Norms of compositions of bounded operators between different spaces

In summary, the operators B and A are bounded, and it follows that AB is also bounded. The norm of AB is less than or equal to the product of the norms of A and B. This can be proven by showing that AB is the smallest number C such that \|ABx\|\leq C\|x\| for each x in the domain.
  • #1
AxiomOfChoice
533
1
Suppose I have [itex]B: X\to Y[/itex] and [itex]A: Y\to Z[/itex], where [itex]X,Y,Z[/itex] are Banach spaces and [itex]B\in \mathcal L(X,Y)[/itex] and [itex]A\in \mathcal L(Y,Z)[/itex]; that is, both of these operators are bounded. Does it follow that [itex]AB \in \mathcal L(X,Z)[/itex] and
[tex]
\| AB \|_{\mathcal L(X,Z)} \leq \|A\|_{\mathcal L(Y,Z)} \|B\|_{\mathcal L(X,Y)}
[/tex]
It seems like this should be the case, but any time I try to prove a functional analytic result like this, I always get mired in uncertainty about the details...
 
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  • #2
Hmmm...okay, well, I think I've found my answer in Eqn. 3.3 of this PDF. Does this suffice for a proof of this result:
[tex]
\| AB \|_{\mathcal L(X,Z)} = \sup_{x\in X, \|x\|_X = 1} \|ABx\|_Z \leq \sup_{x\in X, \|x\|_X = 1} \|A\|_{\mathcal L(Y,Z)} \|Bx\|_Y = \|A\|_{\mathcal L(Y,Z)} \sup_{x\in X, \|x\|_X = 1} \|Bx\|_Y = \|A\|_{\mathcal L(Y,Z)} \|B\|_{\mathcal L(X,Y)}.
[/tex]
 
  • #3
This is ok. Another way of proving it is to note that ##\|A\|## is the smallest number ##C## such that [tex]\|Ax\|\leq \|A\|\|x\|[/tex] for each ##x## in the domain. It follows that for each ##x\in X##: [tex]\|ABx\|\leq \|A\|\|Bx\|\leq \|A\|\|B\|\|x\|[/tex] So ##\|A\|\|B\|## is some number ##C## such that ##\|ABx\|\leq C\|x\|##. It follows that ##AB## is bounded and that ##\|AB\|\leq \|A\|\|B\|##, since ##\|AB\|## is by definition the smallest ##C## such that ##\|ABx\|\leq C\|x\|##.
 

1. What are norms of compositions of bounded operators between different spaces?

The norm of a composition of bounded operators between different spaces is a measure of the size or magnitude of the operator. It describes how much the operator can stretch or distort the input vectors and how much it can amplify the output vectors. The norm is an important concept in functional analysis and is used to study the properties of linear operators.

2. How are norms of compositions of bounded operators between different spaces calculated?

The norm of a composition of bounded operators is typically calculated using the operator norm, which is the maximum value of the operator on a unit ball. This can be computed using various techniques such as the spectral norm, the operator norm, or the induced norm. These methods take into account the size and behavior of the operator on different input vectors.

3. What is the significance of norms of compositions of bounded operators between different spaces?

The norms of compositions of bounded operators play a crucial role in functional analysis, as they help to determine the behavior, properties, and convergence of operators between different spaces. They also aid in studying the stability, invertibility, and continuity of operators, and are used in various applications such as signal processing, control theory, and quantum mechanics.

4. How do norms of compositions of bounded operators between different spaces affect the convergence of series?

The norms of compositions of bounded operators can affect the convergence of series by determining the rate at which the series converges. For example, if the norm of an operator is smaller than 1, then the series will converge faster, while a norm greater than 1 will result in slower convergence. This is important when studying the convergence of series in functional analysis and other related fields.

5. Can norms of compositions of bounded operators between different spaces be compared?

Yes, norms of compositions of bounded operators between different spaces can be compared using various techniques. For instance, the triangle inequality can be used to compare the norms of two different operators, while the ratio test can be used to compare the norms of a single operator on different spaces. These comparisons can provide insights into the behavior and properties of operators between different spaces.

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