Isomorphic vector spaces/Introduction/Section


Let denote a field and let and denote -vector spaces. A bijective linear mapping

is called isomorphism.

An isomorphism from to is called automorphism.


Let denote a field. Two -vector spaces and are called isomorphic, if there exists an isomorphism

from to .


Let denote a field and let and denote finite-dimensional -vector spaces. Then and are isomorphic to each other if and only if their dimension

coincides. In particular, an -dimensional -vector space is isomorphic to .

Proof



An isomorphism between an -dimensional vector space and the standard space is essentially equivalent with the choice of a basis of . For a basis

we associate the linear mapping

which maps from the standard space to the vector space by sending the -th standard vector to the -th basis vector of the given basis. This defines a unique linear mapping due to fact. Due to exercise, this mapping is bijective. It is just the mapping

The inverse mapping

is also linear, and it is called the coordinate mapping for this basis. The -th component of this map, that is, the composed mapping

is called the -th coordinate function. It is denoted by . It assigns to vector with the unique representation

the coordinate . Note that the linear mapping depends on the basis, not only on the vector .

If an isomorphism

is given, then the images

form a basis of .