Alphabeta Math
ExampleConstruction: AI-adaptedVerification: AI-generatedSession-authored (Fable 5 assisted)precheck passjudge pass (z-ai/glm-5.2)audited 2026-07-29
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.

Steinitz's confinement bound realised on an explicit list of six unit vectors in R2\mathbb{R}^{2} summing to zero

Example

Take n=2n = 2 and m=6m = 6, and let a:=1/ι(2)a := 1/\sqrt{\iota(2)}, so that u:=(a,a)R2u := (a,a) \in \mathbb{R}^{2} has u2=a2+a2=1\lVert u\rVert_2 = \sqrt{a^{2}+a^{2}} = 1. Define v:6R2v : 6 \to \mathbb{R}^{2} by

v0:=e0,v1:=e1,v2:=u,v3:=e0,v4:=e1,v5:=u,v_0 := e_0, \quad v_1 := -e_1, \quad v_2 := u, \quad v_3 := -e_0, \quad v_4 := e_1, \quad v_5 := -u ,

with e0=(1,0)e_0 = (1,0) and e1=(0,1)e_1 = (0,1) (The standard list e:nFne : n \to F^{n} with ei(i)=1Fe_i(i) = 1_F and ei(j)=0Fe_i(j) = 0_F for jij \ne i is an ordered basis of FnF^{n}; hence dimFFn=n\dim_F F^{n} = n, and F0F^{0} is the zero space with basis \varnothing and dimension 00). Every vi2\lVert v_i\rVert_2 is 11 and i<6vi=0\sum_{i<6}v_i = 0, so Steinitz's polygonal confinement theorem: finitely many vectors of norm at most 11 summing to 00 can be ordered so that every partial sum has norm at most nn applies and asserts an ordering all of whose partial sums have norm at most ι(2)\iota(2).

A good ordering. The identity ordering works: the partial sums sk=j<kvjs_k = \sum_{j<k}v_j are

s0=(0,0),s1=(1,0),s2=(1,1),s3=(1+a, a1),s4=(a, a1),s5=(a,a),s6=(0,0),s_0 = (0,0), \quad s_1 = (1,0), \quad s_2 = (1,-1), \quad s_3 = (1+a,\ a-1), \quad s_4 = (a,\ a-1), \quad s_5 = (a,a), \quad s_6 = (0,0),

with norms 00, 11, ι(2)\sqrt{\iota(2)}, ι(3)\sqrt{\iota(3)}, ι(2)ι(2)\sqrt{\iota(2)-\sqrt{\iota(2)}}, 11, 00, each at most ι(2)\iota(2).

A bad ordering, which exceeds the bound. Reordering as e0,e1,u,e0,e1,ue_0, e_1, u, -e_0, -e_1, -u gives the third partial sum (1+a, 1+a)(1+a,\ 1+a), whose norm squared is ι(3)+ι(2)ι(2)>ι(4)\iota(3)+\iota(2)\sqrt{\iota(2)} > \iota(4). So that ordering has a partial sum of norm strictly greater than ι(2)\iota(2), and the theorem is saying something.

One step of the descending construction. With b6b^{6} the identity of 66 and μj6:=ι(4)/ι(6)\mu^{6}_j := \iota(4)/\iota(6) for j<6j<6, the pair (b6,μ6)(b^{6},\mu^{6}) is admissible at k=6k = 6 in the sense of the proof of Steinitz's polygonal confinement theorem: finitely many vectors of norm at most 11 summing to 00 can be ordered so that every partial sum has norm at most nn. At the next stage the feasible set is

Λ  =  {μ[0,1]6  :  j<6μjvj=0, j<6μj=ι(3)},\Lambda \;=\; \Bigl\{\, \mu \in [0,1]^{6} \;:\; \sum_{j<6}\mu_j v_j = 0,\ \sum_{j<6}\mu_j = \iota(3) \,\Bigr\},

and μ:=(1, 1ι(2), 0, 1, 1ι(2), 0)\mu := \bigl(1,\ \tfrac{1}{\iota(2)},\ 0,\ 1,\ \tfrac{1}{\iota(2)},\ 0\bigr) lies in it with exactly two coordinates strictly between 00 and 11, which is the least possible. Its support is {0,1,3,4}\{0,1,3,4\}, of size 4k1=54 \le k-1 = 5, so the support bound holds with room; dropping the coordinate j0=5j_0 = 5 gives the admissible pair at k=5k = 5 with b5=(0,1,2,3,4)b^{5} = (0,1,2,3,4) and μ5=(1, 1ι(2), 0, 1, 1ι(2))\mu^{5} = \bigl(1,\ \tfrac{1}{\iota(2)},\ 0,\ 1,\ \tfrac{1}{\iota(2)}\bigr).

