Andrew Thangaraj
Aug-Nov 2020
\(S,T:V\to W\) are linear maps, \(\lambda\in F\). Sum of \(S\) and \(T\), denoted \(S+T\), is defined as \[(S+T)v = Sv + Tv.\] The scalar product of \(\lambda\) and \(T\), denoted \(\lambda T\), is defined as \[(\lambda T)v = \lambda (Tv).\]
Results
\(S+T\) and \(\lambda T\) are linear maps from \(V\to W\).
\(\mathcal{L}(V,W)\): set of all linear maps from \(V\) to \(W\)
\(\mathcal{L}(V,W)\) is a vector space over \(F\)
under addition and scalar multiplication defined above
additive identity: zero map
\(U,V,W\): vector spaces over \(F\) and \(T:U\to V\), \(S:V\to W\) are linear maps. Product of \(S\) and \(T\), denoted \(ST\), is defined as \[(ST)u = S(Tu).\] \(ST\): linear map from \(U\) to \(W\); composition of the two maps \(T\) and \(S\)
Algebraic properties of linear maps
Multiplication is associative
Multiplication need not be commutative
If \(ST\) is defined, \(TS\) may not even be defined
Even if \(ST\) and \(TS\) are defined, they may not be the same map
Distributive property
\[\begin{align} \begin{bmatrix} A_{11}&\cdots&A_{1n}\\ \vdots&\ddots&\vdots\\ A_{m1}&\cdots&A_{mn} \end{bmatrix}+\begin{bmatrix} B_{11}&\cdots&B_{1n}\\ \vdots&\ddots&\vdots\\ B_{m1}&\cdots&B_{mn} \end{bmatrix}&=\begin{bmatrix} A_{11}{+}B_{11}&\cdots&A_{1n}{+}B_{1n}\\ \vdots&\ddots&\vdots\\ A_{m1}{+}B_{m1}&\cdots&A_{mn}{+}B_{mn} \end{bmatrix}\\[5pt] \lambda\begin{bmatrix} A_{11}&\cdots&A_{1n}\\ \vdots&\ddots&\vdots\\ A_{m1}&\cdots&A_{mn} \end{bmatrix}&=\begin{bmatrix} \lambda A_{11}&\cdots&\lambda A_{1n}\\ \vdots&\ddots&\vdots\\ \lambda A_{m1}&\cdots&\lambda A_{mn} \end{bmatrix} \end{align}\]
\(V,W\): finite-dimensional and \(S,T:V\to W\). Fix bases for \(V\) and for \(W\).
\(M(S), M(T), M(S+T), M(\lambda T)\) are matrices for \(S\), \(T\), \(S+T\) and \(\lambda T\) with respect to the chosen bases. Then, \[\begin{align} M(S+T)&=M(S)+M(T)\\ M(\lambda T)&=\lambda M(T) \end{align}\]
\[\begin{bmatrix} A_{11}&\cdots&A_{1n}\\ \vdots&\ddots&\vdots\\ A_{m1}&\cdots&A_{mn} \end{bmatrix}\begin{bmatrix} B_{11}&\cdots&B_{1k}\\ \vdots&\ddots&\vdots\\ B_{n1}&\cdots&B_{nk} \end{bmatrix}=\begin{bmatrix} C_{11}&\cdots&C_{1k}\\ \vdots&\ddots&\vdots\\ C_{m1}&\cdots&C_{mk} \end{bmatrix}\]
\(C_{ij}=\sum_{l=1}^n A_{il}B_{lj}\)
(dot product of \(i\)-th row of \(A\) and \(j\)-th column of \(B\))
\(U,V,W\): finite-dimensional and \(T:U\to V\), \(S:V\to W\). Fix bases for \(U\), \(V\) and \(W\).
\(M(S), M(T), M(ST)\) are matrices for \(S\), \(T\) and \(ST\) with respect to the chosen bases. Then, \[M(ST)=M(S)M(T)\]
\(\begin{bmatrix} b_1&b_2&\cdots&b_n \end{bmatrix}\begin{bmatrix} a_1\\a_2\\\vdots\\a_n \end{bmatrix}=a_1b_1+\cdots+a_nb_n\)
\(S: F^n\to F\), \(T:F\to F^n\)
\(ST: F\to F\)
\(\begin{bmatrix} a_1\\a_2\\\vdots\\a_m \end{bmatrix}\begin{bmatrix} b_1&b_2&\cdots&b_n \end{bmatrix}=\begin{bmatrix} a_1b_1&a_1b_2&\cdots&a_1b_n\\ a_2b_1&a_2b_2&\cdots&a_2b_n\\ \vdots&\vdots&\vdots&\vdots\\ a_mb_1&a_mb_2&\cdots&a_mb_n \end{bmatrix}\)
\(S:F\to F^m\), \(T:F^n\to F\)
\(ST: F^n\to F^m\)
\[\begin{bmatrix} A_{11}&\cdots&A_{1n}\\ \vdots&\ddots&\vdots\\ A_{m1}&\cdots&A_{mn} \end{bmatrix}\begin{bmatrix} B_{11}&\cdots&B_{1k}\\ \vdots&\ddots&\vdots\\ B_{n1}&\cdots&B_{nk} \end{bmatrix}=\begin{bmatrix} C_{11}&\cdots&C_{1k}\\ \vdots&\ddots&\vdots\\ C_{m1}&\cdots&C_{mk} \end{bmatrix}\]
\(C_{ij}=\sum_{l=1}^n A_{il}B_{lj}\)
\(C_{ij}\): (\(i\)-th row of \(A\)) \(\times\) (\(j\)-th column of \(B\))
\(i\)-th row of \(C\): (\(i\)-th row of \(A\)) \(\times\) \(B\)
\(j\)-th column of \(C\): \(A\) \(\times\) (\(j\)-th column of \(B\))
\(C=\sum_{l=1}^n (l\)-th column of \(A) \times (l\)-th row of \(B)\)