In functional analysis and operator theory, a bounded linear operator is a linear transformation L : X → Y {\displaystyle L:X\to Y} between topological vector spaces (TVSs) X {\displaystyle X} and Y {\displaystyle Y} that maps bounded subsets of X {\displaystyle X} to bounded subsets of Y . {\displaystyle Y.} If X {\displaystyle X} and Y {\displaystyle Y} are normed vector spaces (a special type of TVS), then L {\displaystyle L} is bounded if and only if there exists some M > 0 {\displaystyle M>0} such that for all x ∈ X , {\displaystyle x\in X,} ‖ L x ‖ Y ≤ M ‖ x ‖ X . {\displaystyle \|Lx\|_{Y}\leq M\|x\|_{X}.} The smallest such M {\displaystyle M} is called the operator norm of L {\displaystyle L} and denoted by ‖ L ‖ . {\displaystyle \|L\|.} A linear operator between normed spaces is continuous if and only if it is bounded.
The concept of a bounded linear operator has been extended from normed spaces to all topological vector spaces.
Outside of functional analysis, when a function f : X → Y {\displaystyle f:X\to Y} is called "bounded" then this usually means that its image f ( X ) {\displaystyle f(X)} is a bounded subset of its codomain. A linear map has this property if and only if it is identically 0. {\displaystyle 0.} Consequently, in functional analysis, when a linear operator is called "bounded" then it is never meant in this abstract sense (of having a bounded image).