Facts & Assumptions

Given: The list v:6R2v : 6 \to \mathbb{R}^{2} above, with a=1/ι(2)a = 1/\sqrt{\iota(2)} and u=(a,a)u = (a,a); the partial sums sk=j<kvjs_k = \sum_{j<k}v_j of the identity ordering; the vector μ=(1,1/ι(2),0,1,1/ι(2),0)\mu = \bigl(1, 1/\iota(2), 0, 1, 1/\iota(2), 0\bigr).

[L2]

Square roots: c\sqrt{c} is the unique nonnegative ss with s2=cs^{2} = c; (ι(2))2=ι(2)\bigl(\sqrt{\iota(2)}\bigr)^{2} = \iota(2); and for c,d0c,d \ge 0, cdc \le d exactly when cd\sqrt{c} \le \sqrt{d} (Square roots exist: a unique a0\sqrt{a} \ge 0 with (a)2=a(\sqrt{a})^2 = a; the positives are {x2:x0}\{x^2 : x \neq 0\}, Squaring is monotone on the nonnegatives, Integer powers ama^m).

[L3]

Canonical naturals are positive and strictly increasing and carry sums to sums and products to products (The canonical natural ι(n)=n1F\iota(n) = n \cdot 1_F of a field, Canonical naturals are positive and strictly increasing); inverses of positives are positive (Inverses of positives are positive, and reciprocation reverses order).

Verification

technique · direct
1.1

a2=1/ι(2)a^{2} = 1/\iota(2) by [L2], so u22=a2+a2=1\lVert u\rVert_2^{2} = a^{2}+a^{2} = 1 and u2=1\lVert u\rVert_2 = 1; also e02=e12=1\lVert e_0\rVert_2 = \lVert e_1\rVert_2 = 1 and y2=y2\lVert -y\rVert_2 = \lVert y\rVert_2. Hence vi2=1\lVert v_i\rVert_2 = 1 for every i<6i<6.

L1L2L3
1.2

i<6vi=(e0e0)+(e1+e1)+(uu)=0\sum_{i<6}v_i = (e_0 - e_0) + (-e_1 + e_1) + (u - u) = 0, computing coordinatewise.

L4
1.3

For the ordering e0,e1,u,e0,e1,ue_0, e_1, u, -e_0, -e_1, -u the third partial sum is (1+a,1+a)(1+a, 1+a), whose norm squared is ι(2)(1+a)2=ι(2)+ι(2)ι(2)a+ι(2)a2=ι(3)+ι(2)ι(2)\iota(2)(1+a)^{2} = \iota(2) + \iota(2)\iota(2)a + \iota(2)a^{2} = \iota(3) + \iota(2)\sqrt{\iota(2)}, using ι(2)a=ι(2)/ι(2)=ι(2)\iota(2)a = \iota(2)/\sqrt{\iota(2)} = \sqrt{\iota(2)}.

L1L2L3
1.4

The vector μ=(1,1/ι(2),0,1,1/ι(2),0)\mu = \bigl(1, 1/\iota(2), 0, 1, 1/\iota(2), 0\bigr) lies in Λ\Lambda: its values lie in [0,1][0,1]; j<6μj=1+1/ι(2)+0+1+1/ι(2)+0=ι(3)\sum_{j<6}\mu_j = 1 + 1/\iota(2) + 0 + 1 + 1/\iota(2) + 0 = \iota(3); and j<6μjvj=(v0+v3)+(1/ι(2))(v1+v4)=0+0=0\sum_{j<6}\mu_j v_j = (v_0 + v_3) + \bigl(1/\iota(2)\bigr)(v_1+v_4) = 0 + 0 = 0.

