Chapter 14
Advanced Linear Algebra · 24 exercises
Problem 1
Show that if \(\tau: W \rightarrow X\) is a linear map and \(b: U \times V \rightarrow W\) is bilinear, then \(\tau \circ b: U \times V \rightarrow X\) is bilinear.
2 step solution
Problem 4
Let \(\mathcal{B}=\left\\{u_{i} \mid i \in I\right\\}\) be a basis for \(U\) and let \(\mathcal{C}=\left\\{v_{j} \mid j \in J\right\\}\) be a basis for \(V\). Show that the set $$ \mathcal{D}=\left\\{u_{i} \otimes v_{j} \mid i \in I, j \in J\right\\} $$ is a basis for \(U \otimes V\) by showing that it is linearly independent and spans.
2 step solution
Problem 5
Prove that the following property of a pair \((W, g: U \times V \rightarrow W)\) with \(g\) bilinear characterizes the tensor product \((U \otimes V, t: U \times V \rightarrow U \otimes V)\) up to isomorphism, and thus could have been used as the definition of tensor product: For a pair \((W, g: U \times V \rightarrow W)\) with \(g\) bilinear if \(\left\\{u_{i}\right\\}\) is a basis for \(U\) and \(\left\\{v_{i}\right\\}\) is a basis for \(V\), then \(\left\\{g\left(u_{i}, v_{j}\right)\right\\}\) is a basis for \(W\).
5 step solution
Problem 6
Prove that \(U \otimes V \approx V \otimes U\).
5 step solution
Problem 9
Let \(\mathcal{B}=\left\\{b_{i}\right\\}\) be a basis for \(U\) and \(\mathcal{C}=\left\\{c_{i}\right\\}\) be a basis for \(V\). Show that any function \(f: \mathcal{B} \times \mathcal{C} \rightarrow W\) can be extended to a linear function \(\bar{f}: U \otimes V \rightarrow W\). Deduce that the function \(f\) can be extended in a unique way to a bilinear map \(\widehat{f}: U \times V \rightarrow W\). Show that all bilinear maps are obtained in this way.
6 step solution
Problem 11
Let \(S \subseteq U\) and \(T \subseteq V\) be subspaces of vector spaces \(U\) and \(V\), respectively. Show that $$ (S \otimes V) \cap(U \otimes T) \approx S \otimes T $$
3 step solution
Problem 12
Let \(S_{1}, S_{2} \subseteq U\) and \(T_{1}, T_{2} \subseteq V\) be subspaces of \(U\) and \(V\), respectively. Show that $$ \left(S_{1} \otimes T_{1}\right) \cap\left(S_{2} \otimes T_{2}\right) \approx\left(S_{1} \cap S_{2}\right) \otimes\left(T_{1} \otimes T_{2}\right) $$
5 step solution
Problem 13
Find an example of two vector spaces \(U\) and \(V\) and a nonzero vector \(x \in U \otimes V\) that has at least two distinct (not including order of the terms) representations of the form $$ x=\sum_{i=1}^{n} u_{i} \otimes v_{i} $$ where the \(u_{i}\) 's are linearly independent and so are the \(v_{i}^{\prime}\) s.
3 step solution
Problem 14
Let \(\iota_{X}\) denote the identity operator on a vector space \(X\). Prove that \(\iota_{V} \odot \iota_{W}=\iota_{V \otimes W}\).
4 step solution
Problem 15
Suppose that \(\tau_{1}: U \rightarrow V, \tau_{2}: V \rightarrow W\) and \(\sigma_{1}: U^{\prime} \rightarrow V_{K}, \sigma_{2}: V_{K} \rightarrow W^{\prime}\). Prove that $$ \left(\tau_{2} \circ \tau_{1}\right) \odot\left(\sigma_{2} \circ \sigma_{1}\right)=\left(\tau_{2} \odot \sigma_{2}\right) \circ\left(\tau_{1} \odot \sigma_{1}\right) $$
2 step solution
Problem 16
Connect the two approaches to extending the base field of an \(F\)-space \(V\) to \(K\) (at least in the finite-dimensional case) by showing that \(F^{n} \otimes_{F} K \approx(K)^{n}\).
