Differentiation satisfies for constant scalars , so it is a linear map on suitable vector spaces of differentiable functions. An arbitrary set need not even be a vector space, and an endomorphism interpretation also requires .
For a noninvertible example, take . Then and the kernel of a linear map is the nonzero linear span of , so is not injective. The matrix in this basis is .
For an invertible example, take . In this basis, has matrix , and
Thus differentiation is not always invertible; the domain and codomain determine the answer.
For an invertible matrix whose columns give the new basis in old coordinates, the new matrix is . Multiplicativity of the determinant gives
since .
To justify the cyclic property of the trace directly, for two square matrices ,
Apply it with and :
Thus both the determinant and trace are invariant under change of basis.
Write the ordered basis as . Differentiation gives
The corresponding coordinate vectors form the columns of the representing matrix:
This is an example of differentiation on an exponential-polynomial space.
Choose , and denote the new ordered basis by . The change of basis matrix, with columns expressed in , is
This nonzero determinant proves that the proposed fourth function completes a basis. Express the derivatives in that basis:
Reading off columns therefore gives
Yes. The old matrix is triangular, with determinant zero and trace . The upper-left two-by-two block of the new matrix has determinant zero, so the whole determinant remains zero. Its trace is
Thus
This verifies both change of basis invariants from part (b).

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