...

I am currently reading Chapter 8: Differentiable Maps and am specifically focused on Section 8.1 Linear Algebra ...

I need some help in fully understanding some remarks by Browder concerning the "operator norm" for linear transformations ...

The relevant notes form Browder read as follows:https://www.physicsforums.com/attachments/7451
My questions regarding the above text by Browder are as follows:
Question 1

In the above notes from Browder we read the following:

" ... ... A perhaps more natural way to define the distance between linear transformations is by using the so-called "operator norm" defined by

$$\lvert \lvert T \rvert \rvert = \text{ sup} \{ \lvert Tv \rvert \ : \ v \in \mathbb{R}^n , \ \lvert v \rvert \le 1 \}
$$It is not hard to verify that this definition is equivalent to $$\lvert \lvert T \rvert \rvert = \text{ inf} \{ C \ge 0 \ : \ \lvert Tv \rvert \le C \lvert v \rvert \text{ for all } v \in \mathbb{R}^n \} $$

... ... "
Can someone please demonstrate rigorously exactly why/how

$$\lvert \lvert T \rvert \rvert = \text{ sup} \{ \lvert Tv \rvert \ : \ v \in \mathbb{R}^n , \ \lvert v \rvert \le 1 \}
$$

is equivalent to

$$\lvert \lvert T \rvert \rvert = \text{ inf} \{ C \ge 0 \ : \ \lvert Tv \rvert \le C \lvert v \rvert \text{ for all } v \in \mathbb{R}^n \}
$$

... ... ... ?

Question 2


In the above notes from Browder we read the following:

" ... ... The finiteness of $$\lvert \lvert T \rvert \rvert$$ is easy to see ... "Can someone please rigorously demonstrate why/how $$\lvert \lvert T \rvert \rvert$$ is necessarily finite ... ?
Help will be much appreciated ... ...

Peter
 
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Re: The "Operator Norm" for Linear Transfomations ... Browder, page 179, Section 8.1, Ch. 8 ... ...

Hi Peter,
Peter said:
Question 1

In the above notes from Browder we read the following:

" ... ... A perhaps more natural way to define the distance between linear transformations is by using the so-called "operator norm" defined by

$$\lvert \lvert T \rvert \rvert = \text{ sup} \{ \lvert Tv \rvert \ : \ v \in \mathbb{R}^n , \ \lvert v \rvert \le 1 \}
$$It is not hard to verify that this definition is equivalent to $$\lvert \lvert T \rvert \rvert = \text{ inf} \{ C \ge 0 \ : \ \lvert Tv \rvert \le C \lvert v \rvert \text{ for all } v \in \mathbb{R}^n \} $$

... ... "
Can someone please demonstrate rigorously exactly why/how

$$\lvert \lvert T \rvert \rvert = \text{ sup} \{ \lvert Tv \rvert \ : \ v \in \mathbb{R}^n , \ \lvert v \rvert \le 1 \}
$$

is equivalent to

$$\lvert \lvert T \rvert \rvert = \text{ inf} \{ C \ge 0 \ : \ \lvert Tv \rvert \le C \lvert v \rvert \text{ for all } v \in \mathbb{R}^n \}
$$

