 Continuous linear extension

In functional analysis, it is often convenient to define a linear transformation on a complete, normed vector space X by first defining a linear transformation on a dense subset of X and then extending to the whole space via the theorem below. The resulting extension remains linear and bounded (thus continuous).
This procedure is known as continuous linear extension.
Contents
Theorem
Every bounded linear transformation from a normed vector space X to a complete, normed vector space Y can be uniquely extended to a bounded linear transformation from the completion of X to Y. In addition, the operator norm of is c iff the norm of is c.
This theorem is sometimes called the B L T theorem, where B L T stands for bounded linear transformation.
Application
Consider, for instance, the definition of the Riemann integral. A step function on a closed interval [a,b] is a function of the form: where are real numbers, , and 1_{S} denotes the indicator function of the set S. The space of all step functions on [a,b], normed by the norm (see Lp space), is a normed vector space which we denote by . Define the integral of a step function by: . as a function is a bounded linear transformation from into .^{[1]}
Let denote the space of bounded, piecewise continuous functions on [a,b] that are continuous from the right, along with the norm. The space is dense in , so we can apply the B.L.T. theorem to extend the linear transformation to a bounded linear transformation from to . This defines the Riemann integral of all functions in ; for every , .
The Hahn–Banach theorem
The above theorem can be used to extend a bounded linear transformation to a bounded linear transformation from to Y, if S is dense in X. If S is not dense in X, then the Hahn–Banach theorem may sometimes be used to show that an extension exists. However, the extension may not be unique.
References
 Reed, Michael; Barry Simon (1980). Methods of Modern Mathematical Physics, Vol. 1: Functional Analysis. San Diego: Academic Press. ISBN 0125850506.
Footnotes
 ^ Here, is also a normed vector space; is a vector space because it satisfies all of the vector space axioms and is normed by the absolute value function.
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