Alphabeta Math
LemmaStatement: AI-adaptedProof: AI-adaptedSession-authored (Fable 5 assisted)precheck passjudge pass (z-ai/glm-5.2)audited 2026-07-28
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  • AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
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A subset SVS \subseteq V is linearly dependent if and only if some sSs \in S lies in span(S{s})\operatorname{span}(S \setminus \{s\}); and span(S)\operatorname{span}(S) is already the set of linear combinations of INJECTIVE finite lists into SS

Statement

Let VV be a vector space over a field FF (Vector space over a field) and let SVS \subseteq V.

  1. SS is linearly dependent (Linear independence: a finite list v:nVv : n \to V is independent when i<nλivi=0V\sum_{i<n} \lambda_i v_i = 0_V forces every λi=0F\lambda_i = 0_F, and a subset SVS \subseteq V is independent when every injective finite list into SS is independent) if and only if there is sSs \in S with sspan(S{s})s \in \operatorname{span}(S \setminus \{s\}) (Linear combination of a finite list, and the span span(S)\operatorname{span}(S) as the smallest linear subspace containing SS).
  2. span(S)  =  {i<mνixi  :  mN, ν:mF, x:mS injective}.\operatorname{span}(S) \;=\; \Bigl\{\, \sum_{i<m} \nu_i x_i \;:\; m \in \mathbb{N},\ \nu : m \to F,\ x : m \to S \text{ injective} \,\Bigr\} . That is, restricting the lists in span(S)\operatorname{span}(S) is exactly the set of linear combinations of finite lists of elements of SS, and span()={0V}\operatorname{span}(\varnothing) = \{0_V\} to injective lists changes nothing.

The two boundary cases are instances, not exceptions. For S=S = \varnothing both sides of claim 1 fail: \varnothing is independent and there is no ss. For S={0V}S = \{0_V\} both hold: {0V}\{0_V\} is dependent, and 0Vspan()={0V}0_V \in \operatorname{span}(\varnothing) = \{0_V\} (span(S)\operatorname{span}(S) is exactly the set of linear combinations of finite lists of elements of SS, and span()={0V}\operatorname{span}(\varnothing) = \{0_V\}).

Facts & Assumptions

Given: A field FF, a vector space VV over FF, and a subset SVS \subseteq V.

[L1]

span(T)\operatorname{span}(T) is exactly the set of vectors i<pμiwi\sum_{i<p}\mu_i w_i with pNp \in \mathbb{N}, μ:pF\mu : p \to F and w:pTw : p \to T; it is a linear subspace of VV containing TT; and span()={0V}\operatorname{span}(\varnothing) = \{0_V\} (span(S)\operatorname{span}(S) is exactly the set of linear combinations of finite lists of elements of SS, and span()={0V}\operatorname{span}(\varnothing) = \{0_V\}, Linear combination of a finite list, and the span span(S)\operatorname{span}(S) as the smallest linear subspace containing SS).

[L2]

Finite sums: i<0ui=0V\sum_{i<0} u_i = 0_V and i<σ(p)ui=(i<pui)+up\sum_{i<\sigma(p)} u_i = \bigl(\sum_{i<p} u_i\bigr) + u_p, the value depending only on u0,,up1u_0, \dots, u_{p-1} (The product g0g1gn1g_0 g_1 \cdots g_{n-1} of a finite list in a monoid, by recursion, with the empty product (n=0n = 0) equal to the identity, Linear combination of a finite list, and the span span(S)\operatorname{span}(S) as the smallest linear subspace containing SS).

[L3]

(F1) an all-0V0_V list sums to 0V0_V; (F2) λi<pui+i<pwi=i<p(λui+wi)\lambda\sum_{i<p} u_i + \sum_{i<p} w_i = \sum_{i<p}(\lambda u_i + w_i); (F3) i<pui=uj+i<pui(j)\sum_{i<p} u_i = u_j + \sum_{i<p} u^{(j)}_i for j<pj < p, where u(j)u^{(j)} agrees with uu off jj and is 0V0_V at jj (The sum U+WU + W of two linear subspaces and the sum i<nUi\sum_{i<n} U_i of a finite family).

[L4]

Deleting one index: for k<σ(p)k < \sigma(p) the map δk:pσ(p)\delta_k : p \to \sigma(p) is injective with image σ(p){k}\sigma(p) \setminus \{k\}, and a list u:σ(p)Vu : \sigma(p) \to V with uk=0Vu_k = 0_V satisfies j<σ(p)uj=i<puδk(i)\sum_{j<\sigma(p)} u_j = \sum_{i<p} u_{\delta_k(i)} (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 0V0_V, 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, claim 2).