... ... ... ?
If $v\in \Bbb R^n - \{\bf 0\}$, then $\dfrac{v}{\lvert v\rvert}$ has norm $1$, so $\left\lvert T\left(\dfrac{v}{\lvert v\rvert}\right)\right\rvert \le \|T\|$. Since $T$ is linear, $T\left(\dfrac{v}{\lvert v\rvert}\right) = \dfrac{1}{\lvert v\rvert}T(v)$. Thus $\lvert T(v)\rvert \le \|T\|\lvert v\rvert$. Since $T$ is linear, $T(0) = 0$, so the inequality $\lvert T(v)\rvert \le \|T\|\lvert v\rvert$ holds for $v = 0$. Since $\lvert Tv\rvert \le \|T\|\lvert v\rvert$ for all $v\in \Bbb R^n$, then $\|T\|$ is an element of the set $\{C\ge 0 : \text{$\lvert Tv\rvert \le C\lvert v\rvert$ for all $v\in \Bbb R^n$}\}$. Therefore,
$$\|T\| \ge \inf\{C\ge 0: \text{$\lvert Tv\rvert \le C\lvert v\rvert$ for all $v\in \Bbb R^n$}\}\tag{1}\label{eq1}$$
On the other hand, if $C > 0$ such that $\lvert Tv\rvert \le C\lvert v\rvert$ for all $v\in \Bbb R^n$. In particular, for all $v\in \Bbb R^n$ with $\lvert v\rvert \le 1$, $\lvert Tv\rvert \le C$. Hence, $\sup_{\lvert v\rvert \le 1} \lvert Tv\rvert \le C$, i.e., $\|T\| \le C$. This shows that $\|T\|$ is a lower bound for the set $\{C\ge 0: \text{$\lvert Tv\rvert \le C\lvert v\rvert$ for all $v\in \Bbb R^n$}\}$. Hence, $$\|T\| \le \inf\{C\ge 0 : \text{$\lvert Tv\rvert \le C\lvert v\rvert$ for all $v\in \Bbb R^n$}\}\tag{2}\label{eq2}$$ By inequalities \eqref{eq1} and \eqref{eq2}, the result follows.
Peter said:
Question 2


In the above notes from Browder we read the following:

" ... ... The finiteness of $$\lvert \lvert T \rvert \rvert$$ is easy to see ... "Can someone please rigorously demonstrate why/how $$\lvert \lvert T \rvert \rvert$$ is necessarily finite ... ?

Let $\mathbf{e}_1,\ldots, \mathbf{e}_n$ be the standard basis of $\Bbb R^n$. For all $\mathbf{v} = (v_1,\ldots, v_n)\in \Bbb R^n$, $$T(\mathbf{v}) = T\left(\sum_{i = 1}^n v_i \mathbf{e}_i\right) = \sum_{i = 1}^n v_i T(\mathbf{e}_i) = \mathbf{v}\cdot (T(\mathbf{e}_1),\ldots, T(\mathbf{e}_n))$$ The Cauchy-Schwarz inequality gives $\lvert Tv\rvert \le C\lvert \mathbf{v}\rvert$ where $C$ is the norm of the vector $(T(\mathbf{e}_1),\ldots, T(\mathbf{e}_n))$. Note the $C$ a constant independent of $\mathbf{v}$. Since $\mathbf{v}$ was arbitrary, $\|T\| \le C$. Therefore, $\|T\|$ is finite.
 
Re: The "Operator Norm" for Linear Transfomations ... Browder, page 179, Section 8.1, Ch. 8 ... ...

Euge said:
Hi Peter,If $v\in \Bbb R^n - \{\bf 0\}$, then $\dfrac{v}{\lvert v\rvert}$ has norm $1$, so $\left\lvert T\left(\dfrac{v}{\lvert v\rvert}\right)\right\rvert \le \|T\|$. Since $T$ is linear, $T\left(\dfrac{v}{\lvert v\rvert}\right) = \dfrac{1}{\lvert v\rvert}T(v)$. Thus $\lvert T(v)\rvert \le \|T\|\lvert v\rvert$. Since $T$ is linear, $T(0) = 0$, so the inequality $\lvert T(v)\rvert \le \|T\|\lvert v\rvert$ holds for $v = 0$. Since $\lvert Tv\rvert \le \|T\|\lvert v\rvert$ for all $v\in \Bbb R^n$, then $\|T\|$ is an element of the set $\{C\ge 0 : \text{$\lvert Tv\rvert \le C\lvert v\rvert$ for all $v\in \Bbb R^n$}\}$. Therefore,
$$\|T\| \ge \inf\{C\ge 0: \text{$\lvert Tv\rvert \le C\lvert v\rvert$ for all $v\in \Bbb R^n$}\}\tag{1}\label{eq1}$$
On the other hand, if $C > 0$ such that $\lvert Tv\rvert \le C\lvert v\rvert$ for all $v\in \Bbb R^n$. In particular, for all $v\in \Bbb R^n$ with $\lvert v\rvert \le 1$, $\lvert Tv\rvert \le C$. Hence, $\sup_{\lvert v\rvert \le 1} \lvert Tv\rvert \le C$, i.e., $\|T\| \le C$. This shows that $\|T\|$ is a lower bound for the set $\{C\ge 0: \text{$\lvert Tv\rvert \le C\lvert v\rvert$ for all $v\in \Bbb R^n$}\}$. Hence, $$\|T\| \le \inf\{C\ge 0 : \text{$\lvert Tv\rvert \le C\lvert v\rvert$ for all $v\in \Bbb R^n$}\}\tag{2}\label{eq2}$$ By inequalities \eqref{eq1} and \eqref{eq2}, the result follows.Let $\mathbf{e}_1,\ldots, \mathbf{e}_n$ be the standard basis of $\Bbb R^n$. For all $\mathbf{v} = (v_1,\ldots, v_n)\in \Bbb R^n$, $$T(\mathbf{v}) = T\left(\sum_{i = 1}^n v_i \mathbf{e}_i\right) = \sum_{i = 1}^n v_i T(\mathbf{e}_i) = \mathbf{v}\cdot (T(\mathbf{e}_1),\ldots, T(\mathbf{e}_n))$$ The Cauchy-Schwarz inequality gives $\lvert Tv\rvert \le C\lvert \mathbf{v}\rvert$ where $C$ is the norm of the vector $(T(\mathbf{e}_1),\ldots, T(\mathbf{e}_n))$. Note the $C$ a constant independent of $\mathbf{v}$. Since $\mathbf{v}$ was arbitrary, $\|T\| \le C$. Therefore, $\|T\|$ is finite.

