Alphabeta Math
TheoremStatement: AI-adaptedProof: AI-adaptedprecheck passjudge pass (z-ai/glm-5.2)audited 2026-07-28
How statement and proof provenance work

The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.

  • Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
  • AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
  • AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.

These labels describe origin, not correctness: citations and verification chips remain separate evidence.

The dimension formula: for finite-dimensional linear subspaces U and W of V, the subspaces U+W and U∩W are finite-dimensional and dim⁡F(U+W)+dim⁡F(U∩W)=dim⁡FU+dim⁡FW

Statement

Let V be a vector space over a field F (Vector space over a field) and let U and W be linear subspaces of V (Linear subspace of a vector space), both finite-dimensional over F (Finite-dimensional vector space, and its dimension dim⁡FV; infinite-dimensional means having no finite basis). Then U∩W and U+W (The sum U+W of two linear subspaces and the sum ∑i<nUi of a finite family) are finite-dimensional and

dim⁡F(U+W)  +  dim⁡F(U∩W)  =  dim⁡FU  +  dim⁡FW.

The ambient space V is arbitrary and need not be finite-dimensional.

The two boundary cases. If U∩W={0V} the formula reads dim⁡F(U⊕W)=dim⁡FU+dim⁡FW, since dim⁡F{0V}=0; if U=W it reads dim⁡FU+dim⁡FU=dim⁡FU+dim⁡FU.

No choice principle is used. The bases of U and of W extending a basis of U∩W come from claim 3 of If dim⁡FV=n and U is a linear subspace of V, then U is finite-dimensional, dim⁡FU≤n, and dim⁡FU=n if and only if U=V, which is proved by a largest-independent-subset argument inside a finite-dimensional space. Zorn's lemma is not used anywhere below, and the Zorn-based extension theorem of this page is neither cited nor needed; the remarks say where the difference lies.

Facts & Assumptions

Given: A field F; a vector space V over F; and finite-dimensional linear subspaces U and W of V; write u:=dim⁡FU and w:=dim⁡FW.

[L2]

The intersection of two linear subspaces of V is a linear subspace of V (The intersection of a nonempty family of linear subspaces of V is a linear subspace of V); a linear subspace of V contained in U is a linear subspace of U, linear independence is the same computed in a linear subspace or in V, and spans agree (Basis of a vector space: a linearly independent spanning subset; and ordered basis: an injective finite list whose image is a basis, section on bases of a linear subspace, Linear subspace of a vector space).

[L5]

In a finite-dimensional vector space X over F, every linearly independent A0⊆X is contained in a basis of X, and no choice principle is used to produce it (If dim⁡FV=n and U is a linear subspace of V, then U is finite-dimensional, dim⁡FU≤n, and dim⁡FU=n if and only if U=V, claim 3, which states this for a linear subspace and notes that a space is a linear subspace of itself). Also span⁡(X)=X for a linear subspace X (The span is monotone and idempotent, span⁡(S)=S exactly when S is a linear subspace, and span⁡(S∪{0V})=span⁡(S), claim 4).

[L6]

Concatenation: for y:p→Z and z:q→Z there is exactly one c:p+q→Z with ci=yi for i<p and cp+j=zj for j<q; for Z=V it satisfies ∑i<p+qci=∑i<pyi+∑j<qzj; and if y,z are injective with disjoint images then c is injective with image y[p]∪z[q]. A list is linearly independent exactly when it is injective with linearly independent image, and every subset of a linearly independent set is linearly independent (Finite sums re-indexed along an injection, with a zero term deleted, and concatenated; and the closure properties of linear independence: an independent list is injective and never 0V, its sublists are independent, a list is independent exactly when it is injective with linearly independent image, and every subset of a linearly independent set is linearly independent, claims 3, 6 and 7). The scalar case is the same statement read in F, a vector space over itself (A field is a vector space over itself, and over any subfield K⊆F every F-vector space is a K-vector space by restricting the scalars).

Proof

technique · constructive
1.1

U∩W is a linear subspace of V contained in U, hence a linear subspace of U; since U is finite-dimensional, so is U∩W. Write a:=dim⁡F(U∩W), fix a basis A of U∩W with A≈a, and fix an injective list α:a→V with image A. Note span⁡(A)=U∩W, and that independence and spans may be computed in V throughout.

