Proving ||u||_d = 0 and u=0 in Metric Spaces

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In summary, the author has difficulty proving that $|u|_d = 0$ for a particular u, and suggests that the problem may be different if the metric space is not the real line.
  • #1
Linux
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Let \(\displaystyle (X, d)\) be a metric space, \(\displaystyle AE_0(X) = \{ u : X \rightarrow \mathbb{R} \ : \ u^{-1} (\mathbb{R} \setminus \{0 \} ) \ \ \text{is finite}, \ \sum_{x \in X} u(x)=0 \}\),

for \(\displaystyle x,y \in X, \ x \neq y, \ m_{xy} \in AE_0(X), \ \ m_{xy} (x)=1, \ m_{xy}(y)=-1, \ m_{xy}(z)=0\) for \(\displaystyle z \neq x, y\) and \(\displaystyle m_{xx} \equiv 0\)

for \(\displaystyle u \in AE_0(X), \ ||u||_d = \inf \{ \sum_{k=1}^n |a_k| d(x_k, y_k) \ : \ u= \sum_{k=1}^n a_km_{x_k, y_k}, a_k \in \mathbb{R}, x_k, y_k \in X, n \ge 1 \}\)

How to prove that \(\displaystyle ||u||_d = 0 \ \iff \ u=0\)?

I know it is not so obvious that then all terms in the sum \(\displaystyle \sum_{k=1}^n |a_k| d(x_k, y_k)\) must be zero.

Could you help me out a bit?

Thank you.
 
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  • #2
Linux said:
Let \(\displaystyle (X, d)\) be a metric space, \(\displaystyle AE_0(X) = \{ u : X \rightarrow \mathbb{R} \ : \ u^{-1} (\mathbb{R} \setminus \{0 \} ) \ \ \text{is finite}, \ \sum_{x \in X} u(x)=0 \}\),

for \(\displaystyle x,y \in X, \ x \neq y, \ m_{xy} \in AE_0(X), \ \ m_{xy} (x)=1, \ m_{xy}(y)=-1, \ m_{xy}(z)=0\) for \(\displaystyle z \neq x, y\) and \(\displaystyle m_{xx} \equiv 0\)

for \(\displaystyle u \in AE_0(X), \ ||u||_d = \inf \{ \sum_{k=1}^n |a_k| d(x_k, y_k) \ : \ u= \sum_{k=1}^n a_km_{x_k, y_k}, a_k \in \mathbb{R}, x_k, y_k \in X, n \ge 1 \}\)

How to prove that \(\displaystyle ||u||_d = 0 \ \iff \ u=0\)?

I know it is not so obvious that then all terms in the sum \(\displaystyle \sum_{k=1}^n |a_k| d(x_k, y_k)\) must be zero.

Could you help me out a bit?

Thank you.
Hi Linux, and welcome to MHB!

The problem of showing that $\|u\|_d = 0$ implies $u=0$ seems difficult, and I have not been able to solve it. See http://mathhelpboards.com/analysis-50/could-you-check-my-solution-13108.html.
 
  • #3
Hi,

I have not much time so I may be wrong but doing it fast I think that the set $\{(a_{k},x_{k},y_{k}) \ : \ u=\displaystyle\sum_{k=1}^{n}a_{k}m_{x_{k},y_{k}}\}$ is finite, so the infimum is always reched (i.e., it's a minimum) and your norm is given by series of positive terms, si the minimum being zero implies that all terms are zero.

I will think on it with caution later.
 
  • #4
Fallen Angel said:
I have not much time so I may be wrong but doing it fast I think that the set $\{(a_{k},x_{k},y_{k}) \ : \ u=\displaystyle\sum_{k=1}^{n}a_{k}m_{x_{k},y_{k}}\}$ is finite, so the infimum is always reached (i.e., it's a minimum) and your norm is given by series of positive terms, so the minimum being zero implies that all terms are zero.
The problem is that there may be different representations of $u$ using points other than those at which $u$ is nonzero.

Suppose for example that the underlying metric space is the real line, and that $u = m_{0,1}$ (so that $u(0) = 1$, $u(1) = -1$ and $u$ is zero at all other points). Then $u$ can also be expressed as $u = m_{0,1/2} + m_{1/2,1}$, or as \(\displaystyle u = \sum_{k=0}^{999}m_{k/1000,(k+1)/1000}.\) It is intuitively clear that $\|u\|_d$ cannot be decreased by such procedures, but a formal proof seems very elusive.
 
  • #5


To prove that ||u||_d = 0 \ \iff \ u=0, we can start by considering the definition of ||u||_d. From the given definition, we can see that ||u||_d = 0 if and only if the infimum of the set is equal to 0. This means that for any given \epsilon > 0, there exists a sum \sum_{k=1}^n |a_k| d(x_k, y_k) such that ||u||_d < \epsilon.

Now, if ||u||_d = 0, then this means that for any \epsilon > 0, there exists a sum \sum_{k=1}^n |a_k| d(x_k, y_k) such that ||u||_d < \epsilon. However, since ||u||_d = 0, this sum must be equal to 0. This implies that all terms in the sum must be equal to 0, since otherwise, the sum would be greater than 0. In other words, we must have a_k = 0 for all k, which means that u = 0.

Conversely, if u = 0, then all the terms in the sum \sum_{k=1}^n |a_k| d(x_k, y_k) must be equal to 0, since u = \sum_{k=1}^n a_km_{x_k, y_k} and m_{x_k, y_k} \neq 0 for any k. This means that ||u||_d = 0, since the infimum of the set is equal to 0.

Therefore, we have shown that ||u||_d = 0 \ \iff \ u=0, which proves the desired statement.
 

FAQ: Proving ||u||_d = 0 and u=0 in Metric Spaces

What is the definition of "Norm given by infimum"?

The norm given by infimum, also known as the infimum norm, is a mathematical concept used to measure the size or magnitude of a vector. It is defined as the smallest lower bound on the magnitude of the vector's components.

How is the infimum norm calculated?

The infimum norm is calculated by taking the absolute value of each component of the vector, finding the smallest value among these absolute values, and then taking the infimum (or greatest lower bound) of these values.

What is the difference between the infimum norm and other types of norms?

The main difference between the infimum norm and other types of norms, such as the Euclidean norm or the maximum norm, is the way they measure the size of a vector. The infimum norm takes into account the smallest component of the vector, while other norms may consider all components equally.

What are the applications of the infimum norm?

The infimum norm is commonly used in optimization problems, particularly in linear programming and convex optimization. It is also used in functional analysis and other areas of mathematics to define and analyze vector spaces.

Can the infimum norm be negative?

No, the infimum norm is always a positive value. This is because it is defined as the smallest lower bound, and a lower bound cannot be negative. However, the vector itself may have negative components, which will be taken into account when calculating the infimum norm.

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