6 step solution
Problem 17
Prove that in a tensor product \(U \otimes U\) for which \(\operatorname{dim}(U) \geq 2\) not all vectors have the form \(u \otimes v\) for some \(u, v \in U\). Hint. Suppose that \(u, v \in U\) are linearly independent and consider \(u \otimes v+v \otimes u\).
7 step solution
Problem 18
Prove that for the block matrix $$ M=\left[\begin{array}{ll} A & B \\ 0 & C \end{array}\right]_{\text {block }} $$ we have \(d(M)=d(A) d(C)\).
4 step solution
Problem 19
Let \(A, B \in M_{n}(F)\). Prove that if either \(A\) or \(B\) is invertible, then the matrices \(A+\alpha B\) are invertible except for a finite number of \(\alpha\) 's. The Tensor Product of Matrices
5 step solution
Problem 20
Let \(A=\left(a_{i, j}\right)\) be the matrix of a linear operator \(\tau \in
\mathcal{L}(V)\) with respect to the ordered basis \(\mathcal{A}=\left(u_{1},
\ldots, u_{n}\right)\). Let \(B=\left(b_{i, j}\right)\) be the matrix of a linear
operator \(\sigma \in \mathcal{L}(V)\) with respect to the ordered basis
\(\mathcal{B}=\left(v_{1}, \ldots, v_{m}\right)\). Consider the ordered basis
\(\mathcal{C}=\left(u_{i} \otimes v_{j}\right)\) ordered lexicographically; that
is \(u_{i} \otimes v_{j}
5 step solution
Problem 21
Show that the tensor product is not, in general, commutative.
4 step solution
Problem 22
Show that the tensor product \(A \otimes B\) is bilinear in both \(A\) and \(B\).
2 step solution
Problem 23
Show that \(A \otimes B=0\) if and only if \(A=0\) or \(B=0\).
5 step solution
Problem 24
Show that a) \((A \otimes B)^{t}=A^{t} \otimes B^{t}\) b) \((A \otimes B)^{*}=A^{*} \otimes B^{*}(\) when \(F=\mathbb{C})\)
8 step solution
Problem 26
Suppose that \(A_{m, n}, B_{p, q}, C_{n, k}\) and \(D_{q, r}\) are matrices of the given sizes. Prove that $$ (A \otimes B)(C \otimes D)=(A C) \otimes(B D) $$ Discuss the case \(k=r=1\).
6 step solution
Problem 27
Prove that if \(A\) and \(B\) are nonsingular, then so is \(A \otimes B\) and $$ (A \otimes B)^{-1}=A^{-1} \otimes B^{-1} $$
3 step solution
Problem 28
Prove that \(\operatorname{tr}(A \otimes B)=\operatorname{tr}(A) \cdot \operatorname{tr}(B)\).
4 step solution
Problem 29
Suppose that \(F\) is algebraically closed. Prove that if \(A\) has eigenvalues \(\lambda_{1}, \ldots, \lambda_{n}\) and \(B\) has eigenvalues \(\mu_{1}, \ldots, \mu_{m}\), both lists including multiplicity, then \(A \otimes B\) has eigenvalues \(\left\\{\lambda_{i} \mu_{j} \mid i \leq n, j \leq m\right\\}\), again counting multiplicity.
3 step solution
Problem 30
Prove that \(\operatorname{det}\left(A_{n, n} \otimes B_{m, m}\right)=\left(\operatorname{det}\left(A_{n, n}\right)\right)^{m}\left(\operatorname{det}\left(B_{m, m}\right)\right)^{n}\).
3 step solution