[L5]

The vector space axioms (Vector space over a field) and their elementary consequences (In any vector space 0Fv=0V0_F v = 0_V, λ0V=0V\lambda 0_V = 0_V, (λ)v=(λv)(-\lambda)v = -(\lambda v), (1F)v=v(-1_F)v = -v, and λv=0V\lambda v = 0_V forces λ=0F\lambda = 0_F or v=0Vv = 0_V): (V,+,0V)(V,+,0_V) is an abelian group; 0Fw=0V0_F w = 0_V; λ0V=0V\lambda 0_V = 0_V; (1F)w=w(-1_F)w = -w; 1Fw=w1_F w = w; and (V4) (λμ)w=λ(μw)(\lambda\mu)w = \lambda(\mu w), (V3) (λ+μ)w=λw+μw(\lambda+\mu)w = \lambda w + \mu w.

[L6]

FF is a field: 0F1F0_F \ne 1_F, every λ0F\lambda \ne 0_F has an inverse λ1\lambda^{-1} with λ1λ=1F\lambda^{-1}\lambda = 1_F, and every μ\mu has an additive inverse μ-\mu (Field).

[L7]

A list v:pVv : p \to V is independent when i<pλivi=0V\sum_{i<p}\lambda_i v_i = 0_V forces every λi=0F\lambda_i = 0_F, and SS is dependent exactly when some injective finite list into SS is dependent (Linear independence: a finite list v:nVv : n \to V is independent when i<nλivi=0V\sum_{i<n} \lambda_i v_i = 0_V forces every λi=0F\lambda_i = 0_F, and a subset SVS \subseteq V is independent when every injective finite list into SS is independent).

[L8]

Naturals and maps: every p0p \ne 0 is a successor (Every nonzero natural number is a successor); σ(p)=p{p}\sigma(p) = p \cup \{p\} with ppp \notin p (The natural numbers N\mathbb{N} (von Neumann), On N\mathbb{N} the order is membership: m<n    mnm < n \iff m \in n); induction (The principle of mathematical induction); and injectivity as in Injection, surjection, bijection.

Proof

technique · direct
1.1

Collecting repeated entries. For every pNp \in \mathbb{N}, every w:pVw : p \to V and every μ:pF\mu : p \to F there are mNm \in \mathbb{N}, an injective x:mVx : m \to V with x[m]w[p]x[m] \subseteq w[p], and ν:mF\nu : m \to F, with i<pμiwi=i<mνixi\sum_{i<p}\mu_i w_i = \sum_{i<m}\nu_i x_i. By induction on pp: at p=0p = 0 take m=0m = 0, both sums being 0V0_V. Assume it at pp, and let w:σ(p)Vw : \sigma(p) \to V and μ:σ(p)F\mu : \sigma(p) \to F; applying the hypothesis to the restrictions gives i<pμiwi=i<mνixi\sum_{i<p}\mu_i w_i = \sum_{i<m}\nu_i x_i with xx injective and x[m]w[p]x[m] \subseteq w[p], and the recursion gives i<σ(p)μiwi=i<mνixi+μpwp\sum_{i<\sigma(p)}\mu_i w_i = \sum_{i<m}\nu_i x_i + \mu_p w_p. If wpx[m]w_p \notin x[m], extend xx to x:σ(m)Vx' : \sigma(m) \to V by xm:=wpx'_m := w_p and ν\nu to ν\nu' by νm:=μp\nu'_m := \mu_p; then xx' is injective with x[σ(m)]w[σ(p)]x'[\sigma(m)] \subseteq w[\sigma(p)] and the recursion gives i<σ(m)νixi=i<mνixi+μpwp\sum_{i<\sigma(m)}\nu'_i x'_i = \sum_{i<m}\nu_i x_i + \mu_p w_p. If instead wp=xkw_p = x_k for the unique such k<mk < m, put νk:=νk+μp\nu'_k := \nu_k + \mu_p and νi:=νi\nu'_i := \nu_i for iki \ne k; applying (F3) at kk to the lists iνixii \mapsto \nu_i x_i and iνixii \mapsto \nu'_i x_i, whose kk-deleted forms coincide, and using (V3) in the form (νk+μp)xk=νkxk+μpxk(\nu_k + \mu_p)x_k = \nu_k x_k + \mu_p x_k, gives i<mνixi=i<mνixi+μpxk\sum_{i<m}\nu'_i x_i = \sum_{i<m}\nu_i x_i + \mu_p x_k, which is the required value.

