Norm of a Linear Transformation .... Junnheng Proposition 9.2.3 .... ....

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SUMMARY

The discussion centers on the proof of Proposition 9.2.3 from Hugo D. Junghenn's "A Course in Real Analysis," specifically regarding the properties of linear transformations and their norms. Participants clarify that for a linear transformation \( T \), the equality \( \| \mathbf{x} \|^{-1} \| T \mathbf{x} \| = \| T ( \| \mathbf{x} \|^{-1} \mathbf{x} ) \| \) holds due to the linearity of \( T \). Furthermore, it is established that \( \| T ( \| \mathbf{x} \|^{-1} \mathbf{x} ) \| \le \| T \| \) follows from the definition of the operator norm, where \( \|T\| = \sup\{\|T \mathbf{y} \| : \| \mathbf{y} \| = 1\} \).

PREREQUISITES
  • Understanding of linear transformations and their properties
  • Familiarity with norms in vector spaces
  • Knowledge of operator norms and their definitions
  • Basic proficiency in real analysis, particularly in differentiation on \( \mathbb{R}^n \)
NEXT STEPS
  • Study the concept of operator norms in detail
  • Review linear transformation properties in real analysis
  • Explore the implications of Proposition 9.2.3 in various contexts
  • Investigate additional examples of linear transformations and their norms
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Students of real analysis, mathematicians focusing on linear algebra, and anyone seeking to deepen their understanding of linear transformations and their properties in the context of differentiation on \( \mathbb{R}^n \).

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I am reading Hugo D. Junghenn's book: "A Course in Real Analysis" ...

I am currently focused on Chapter 9: "Differentiation on $$\mathbb{R}^n$$"

I need some help with the proof of Proposition 9.2.3 ...

Proposition 9.2.3 and the preceding relevant Definition 9.2.2 read as follows:
https://www.physicsforums.com/attachments/7889
View attachment 7890
In the above proof we read the following:

" ... ... If $$\mathbf{x} \neq \mathbf{0}$$ then $$\| \mathbf{x} \|^{-1} \mathbf{x}$$ has a norm $$1$$, hence


$$\| \mathbf{x} \|^{-1} \| T \mathbf{x} \| = \| T ( \| \mathbf{x} \|^{-1} \mathbf{x} ) \| \le 1$$ ... ... "
Now I know that $$T( c \mathbf{x} ) = c T( \mathbf{x} ) $$... BUT ...... how do we know that this works "under the norm sign" ...... that is, how do we know ...$$\| \mathbf{x} \|^{-1} \| T \mathbf{x} \| = \| T ( \| \mathbf{x} \|^{-1} \mathbf{x} ) \| $$
... and further ... how do we know that ...
$$\| T ( \| \mathbf{x} \|^{-1} \mathbf{x} ) \| \le 1 $$Help will be appreciated ...

Peter
 
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Peter said:
I know that $$T( c \mathbf{x} ) = c T( \mathbf{x} ) $$

... BUT ...

... how do we know that this works "under the norm sign" ...

... that is, how do we know ...

$$\| \mathbf{x} \|^{-1} \| T \mathbf{x} \| = \| T ( \| \mathbf{x} \|^{-1} \mathbf{x} ) \| $$
If you make the substitution $c = \| \mathbf{x} \|^{-1}$ in the equation $\| c \mathbf{y}\| = c\| \mathbf{y}\|$ (where $c$ is a positive constant), then it becomes $\| \| \mathbf{x} \|^{-1} \mathbf{y}\| = \| \mathbf{x} \|^{-1}\| \mathbf{y}\|$. Do that when $\mathbf{y} = T\mathbf{x}$, to get $\| \|T( \mathbf{x} \|^{-1} \mathbf{x})\| = \| \| \mathbf{x} \|^{-1}(T \mathbf{x})\| = \| \mathbf{x} \|^{-1}\|T \mathbf{x}\|$.

Peter said:
... and further ... how do we know that ...

$$\| T ( \| \mathbf{x} \|^{-1} \mathbf{x} ) \| \le 1 $$
That is a mistake. It should read $$\| T ( \| \mathbf{x} \|^{-1} \mathbf{x} ) \| \le \|T\| $$.
 
Opalg said:
If you make the substitution $c = \| \mathbf{x} \|^{-1}$ in the equation $\| c \mathbf{y}\| = c\| \mathbf{y}\|$ (where $c$ is a positive constant), then it becomes $\| \| \mathbf{x} \|^{-1} \mathbf{y}\| = \| \mathbf{x} \|^{-1}\| \mathbf{y}\|$. Do that when $\mathbf{y} = T\mathbf{x}$, to get $\| \|T( \mathbf{x} \|^{-1} \mathbf{x})\| = \| \| \mathbf{x} \|^{-1}(T \mathbf{x})\| = \| \mathbf{x} \|^{-1}\|T \mathbf{x}\|$.That is a mistake. It should read $$\| T ( \| \mathbf{x} \|^{-1} \mathbf{x} ) \| \le \|T\| $$.
Thanks Opalg ...

Appreciate your help ...

Peter
 
Opalg said:
If you make the substitution $c = \| \mathbf{x} \|^{-1}$ in the equation $\| c \mathbf{y}\| = c\| \mathbf{y}\|$ (where $c$ is a positive constant), then it becomes $\| \| \mathbf{x} \|^{-1} \mathbf{y}\| = \| \mathbf{x} \|^{-1}\| \mathbf{y}\|$. Do that when $\mathbf{y} = T\mathbf{x}$, to get $\| \|T( \mathbf{x} \|^{-1} \mathbf{x})\| = \| \| \mathbf{x} \|^{-1}(T \mathbf{x})\| = \| \mathbf{x} \|^{-1}\|T \mathbf{x}\|$.That is a mistake. It should read $$\| T ( \| \mathbf{x} \|^{-1} \mathbf{x} ) \| \le \|T\| $$.

Hi Opalg ...

Just realized that I don't fully understand why $$\| T ( \| \mathbf{x} \|^{-1} \mathbf{x} ) \| \le \|T\| $$ ...

Can you please help further and demonstrate why this is the case ...

Peter
 
Peter said:
Hi Opalg ...

Just realized that I don't fully understand why $$\| T ( \| \mathbf{x} \|^{-1} \mathbf{x} ) \| \le \|T\| $$ ...

Can you please help further and demonstrate why this is the case ...

Peter
The definition $\|T\| = \sup\{\|T \mathbf{y} \| : \| \mathbf{y} \| = 1\}$ says that if $\| \mathbf{y} \| = 1$ then $\|T \mathbf{y} \| \leqslant \|T\|$. But $ \| \mathbf{x} \|^{-1} \mathbf{x} $ has norm $1$, so you can substitute that vector for $ \mathbf{y}$, to get $\bigl\|T( \| \mathbf{x} \|^{-1} \mathbf{x} )\bigr\| \leqslant \|T\|$.
 
Opalg said:
The definition $\|T\| = \sup\{\|T \mathbf{y} \| : \| \mathbf{y} \| = 1\}$ says that if $\| \mathbf{y} \| = 1$ then $\|T \mathbf{y} \| \leqslant \|T\|$. But $ \| \mathbf{x} \|^{-1} \mathbf{x} $ has norm $1$, so you can substitute that vector for $ \mathbf{y}$, to get $\bigl\|T( \| \mathbf{x} \|^{-1} \mathbf{x} )\bigr\| \leqslant \|T\|$.
Hi Opalg ... thanks again for the help ...

Peter
 

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