Thanks so much Euge ...

Really appreciate your help on this matter ...

Just working through what you have written ...

Thanks again ...

Peter
 
Re: The "Operator Norm" for Linear Transfomations ... Browder, page 179, Section 8.1, Ch. 8 ... ...

Euge said:
Hi Peter,If $v\in \Bbb R^n - \{\bf 0\}$, then $\dfrac{v}{\lvert v\rvert}$ has norm $1$, so $\left\lvert T\left(\dfrac{v}{\lvert v\rvert}\right)\right\rvert \le \|T\|$. Since $T$ is linear, $T\left(\dfrac{v}{\lvert v\rvert}\right) = \dfrac{1}{\lvert v\rvert}T(v)$. Thus $\lvert T(v)\rvert \le \|T\|\lvert v\rvert$. Since $T$ is linear, $T(0) = 0$, so the inequality $\lvert T(v)\rvert \le \|T\|\lvert v\rvert$ holds for $v = 0$. Since $\lvert Tv\rvert \le \|T\|\lvert v\rvert$ for all $v\in \Bbb R^n$, then $\|T\|$ is an element of the set $\{C\ge 0 : \text{$\lvert Tv\rvert \le C\lvert v\rvert$ for all $v\in \Bbb R^n$}\}$. Therefore,
$$\|T\| \ge \inf\{C\ge 0: \text{$\lvert Tv\rvert \le C\lvert v\rvert$ for all $v\in \Bbb R^n$}\}\tag{1}\label{eq1}$$
On the other hand, if $C > 0$ such that $\lvert Tv\rvert \le C\lvert v\rvert$ for all $v\in \Bbb R^n$. In particular, for all $v\in \Bbb R^n$ with $\lvert v\rvert \le 1$, $\lvert Tv\rvert \le C$. Hence, $\sup_{\lvert v\rvert \le 1} \lvert Tv\rvert \le C$, i.e., $\|T\| \le C$. This shows that $\|T\|$ is a lower bound for the set $\{C\ge 0: \text{$\lvert Tv\rvert \le C\lvert v\rvert$ for all $v\in \Bbb R^n$}\}$. Hence, $$\|T\| \le \inf\{C\ge 0 : \text{$\lvert Tv\rvert \le C\lvert v\rvert$ for all $v\in \Bbb R^n$}\}\tag{2}\label{eq2}$$ By inequalities \eqref{eq1} and \eqref{eq2}, the result follows.Let $\mathbf{e}_1,\ldots, \mathbf{e}_n$ be the standard basis of $\Bbb R^n$. For all $\mathbf{v} = (v_1,\ldots, v_n)\in \Bbb R^n$, $$T(\mathbf{v}) = T\left(\sum_{i = 1}^n v_i \mathbf{e}_i\right) = \sum_{i = 1}^n v_i T(\mathbf{e}_i) = \mathbf{v}\cdot (T(\mathbf{e}_1),\ldots, T(\mathbf{e}_n))$$ The Cauchy-Schwarz inequality gives $\lvert Tv\rvert \le C\lvert \mathbf{v}\rvert$ where $C$ is the norm of the vector $(T(\mathbf{e}_1),\ldots, T(\mathbf{e}_n))$. Note the $C$ a constant independent of $\mathbf{v}$. Since $\mathbf{v}$ was arbitrary, $\|T\| \le C$. Therefore, $\|T\|$ is finite.
I am revising question 1 above ... where Euge is proving that $$\lvert \lvert T \rvert \rvert = \text{ sup} \{ \lvert Tv \rvert \ : \ v \in \mathbb{R}^n , \ \lvert v \rvert \le 1 \}
$$is equivalent to $$\lvert \lvert T \rvert \rvert = \text{ inf} \{ C \ge 0 \ : \ \lvert Tv \rvert \le C \lvert v \rvert \text{ for all } v \in \mathbb{R}^n \}
$$In the above proof by Euge ... Euge writes the following:" ... ... In particular, for all $v\in \Bbb R^n$ with $\lvert v\rvert \le 1$, $\lvert Tv\rvert \le C$. Hence, $\sup_{\lvert v\rvert \le 1} \lvert Tv\rvert \le C$, i.e., $\|T\| \le C$. ... ... "

