Prove Dual Space Isometry: X = C[0,1] Sup Norm

In summary, the homework statement is to prove that the supremum norm for a function f in C[0,1] is given by||f|| = \sup_{x \in [0,1]} |f(x)|.
  • #1
complexnumber
62
0

Homework Statement



For the Banach space [tex]X = C[0,1][/tex] with the supremum norm, fix
an element [tex]g \in X[/tex] and define a map [tex]\varphi_g : X \to \mathbb{C}[/tex]
by
[tex]
\begin{align*}
\varphi_g(h) := \int^1_0 g(t) h(t) dt, \qquad h \in X
\end{align*}
[/tex]
Define [tex]W := \{ \varphi_g | g \in X \}[/tex].


Prove that [tex]\varphi_g \in X^*[/tex] and calculate
[tex]||\varphi_g||_{X^*}[/tex].




Homework Equations





The Attempt at a Solution



The supremum norm for a function [tex]f \in C[0,1][/tex] is [tex]\displaystyle
||f|| = \sup_{x \in [0,1]} |f(x)|[/tex].

For [tex]h_1,h_2 \in X[/tex] and [tex]\lambda \in \mathbb{C}[/tex]
[tex]
\begin{align*}
\varphi_g(h_1 + h_2) =& \int^1_0 g(t) (h_1(t) + h_2(t)) dt =
\int^1_0 g(t) h_1(t) dt + \int^1_0 g(t) h_2(t) dt = \varphi_g(h_1) +
\varphi_g(h_2) \\
\varphi_g(\lambda h_1) =& \int^1_0 \lambda g(t) h_1(t) dt = \lambda
\int^1_0 g(t) h_1(t) dt
\end{align*}
[/tex]
So [tex]\varphi_g[/tex] is linear functional.

For any [tex]h \in X[/tex], [tex]\varphi_g[/tex] is continuous if [tex]\forall \varepsilon
> 0[/tex] [tex]\exists \delta > 0[/tex] such that any [tex]h' \in X[/tex] satisfies
[tex]
\begin{align*}
d(h,h') < \delta \implies d(\varphi_g(h), \varphi_g(h')) <
\varepsilon \text{.}
\end{align*}
[/tex]
The distance function is [tex]\displaystyle d(h,h') = ||h - h'|| =
\sup_{x \in [0,1]} |h(t) - h'(t)|[/tex].
[tex]
\begin{align*}
d(\varphi_g(h), \varphi_g(h')) =& |\int^1_0 g(t) h(t) dt -
\int^1_0 g(t) h'(t) dt | = |\int^1_0 g(t) h(t) - g(t) h'(t) dt | \\
=& |\int^1_0 g(t) (h(t) - h'(t)) dt| \leq \int^1_0 |g(t) (h(t) - h'(t))| dt \\
\leq & \int^1_0 |g(t)| |(h(t) - h'(t))| dt \leq \sup_{t \in
[0,1]} |(h(t) - h'(t))| \int^1_0 |g(t)| dt \\
=& d(h,h') \int^1_0 |g(t)| dt
\end{align*}
[/tex]
For any [tex]\varepsilon > 0[/tex], we get [tex]\displaystyle d(h,h') \int^1_0
|g(t)| dt < \varepsilon[/tex] when [tex]\displaystyle d(h,h') <
\frac{\varepsilon}{\displaystyle \int^1_0 |g(t)| dt} = \delta[/tex].
Thus [tex]\varphi_g[/tex] is continuous. Are the above proofs correct?

The formula for [tex]||\varphi_g||_{X^*}[/tex] is
[tex]
\begin{align*}
||\varphi_g||_{X^*} :=& \sup \{ |\varphi_g(h)| | \norm{h} = 1
\} \\
=& \sup \left\{ |\int^1_0 g(t)h(t) dt| \bigg| \sup_{t \in [0,1]}
|h| = 1 \right\}
\end{align*}
[/tex]
How can I find the value of this?
 
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  • #2
For the supremum, maybe some sort of triangle inequality application can give you a starting upper bound
 
  • #3
complexnumber said:
Are the above proofs correct?
As far as I can say, they are.

complexnumber said:
The formula for [tex]||\varphi_g||_{X^*}[/tex] is
[tex]
\begin{align*}
||\varphi_g||_{X^*} :=& \sup \{ |\varphi_g(h)| | \norm{h} = 1
\} \\
=& \sup \left\{ |\int^1_0 g(t)h(t) dt| \bigg| \sup_{t \in [0,1]}
|h| = 1 \right\}
\end{align*}
[/tex]
How can I find the value of this?

You have
[tex]\left|\int^1_0 g(t)h(t) dt\right| \le \int^1_0 |g(t)| |h(t)| dt \le \int^1_0 |g(t)| dt[/tex]
therefore
[tex]||\varphi_g|| \le \int^1_0 |g(t)| dt [/tex].

I think that [tex]||\varphi_g|| = \int^1_0 |g(t)| dt [/tex] holds. A naive approach to show this would be trying to approximate the step function [tex]h(t)=g(t)/|g(t)|[/tex] by continuous functions; but I guess there is a simpler solution.

BTW the same question was asked here: http://www.mathhelpforum.com/math-h...tial-geometry/146627-dual-space-isometry.html
 
  • #4
Is this correct?

[PLAIN]http://9ya7ng.blu.livefilestore.com/y1pFP94kdkanTL7oWHQXuecgsG7MYfNfM3fHYVt7AE01cgDtbQY8VkjQk94V8H5WceDMp8kOlh-X1WSs79GZtIUTEWTFMCBtceU/q3.jpg
 
Last edited by a moderator:

What is the definition of "dual space"?

The dual space of a vector space V is the set of all linear functionals on V, which are just linear maps from V to the field of scalars. In other words, it is the space of all possible linear combinations of the basis elements of V.

What is the meaning of "isometry" in this context?

In mathematics, an isometry is a transformation that preserves distances between points. In the context of dual spaces, an isometry is a linear map that preserves the norm of vectors, meaning that the distance between two vectors in the original space is equal to the distance between their images in the dual space.

Why is it important to prove that the dual space of X is isometric to C[0,1] Sup Norm?

Proving that the dual space of X is isometric to C[0,1] Sup Norm is important because it allows us to understand the structure of both spaces and their relationship to each other. This result can also be used to simplify calculations and proofs in linear algebra and functional analysis.

What are the steps involved in proving the isometry of the dual space of X to C[0,1] Sup Norm?

The proof involves showing that there exists a bijection between the dual space of X and C[0,1] Sup Norm, and that this bijection preserves the norm of vectors in both spaces. This is typically done by defining an appropriate linear map and showing that it satisfies the necessary properties.

What are some applications of this result in real-world problems?

This result has various applications in areas such as signal processing, control theory, and optimization. It can also be used in the analysis of differential equations, where the dual space of X represents the space of solutions to the given equation. Additionally, this result has implications in the study of Banach spaces and their isometries.

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