Discovery guide 44.1 Discovery guide
Discovery 44.1.
Let \funcdef{T}{\poly_3(\R)}{\matrixring_2(\R)} and \funcdef{S}{\matrixring_2(\R)}{\R^1} be defined by
(a)
Are T and S linear?
(b)
What are the domain and the codomain of the composite transformation S \circ T\text{?}
(c)
Compute a general input-output formula for S \circ T similar to the formulas for S and T defined above.
Discovery 44.2.
Verify that if \funcdef{T}{U}{V} and \funcdef{S}{V}{W} are linear, then \funcdef{S \circ T}{U}{W} is also linear.
Discovery 44.3.
Consider matrix transformations \funcdef{T_A}{\R^3}{\R^2} and \funcdef{S_B}{\R^2}{\R^4} corresponding to matrices
(a)
How should an image vector (S_B \circ T_A)(\uvec{x}) be computed?
(b)
Corollary 42.5.4 says that every transformation \R^3 \to \R^4 is a matrix transformation. Based on the pattern in Task a, what is the matrix of the composite transformation S_B \circ T_A\text{?}
(c)
Describe the pattern in words: The standard matrix of a composition of matrix transformations is .
Describe the pattern in symbols: For \funcdef{T}{\R^n}{\R^m} and \funcdef{S}{\R^m}{\R^\ell}\text{,} \stdmatrixOf{S \circ T} = \underline{\hspace{4.545454545454546em}} \text{.}
Notation.
In analogy with the pattern of Discovery 44.3.c, we will use multiplication notation S T in place of composite function notation S \circ T for all linear transformations.Discovery 44.4.
Let \uppermatring_2(\R) represent the space of 2 \times 2 upper triangular matrices, and let
be defined by
(a)
Compute an input-output formula similar to those above for the composite transformation S T\text{.}
(b)
Based on your result in Task a, what should we call S relative to T\text{?}
(c)
Does it work the other way? Compute an input-output formula for the composite transformation T S\text{.}
(d)
Would Task c have worked if S used the same output formula, but was defined as a transformation \funcdef{S}{\matrixring_2(\R)}{\poly_2(\R)}\text{?} Say, as
(e)
Describe the pattern: If T is an invertible linear transformation, the domain of \inv{T} should be .
Discovery 44.5.
Consider \funcdef{T}{\poly_2(\R)}{\matrixring_2(\R)} defined by
(a)
Based on the pattern from Discovery 44.4.e, if T is invertible, what should the domain of \inv{T} be?
(b)
Is T invertible? To decide, try to define an input-output formula for \funcdef{\inv{T}}{D}{\poly_2(\R)} (where D is the domain for \inv{T} that you identified in Task a) so that your formula βreversesβ T\text{,} just as S reversed the transformation T in Discovery 44.4.
(c)
Compute the image vectors T(x^2) and T(1)\text{.}
What do the results say about the potential invertibility of T\text{?}
(d)
Compute the image vector T(x^2 - 1) (and compare with Task c).
What does the result say about the potential invertibility of T\text{?}
(e)
Describe the pattern: If a transformation \funcdef{T}{V}{W} is invertible, then the kernel of T must be .
So \nullity T must be and then \rank T must be .
For \(\rank T\text{,}\) consider the Dimension Theorem.
Discovery 44.6.
(a)
Based on Discovery 44.5.e, could a transformation \funcdef{T}{\matrixring_5(\R)}{\R^5} be invertible?
(b)
Describe the pattern: If a transformation \funcdef{T}{V}{W} is invertible, then \dim V and \dim W must satisfy: .
Discovery 44.7.
Consider matrix transformation \funcdef{T_A}{\R^3}{\R^3} corresponding to matrix
(a)
Confirm that T_A satisfies the conditions you've identified in both Discovery 44.5.e and Discovery 44.6.b.
Assuming T_A is invertible, what must the domain of \inv{T}_A be?
(b)
Corollary 42.5.4 says that every transformation \R^3 \to \R^3 is a matrix transformation. Based on the calculation patterns from Discovery 44.4, we should have (\inv{T}_A T_A)(\uvec{x}) = \uvec{x} for every \uvec{x} in \R^3\text{.}
So what matrix should correspond to \inv{T}_A\text{?}
(c)
Describe the pattern in words: The standard matrix of the inverse of a (square) matrix transformation is .
Describe the pattern in symbols: For invertible \funcdef{T}{\R^n}{\R^n}\text{,} \stdmatrixOf{\inv{T}} = \underline{\hspace{2.272727272727273em}}\text{.}
Discovery 44.8.
In each of the following, provide a specific example of an isomorphism \funcdef{T}{V}{\R^n} for a specific value of n\text{.} In each case, are there multiple values of n for which this is achievable?
(a)
V = \matrixring_2(\R)\text{.}
(b)
V = \uppermatring_2(\R)\text{.}
(c)
V = \poly_3(\R)\text{.}
(d)
V = \poly_2(\R)\text{.}
(e)
V = \Span \{ \sin x, \cos x, e^x \} (as a subspace of F(\R)).
It's likely that all of your examples followed the same simple pattern of turning the inputs into outputs β what previous course concept were you using (even if unknowingly)?