Can someone please formally and rigorously demonstrate that ...if ... for all $v\in \Bbb R^n$ with $\lvert v\rvert \le 1$, $\lvert Tv\rvert \le C$ ... ...... it then follows that ... $\sup_{\lvert v\rvert \le 1} \lvert Tv\rvert \le C$ ... ... (It seems highly plausible ... but how do you rigorously prove it ... ? )
... help will be much appreciated ...

Peter
 
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Re: The "Operator Norm" for Linear Transfomations ... Browder, page 179, Section 8.1, Ch. 8 ... ...

Peter said:
Can someone please formally and rigorously demonstrate that ...if ... for all $v\in \Bbb R^n$ with $\lvert v\rvert \le 1$, $\lvert Tv\rvert \le C$ ... ...... it then follows that ... $\sup_{\lvert v\rvert \le 1} \lvert Tv\rvert \le C$ .
The statement "for all $v\in \Bbb R^n$ with $\lvert v\rvert \le 1$, $\lvert Tv\rvert \le C$" says that $C$ is an upper bound for the set $\{|Tv| : v\in \Bbb R^n,|v|\leqslant1\}$. The number $\sup_{\lvert v\rvert \le 1} \lvert Tv\rvert$ is the supremum, or least upper bound, of that same set. By definition, the least upper bound is less than or equal to any other upper bound. Therefore $\sup_{\lvert v\rvert \le 1} \lvert Tv\rvert \leqslant C$.
 
Re: The "Operator Norm" for Linear Transfomations ... Browder, page 179, Section 8.1, Ch. 8 ... ...

Opalg said:
The statement "for all $v\in \Bbb R^n$ with $\lvert v\rvert \le 1$, $\lvert Tv\rvert \le C$" says that $C$ is an upper bound for the set $\{|Tv| : v\in \Bbb R^n,|v|\leqslant1\}$. The number $\sup_{\lvert v\rvert \le 1} \lvert Tv\rvert$ is the supremum, or least upper bound, of that same set. By definition, the least upper bound is less than or equal to any other upper bound. Therefore $\sup_{\lvert v\rvert \le 1} \lvert Tv\rvert \leqslant C$.

Thanks Opalg ...

That certainly clears up the issue ...

Peter
 
We all know the definition of n-dimensional topological manifold uses open sets and homeomorphisms onto the image as open set in ##\mathbb R^n##. It should be possible to reformulate the definition of n-dimensional topological manifold using closed sets on the manifold's topology and on ##\mathbb R^n## ? I'm positive for this. Perhaps the definition of smooth manifold would be problematic, though.

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