Alphabeta Math
LemmaStatement: AI-adaptedProof: AI-generatedSession-authored (Fable 5 assisted)precheck 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 span is monotone and idempotent, span(S)=S\operatorname{span}(S) = S exactly when SS is a linear subspace, and span(S{0V})=span(S)\operatorname{span}(S \cup \{0_V\}) = \operatorname{span}(S)

Statement

Let VV be a vector space over a field FF (Vector space over a field) and let S,TVS, T \subseteq V. Then:

  1. Extensive. Sspan(S)S \subseteq \operatorname{span}(S).
  2. Monotone. If STS \subseteq T then span(S)span(T)\operatorname{span}(S) \subseteq \operatorname{span}(T).
  3. Idempotent. span(span(S))=span(S)\operatorname{span}(\operatorname{span}(S)) = \operatorname{span}(S).
  4. span(S)=S\operatorname{span}(S) = S if and only if SS is a linear subspace of VV (Linear subspace of a vector space).
  5. span(S{0V})=span(S)\operatorname{span}(S \cup \{0_V\}) = \operatorname{span}(S).

Facts & Assumptions

Given: A field FF, a vector space VV over FF, and subsets S,TVS, T \subseteq V.

[L1]

span(S)\operatorname{span}(S) is a linear subspace of VV, it contains SS, and it is contained in every linear subspace of VV that contains SS; the same holds with TT or any other subset in place of SS (Linear combination of a finite list, and the span span(S)\operatorname{span}(S) as the smallest linear subspace containing SS).

[L2]

Every linear subspace of VV contains 0V0_V, by condition (W1) (Linear subspace of a vector space).

Proof

technique · direct
1.1

Claim 1 is part of the defining description of the span: it contains SS.

L1
1.2

Claim 2. Suppose STS \subseteq T. Then span(T)\operatorname{span}(T) is a linear subspace of VV containing TT, hence containing SS; since span(S)\operatorname{span}(S) is contained in every linear subspace containing SS, we get span(S)span(T)\operatorname{span}(S) \subseteq \operatorname{span}(T).

L1
1.3

If SS is a linear subspace of VV, then SS is itself a linear subspace containing SS, so span(S)S\operatorname{span}(S) \subseteq S; together with Sspan(S)S \subseteq \operatorname{span}(S) this gives span(S)=S\operatorname{span}(S) = S.

L1
1.4

Conversely, if span(S)=S\operatorname{span}(S) = S then SS is a linear subspace of VV, because span(S)\operatorname{span}(S) is one.

L1
1.5

0Vspan(S)0_V \in \operatorname{span}(S), since span(S)\operatorname{span}(S) is a linear subspace of VV.

L1L2
2.1

Steps 1.3 and 1.4 together are claim 4.

step 1.3step 1.4
2.2

Claim 5. From SS{0V}S \subseteq S \cup \{0_V\} and step 1.2 we get span(S)span(S{0V})\operatorname{span}(S) \subseteq \operatorname{span}(S \cup \{0_V\}). Conversely Sspan(S)S \subseteq \operatorname{span}(S) by step 1.1 and 0Vspan(S)0_V \in \operatorname{span}(S) by step 1.5, so S{0V}span(S)S \cup \{0_V\} \subseteq \operatorname{span}(S), and since span(S)\operatorname{span}(S) is a linear subspace containing S{0V}S \cup \{0_V\}, minimality gives span(S{0V})span(S)\operatorname{span}(S \cup \{0_V\}) \subseteq \operatorname{span}(S).

step 1.1step 1.2step 1.5L1
3.1

Claim 3. The set span(S)\operatorname{span}(S) is a linear subspace of VV, so applying claim 4 to it gives span(span(S))=span(S)\operatorname{span}(\operatorname{span}(S)) = \operatorname{span}(S).

step 2.1L1
4.1

Claims 1, 2, 3, 4 and 5 are steps 1.1, 1.2, 3.1, 2.1 and 2.2 respectively.

step 1.1step 1.2step 2.1step 2.2step 3.1

Remarks

  • These three properties are exactly what makes the span a closure operator on the subsets of VV: extensive, monotone and idempotent. The closed sets of that operator are the linear subspaces, which is the content of claim 4. The subgroup generated by a subset (The subgroup S\langle S \rangle generated by a subset, the cyclic subgroup g\langle g \rangle, and cyclic groups) is the closure operator of the same shape on the subsets of a group.

  • Claim 5 says 0V0_V is invisible to the span. Adding or deleting the zero vector changes nothing, since every linear subspace contains it. It does not follow, and is not claimed here, that deleting any other single vector changes nothing: that question is about linear independence and belongs to a later page.

  • Claim 2 is used constantly in the form "a bigger set spans more". It is what lets a spanning set be enlarged freely, and, with claim 3, what lets the span be computed in stages: spanning a set, then spanning the result, gains nothing.

Depends on

Used by

Dependency tree · next 3 levels

Direct dependencies and their dependencies through the next three levels: 37 results over 16 levels. An arrow runs from a result to what uses it, and this result sits at the bottom with a heavier outline. Click the chart to enlarge it.

Sources