Section 1.8
1. Let Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle L,K:V\to V}
be linear maps between finite-dimensional vector spaces that satisfy Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle L\circ K=0}
. Is it true that Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle K\circ L=0}
?
| Solution: |
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| No. in general composition of functions is not commutative. By the theorem that any linear map can be expressed as a matrix, finding a counterexample comes down to finding two matrices Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle A,B}
such that Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle AB=0}
but Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle BA\neq 0}
. Here is one example of functions: . Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle L(x,y)=(x,0),K(x,y)=(0,x+y)}
. Then we have Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle L\circ K(x,y)=L(0,x+y)=(0,0)}
but Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle K\circ L(x,y)=K(x,0)=(0,x+0)}
so Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle L\circ K=0}
but Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle K\circ L\neq 0}
. |
4. Show that a linear map Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle L:V\to W}
is one-to-one if and only if Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle L(x)=0}
implies .
| Proof: |
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| First note that for any linear map Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle L(0)=0}
because .
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6. Let Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle V\neq \{0\}}
be finite-dimensional and assume that
Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle L_{1},L_{2},...,L_{n}:V\to V}
are linear operators. Show that if Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle L_{1}\circ L_{2}\circ \cdots \circ L_{n}=0}
then at least one of the Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle L_{i}}
are not one-to-one.
| Proof: |
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| I will use proof by contrapositive. The equivalent statement would then be "`If all of the Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle L_{i}}
are one-to-one, then Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle L_{1}\circ \cdots \circ L_{n}\neq 0}
. Then this becomes very easy if you know the fact from set theory that the composition of one-to-one functions is a one-to-one function. This gives the following. Suppose that Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle L_{1},...,L_{n}}
are all one-to-one. Then is also a one-to-one function and so the only input that will give an output of 0 is the input from problem 4. Therefore Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle L_{1}\circ \cdots \circ L_{n}\neq 0}
and we are done.
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13. Consider the map
Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle \Psi :\mathbb {C} \to {\text{Mat}}_{2\times 2}(\mathbb {R} )}
defined by
Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle \Psi (\alpha +i\beta )={\begin{bmatrix}\alpha &-\beta \\\beta &\alpha \end{bmatrix}}}
(
a) Show that this is Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle \mathbb {R} }
-linear and one-to-one, but not onto. Find an example of a matrix in that does not come from .
| Proof: |
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| To show this is Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle \mathbb {R} -}
linear let Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle z_{1}=\alpha _{1}+i\beta _{1},z_{2}=\alpha _{2}+i\beta _{2}\in \mathbb {C} }
. Then: Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle \Psi (z_{1}+z_{2})=\Psi (\alpha _{1}+i\beta _{1}+\alpha _{2}+i\beta _{2})=\Psi (\alpha _{1}+\alpha _{2}+i(\beta _{1}+\beta _{2}))={\begin{bmatrix}\alpha _{1}+\alpha _{2}&-\beta _{1}-\beta _{2}\\\beta _{1}+\beta _{2}&\alpha _{1}+\alpha _{2}\end{bmatrix}}={\begin{bmatrix}\alpha _{1}&-\beta _{1}\\\beta _{1}&\alpha _{1}\end{bmatrix}}+{\begin{bmatrix}\alpha _{2}&-\beta _{2}\\\beta _{2}&\alpha _{2}\end{bmatrix}}=\Psi (z_{1})+\Psi (z_{2})}
|