L1L2L3construct
2.1

Extending A in each of U and W. The set A is linearly independent with A⊆U, and U is finite-dimensional, so A is contained in a basis BU of U; likewise A⊆W gives a basis BW of W with A⊆BW. Both extensions are the finite-dimensional ones, with no appeal to Zorn's lemma. Put AU:=BU∖A and AW:=BW∖A, which are disjoint from A by construction. Each is a subset of a linearly independent set, hence linearly independent, and each lies in a space with a finite basis, hence is finite; fix q and r with AU≈q and AW≈r, and injective lists β:q→V with image AU and δ:r→V with image AW.

step 1.1L1L4L5L6L11construct
3.1

The sizes add up. The lists α and β are injective with disjoint images, so their concatenation is an injective list a+q→V with image A∪AU=BU; hence BU≈a+q. Also BU is a basis of U, so BU≈u, and a finite set is equinumerous with exactly one natural number, so a+q=u. The same argument with δ gives a+r=w.

step 2.1L1L6L11
3.2

AU and AW are disjoint. Suppose y∈AU∩AW. Then y∈BU⊆U and y∈BW⊆W, so y∈U∩W=span⁡(A). But y∈AW means y∉A, so A⊆BW∖{y} and monotonicity gives y∈span⁡(A)⊆span⁡(BW∖{y}), which makes BW linearly dependent and contradicts its being a basis.

step 2.1L8L9
4.1

One list carrying all three blocks. Let c′ be the concatenation of α and β, an injective list a+q→V with image BU, and let c be the concatenation of c′ and δ, a list (a+q)+r→V. By step 3.2 the images BU and AW are disjoint, since BU∩AW would lie in A∩AW or in AU∩AW, both empty; so c is injective with image C:=BU∪AW=A∪AU∪AW=BU∪BW. For scalars γ:(a+q)+r→F the sum splits as ∑i<(a+q)+rγici=(∑i<a+qγici′)+(∑k<rγ(a+q)+kδk).

step 2.1step 3.2L6L10
5.1

The list c is linearly independent. Let γ:(a+q)+r→F with ∑i<(a+q)+rγici=0V, and write P:=∑i<a+qγici′ and R:=∑k<rγ(a+q)+kδk, so P+R=0V by step 4.1 and hence R=−P. Now P is a linear combination of the list c′, whose values lie in BU, so P∈span⁡(BU)=U and therefore R=−P∈U; and R is a linear combination of δ, whose values lie in AW⊆BW, so R∈span⁡(BW)=W. Hence R∈U∩W=span⁡(A)=span⁡(α[a]), so R=∑i<aεiαi for some ε:a→F. Let d be the concatenation of α and δ, injective with image A∪AW=BW since A and AW are disjoint, and let η be the concatenation of ε with k↦−γ(a+q)+k; then ∑i<a+rηidi=R+(−R)=0V. As d is an injective list into the linearly independent set BW, it is a linearly independent list, so every ηi=0F; in particular γ(a+q)+k=0F for every k<r, and εi=0F for every i<a, whence R=0V by (F1) and P=−R=0V. Finally c′ is an injective list into the linearly independent set BU, hence linearly independent, so P=0V forces γi=0F for every i<a+q. Every coefficient of γ therefore vanishes.

step 2.1step 4.1L6L7L9L10
5.2

span⁡(C)=U+W. From BU⊆C and BW⊆C and monotonicity, U=span⁡(BU)⊆span⁡(C) and W=span⁡(BW)⊆span⁡(C), so U∪W⊆span⁡(C) and hence U+W=span⁡(U∪W)⊆span⁡(C). Conversely C=BU∪BW⊆U∪W⊆U+W, and U+W is a linear subspace, so span⁡(C)⊆U+W.

step 2.1step 4.1L9
6.1

C is a basis of U+W with (a+q)+r elements. By step 5.1 the list c is linearly independent, hence injective with linearly independent image C and C≈(a+q)+r; by step 5.2 it spans U+W. So U+W is finite-dimensional with dim⁡F(U+W)=(a+q)+r.

step 4.1step 5.1step 5.2L1L6L11
7.1

The formula. By step 3.1, a+q=u and a+r=w, so step 6.1 gives dim⁡F(U+W)=u+r, and with dim⁡F(U∩W)=a from step 1.1 we get dim⁡F(U+W)+dim⁡F(U∩W)=(u+r)+a=u+(r+a)=u+(a+r)=u+w=dim⁡FU+dim⁡FW, using associativity and commutativity of addition on N.

step 1.1step 3.1step 6.1L11discharge-construct∎

Remarks

Depends on

Used by

Dependency tree · two levels

67 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.

Sources