Writing the given bases as and , a basis of the Cartesian product with its componentwise vector space operations isThis is the direct sum basis. Therefore . The construction includes zero-dimensional factors, whose corresponding portion of the basis is empty.
The intersection of vector subspaces contains zero, so . If and are scalars, thenbecause by the vector subspace conditions. These pairs belong to , since both and belong to the required factors. Thus is a vector subspace of .
Define by . It is well-defined by the definition of , andThus is a linear map. If , comparing first components gives , proving injectivity. Every element of has the form , proving surjectivity. Hence is a linear isomorphism, with inverse , and .
Every output lies in the sum of subspaces , since it is a linear combination of members of the two vector subspaces. For , and scalars ,Therefore is a linear map. Every vector in is such an output: group the terms of any linear combination from according to their originating vector subspace. Thus the addition map of subspaces is also surjective.
The kernel of a linear map is precisely , sincePart (c) gives . Apply the rank-nullity theorem to the finite-dimensional vector space , and then parts (a) and (b):This proves the dimension formula for a sum of subspaces. The kernel of a linear map records exactly the freedom to transfer a shared vector from one summand to the other without changing their sum.
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