No. Over any field , take , let be the identity operator, and choose the vector subspaceBoth and the quotient vector space have dimension one. A one-dimensional vector space has no nonzero proper vector subspace, so neither can have a nonzero proper invariant subspace. The induced linear map on a quotient vector space is again the identity operator.
However, is another nonzero proper vector subspace of , and . HenceThe hypotheses do not prevent a direct sum whose two summands are invariant subspaces.
First assume is injective. If were not surjective, its image of a linear map would be a proper vector subspace of . Choose a basis of and use basis extension to obtain a basis of , with . There is a linear functional withIt is nonzero and vanishes on , so , contradicting injectivity. Equivalently, the annihilator of a vector subspace would give a nonzero kernel for . Therefore
Now assume is surjective. If , basis extension gives a linear functional with : include in a basis and take its coordinate functional. By surjectivity, for some . Buta contradiction. Hence , which proves
Past exam of the mathematics course of the University of Cambridge 2002 ia Paper 1 8D Solution Created 2026-09-24 Updated 2026-10-14
A vector space over the real numbers is a set with an addition making it an abelian group and a scalar multiplication by satisfying, for scalars and vectors , the identities , , and . A vector subspace is a nonempty subset closed under addition and scalar multiplication; a proper vector subspace is one unequal to . A spanning set is a set whose finite linear combinations give every vector of . A basis is a linearly independent spanning set. The dimension is the number of vectors in a basis, or its cardinality when the basis is infinite.
The sum of vector subspaces and their intersection of vector subspaces areBoth are vector subspaces: addition and scalar multiplication preserve the displayed forms or simultaneous membership. The intersection of vector subspaces is never empty because .
For the two given hyperplanes, adding and subtracting their defining equations gives and . HenceThese two nonzero vectors are orthogonal, and consequently form an orthogonal basis of the intersection of vector subspaces. Put and . Direct substitution gives , . Their dot products with vanish, and . Each defining equation of or is one nonzero linear constraint in four variables, so each vector subspace has dimension three. Thus each space has the indicated orthogonal basis:The last four vectors are nonzero and mutually orthogonal, so they are a basis of . They lie in , proving . The dimension identity is therefore verified numerically: