ABSTRACT

It is typical in the study of algebra to begin with the definition of its basic objects and investigate their properties. Then it is customary to introduce maps (functions, transformations) between these objects that preserve the algebraic character of the object. The relevant types of maps when the objects are vector spaces are linear transformations. In this chapter, we introduce and begin to develop the theory of linear transformations between vector spaces. In the first section, we define the concept of a linear transformation and give examples. In the second section, we define the kernel of a linear transformation. We then obtain a criterion for a linear transformation to be injective (one-to-one) in terms of the kernel. In section three, we prove some fundamental theorems about linear transformations, referred to as isomorphism theorems. In section four we consider a linear transformation T from an n-dimensional vector space V to an m-dimensional vector space W and show how, using a fixed pair of bases for V and W, respectively, to obtain an m× n matrix M for the linear transformation. This is used to define addition and multiplication of matrices. In the fifth section, we introduce the notion of an algebra over a field F as well as an isomorphism of algebras. We show that for a finite-dimensional vector space V over a field F the space L(V, V ) of linear operators on V is an algebra over F.We will also introduce the spaceMnn(F) of n×n matrices with entries in the field F and show that this is an algebra isomorphic to L(V, V ) when dim(V ) = n. In the final section, we study linear transformations that are bijective. We investigate the relationship between two matrices, which arise as the matrix of the same transformation but with respect to different bases for the domain and codomain. This gives rise to the notion of a change of basis matrix. When the transformation is an operator on a space V this motivates the definition of similarity of operators and matrices.