0

Here is the question:

Unbounded linear functional maps every open ball to $\mathbb{R}$?

Here is my questions to the answers there:

1-I am not getting the total idea of the solution and what are we exactly doing, could anyone explain to me the total idea?

2- In this paragraph : "Any other ball $B$ in $X$ is of the form $x+\delta X_1$ for some $\delta>0$. Given such $\delta$, for any fixed $t\in\mathbb R$ by the previous paragraph there exists $y\in X_1$ with $f(y)=(t-f(x))/\delta$. Then $f(x+\delta y)=t$. So $f(B)=\mathbb R$." in the first solution, I am not sure exactly why we are sure from this "there exists $y\in X_1$ with $f(y)=(t-f(x))/\delta$." could anyone explain this for me please?

3- I am not sure why $X_1=-X_1$? in the first solution, could anyone explain this for me please?

4- I do not understand why it may be necessarily to replace $x_{n}$ with $-x_{n}$?

5- why we are taking $t\in [0,1]$ and how this shows that $f(X_{1})$ contains the whole segment $[0, f(x_{n})]$ and why we want to show this?

6-convex set means the line segment between any 2 points in the set should lie totally inside the set, how is this used here?

  • 1
    Your questions indicate some lack of understanding of basic facts about linearity and norms. While the steps can be explained, these are things you should have learned well before ever delving into the world of functional analysis. You need to go back and review the basics - hard - before attempting this material. Even if you get past this, you are just going to run into the the same issues over and over again. – Paul Sinclair Feb 05 '20 at 03:08

1 Answers1

3

(1)

  • $X_1$ contains $0$, and $f(0) = 0$.
  • Because $f$ is unbounded, $X_1$ must have points $x$ for which $f(x)$ is as large as desired. I.e., for any real number $r > 0$, we can find an $x$ such that $f(x) > r$.
  • $X_1$ also contains every point of the line segment connecting $0$ to $x$
  • Since $f$ is linear, $f(X_1)$ must likewise contain every number between $0 = f(0)$ and $f(x)$.
  • Since $0 < r < f(x), f(X_1)$ must contain $r$. Since $r$ was arbitrary, every positive real number is in $f(X_1)$.
  • For $r < 0$, there is some $y \in X_1$ with $f(y) = -r$, and therefore $f(-y) = r$. Since $-y \in X_1$, every negative real number is also in $f(X_1)$, as is $0$.
  • Hence every real number is in $f(X_1)$.
  • Every other open ball is a translation and rescaling of $X_1$. Linearity preserves translations and rescaling. But every translation and rescaling of $\Bbb R$ is still all of $\Bbb R$. So every open ball must be carried to $\Bbb R$ by $f$.

(2) $(t - f(x))/\delta$ is a real number, and he just showed that every real number is in $f(X_1)$.

(3) $\|x\| = \|-x\|$.

(4) Because until this point, we only know that $|f(x_n)| > n$. It could be either $f(x_n) > n$ or $f(x_n) < -n$. But if $f(x_n) < -n$, then $f(-x_n) = -f(x_n) > n$. So if we replace the original $x_n$ with its opposite, we can assure that $f(x_n) > n$ always.

(5) If $0 \le r \le n$, let $t = r/f(x_n)$. Because $f(x_n) > n, 0 \le t < 1$. But $f(tx_n) = tf(x_n) = r$. Thus every number $r \in [0,n]$ is the image of $f(tx_n)$ for some $t \in [0,1]$. As for why we want show this. It is because the entire point is the show that $f(X_1)$ contains all real numbers, not just arbitrarily large ones.

(6) The stuff you asked about in (5) is a convexity argument. $f$ carries the line segment from $0$ to $x$ in $X_1$ onto the line segment $[f(0), f(x)]$ in $\Bbb R$. Because of the properties of linearity and balls, it was not necessary to directly cast it in terms of convexity, but it is that convexity that makes the proof work.

Paul Sinclair
  • 43,643