L2L3L5L8
1.2

A scalar passes through a finite sum: for λF\lambda \in F, pNp \in \mathbb{N} and u:pVu : p \to V, applying (F2) with the all-0V0_V second list and using (F1) and the identity law gives λi<pui=i<pλui\lambda\sum_{i<p} u_i = \sum_{i<p}\lambda u_i; combined with (V4) this yields λi<pλivi=i<p(λλi)vi\lambda \sum_{i<p}\lambda_i v_i = \sum_{i<p}(\lambda\lambda_i)v_i for scalars λi\lambda_i and vectors viv_i.

L3L5
2.1

Claim 2. Every i<mνixi\sum_{i<m}\nu_i x_i with x:mSx : m \to S is a linear combination of elements of SS, hence lies in span(S)\operatorname{span}(S), so the right-hand set is contained in span(S)\operatorname{span}(S). Conversely an element of span(S)\operatorname{span}(S) is i<pμiwi\sum_{i<p}\mu_i w_i for some w:pSw : p \to S, and step 1.1 rewrites it as i<mνixi\sum_{i<m}\nu_i x_i with xx injective and x[m]w[p]Sx[m] \subseteq w[p] \subseteq S, so x:mSx : m \to S is an injective finite list.

step 1.1L1
2.2

Claim 1, from left to right. Let SS be dependent, witnessed by an injective v:nSv : n \to S and λ:nF\lambda : n \to F with i<nλivi=0V\sum_{i<n}\lambda_i v_i = 0_V and λj0F\lambda_j \ne 0_F for some j<nj < n. Put ui:=λiviu_i := \lambda_i v_i, so (F3) at jj gives 0V=uj+R0_V = u_j + R with R:=i<nui(j)R := \sum_{i<n} u^{(j)}_i, whence uj=Ru_j = -R and vj=1Fvj=(λj1λj)vj=λj1(λjvj)=λj1(R)=(λj1)Rv_j = 1_F v_j = (\lambda_j^{-1}\lambda_j)v_j = \lambda_j^{-1}(\lambda_j v_j) = \lambda_j^{-1}(-R) = (-\lambda_j^{-1})R. Now ui(j)=λiviu^{(j)}_i = \lambda'_i v_i where λj:=0F\lambda'_j := 0_F and λi:=λi\lambda'_i := \lambda_i for iji \ne j, since 0Fvj=0V0_F v_j = 0_V; also n0n \ne 0, say n=σ(n)n = \sigma(n'), and the entry of this list at jj is 0V0_V, so deleting the index jj gives R=i<nλδj(i)vδj(i)R = \sum_{i<n'}\lambda'_{\delta_j(i)} v_{\delta_j(i)}. Applying step 1.2 to the scalar λj1-\lambda_j^{-1} gives vj=i<nκiyiv_j = \sum_{i<n'}\kappa_i y_i with κi:=(λj1)λδj(i)\kappa_i := (-\lambda_j^{-1})\lambda'_{\delta_j(i)} and y:=vδjy := v \circ \delta_j. Since δj\delta_j has image n{j}n \setminus \{j\} and vv is injective, yy takes its values in S{vj}S \setminus \{v_j\}, so vjv_j is a linear combination of elements of S{vj}S \setminus \{v_j\} and therefore lies in span(S{vj})\operatorname{span}(S \setminus \{v_j\}). Taking s:=vjSs := v_j \in S finishes this direction.

step 1.2L1L3L4L5L6L7
3.1

Claim 1, from right to left. Let sSs \in S with sspan(S{s})s \in \operatorname{span}(S \setminus \{s\}). By step 2.1 applied to S{s}S \setminus \{s\} there are mm, an injective x:mS{s}x : m \to S \setminus \{s\} and ν:mF\nu : m \to F with s=i<mνixis = \sum_{i<m}\nu_i x_i. Extend xx to v:σ(m)Sv : \sigma(m) \to S by vm:=sv_m := s, which is injective because sx[m]s \notin x[m], and extend ν\nu to λ:σ(m)F\lambda : \sigma(m) \to F by λm:=1F\lambda_m := -1_F. The recursion then gives i<σ(m)λivi=i<mνixi+(1F)s=s+(s)=0V\sum_{i<\sigma(m)}\lambda_i v_i = \sum_{i<m}\nu_i x_i + (-1_F)s = s + (-s) = 0_V, while λm=1F0F\lambda_m = -1_F \ne 0_F, since 1F=0F-1_F = 0_F would give 1F=0F1_F = 0_F. So vv is an injective finite list into SS that is dependent, and SS is dependent.

step 2.1L2L5L6L7
4.1

Claim 1 is steps 2.2 and 3.1 together, and claim 2 is step 2.1.

step 2.1step 2.2step 3.1

Remarks

Depends on

Used by

Dependency tree · next 3 levels

Direct dependencies and their dependencies through the next three levels: 65 results over 23 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.

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