Archetype T Archetype T
β¬ Summary Domain and codomain are polynomials. Domain has dimension 5, while codomain has dimension 6. Is injective, can not be surjective.
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Definition A linear transformation (
Definition LT).
T:P4βP5,T(p(x))=(xβ2)p(x)
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Kernel A basis for the kernel of the linear transformation (
Definition KLT).
{ }
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Injective? Is the linear transformation injective (
Definition ILT)? Yes.
Since the kernel is trivial Theorem KILT tells us that the linear transformation is injective.
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Spanning Set for Range A spanning set for the range of a linear transformation (
Definition RLT) can be constructed easily by evaluating the linear transformation on a standard basis (
Theorem SSRLT).
{xβ2,x2β2x,x3β2x2,x4β2x3,x5β2x4,x6β2x5}
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Range A basis for the range of the linear transformation (
Definition RLT). If the linear transformation is injective, then the spanning set just constructed is guaranteed to be linearly independent (
Theorem ILTLI) and is therefore a basis of the range with no changes. Injective or not, this spanning set can be converted to a βniceβ linearly independent spanning set by making the vectors the rows of a matrix (perhaps after using a vector representation), row-reducing, and retaining the nonzero rows (
Theorem BRS), and perhaps un-coordinatizing.
{β132x5+1,β116x5+x,β18x5+x2,β14x5+x3,β12x5+x4}
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Surjective? Is the linear transformation surjective (
Definition SLT)? No.
The dimension of the range is 5, and the codomain (P5) has dimension 6. So the transformation is not surjective. Notice too that since the domain P4 has dimension 5, it is impossible for the range to have a dimension greater than 5, and no matter what the actual definition of the function, it cannot possibly be surjective in this situation.
To be more precise, verify that 1+x+x2+x3+x4βR(T), by setting the output equal to this vector and seeing that the resulting system of linear equations has no solution, i.e. is inconsistent. So the preimage, Tβ1(1+x+x2+x3+x4), is nonempty. This alone is sufficient to see that the linear transformation is not onto.
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Subspace Dimensions Subspace dimensions associated with the linear transformation (
Definition ROLT,
Definition NOLT). Verify
Theorem RPNDD, and examine parallels with earlier results for matrices.
rank=5nullity=0domain=5
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Invertible? Is the linear transformation invertible (
Definition IVLT, and examine parallels with the existence of matrix inverses.)? No.
The relative dimensions of the domain and codomain prohibit any possibility of being surjective, so apply Theorem ILTIS.
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Matrix Representation Matrix representation of the linear transformation, as given by
Definition MR and explained by
Theorem FTMR.
domain basis={1,x,x2,x3,x4}
codomain basis={1,x,x2,x3,x4,x5}
matrix representation=[β200001β200001β200001β200001β200001]