L3L4
2.1

The partial sums of the identity ordering are as displayed, by the recursion of [L4] applied coordinatewise.

step 1.2L4
2.2

Since ι(2)>1\sqrt{\iota(2)} > 1 and ι(2)>0\iota(2) > 0, the quantity of step 1.3 exceeds ι(3)+ι(2)=ι(5)>ι(4)\iota(3)+\iota(2) = \iota(5) > \iota(4), so that partial sum has norm strictly greater than ι(2)\iota(2): a bad ordering really does break the bound.

step 1.3L2L3
2.3

The pair (b6,μ6)(b^{6},\mu^{6}) with b6b^{6} the identity of 66 and μj6=ι(4)/ι(6)\mu^{6}_j = \iota(4)/\iota(6) is admissible at 66: the values lie in [0,1][0,1], j<6μj6vj=(ι(4)/ι(6))j<6vj=0\sum_{j<6}\mu^{6}_j v_j = \bigl(\iota(4)/\iota(6)\bigr)\sum_{j<6}v_j = 0, and j<6μj6=ι(6)ι(4)/ι(6)=ι(4)\sum_{j<6}\mu^{6}_j = \iota(6)\cdot\iota(4)/\iota(6) = \iota(4).

step 1.2L3L4L5
2.4

No element of Λ\Lambda has fewer than two strictly fractional coordinates. If none were fractional, μ\mu would be a {0,1}\{0,1\}-vector with jμj=ι(3)\sum_j\mu_j = \iota(3), hence with support of size 33, and jsuppvj=0\sum_{j \in \operatorname{supp}}v_j = 0; the support cannot contain a pair {0,3}\{0,3\}, {1,4}\{1,4\} or {2,5}\{2,5\}, since the remaining single vector would then have to be 00 while all six are nonzero, so it contains exactly one index from each pair and the sum is ±e0±e1±u\pm e_0 \pm e_1 \pm u, whose second coordinate is ±1±a\pm 1 \pm a and whose first is ±1±a\pm 1 \pm a, and ±1±a0|{\pm}1 \pm a| \ne 0 because a1a \ne 1 (indeed a2=1/ι(2)1a^{2} = 1/\iota(2) \ne 1). If exactly one coordinate were fractional, say with value tt, then jμj\sum_j \mu_j would be tt plus a canonical natural and could not equal ι(3)\iota(3).

step 1.4L1L2L3
3.1

Their norms squared are 00, 11, ι(2)\iota(2), (1+a)2+(a1)2=ι(2)+ι(2)a2=ι(3)(1+a)^{2}+(a-1)^{2} = \iota(2)+\iota(2)a^{2} = \iota(3), a2+(a1)2=ι(2)ι(2)aa^{2}+(a-1)^{2} = \iota(2) - \iota(2)a, ι(2)a2=1\iota(2)a^{2} = 1 and 00.

step 2.1L1L2L3
3.2

So μ\mu of step 1.4 is a minimiser, its support is {0,1,3,4}\{0,1,3,4\} of size 44, and 45=k14 \le 5 = k-1 at k=6k = 6: the support bound of [L5] holds, and a coordinate with value 00 exists, for instance j0=5j_0 = 5.

step 1.4step 2.4L5
4.1

Each of these is at most ι(4)\iota(4): the largest is ι(3)\iota(3), and ι(2)ι(2)aι(2)\iota(2)-\iota(2)a \le \iota(2) because a>0a > 0. So every partial sum of the identity ordering has norm at most ι(4)=ι(2)\sqrt{\iota(4)} = \iota(2), and the identity ordering realises the bound of [L5].

step 3.1L2L3L5
4.2

Deleting position 55 gives b5=(0,1,2,3,4)b^{5} = (0,1,2,3,4) and μ5=(1,1/ι(2),0,1,1/ι(2))\mu^{5} = \bigl(1, 1/\iota(2), 0, 1, 1/\iota(2)\bigr), with j<5μj5=ι(3)\sum_{j<5}\mu^{5}_j = \iota(3) and j<5μj5vb5(j)=0\sum_{j<5}\mu^{5}_j v_{b^{5}(j)} = 0: an admissible pair at k=5k = 5.

step 1.4step 3.2L4L5
5.1

Steps 4.1, 2.2 and 4.2 give, in turn, an ordering realising the bound, an ordering violating it, and one traced step of the descending construction with its support bound checked.

step 4.1step 2.2step 4.2

Remarks

  • The bound ι(n)\iota(n) is not attained here. The largest partial-sum norm of the good ordering is ι(3)\sqrt{\iota(3)}, comfortably below ι(2)\iota(2). The theorem asserts existence of an ordering below ι(n)\iota(n) and claims no sharpness, and this example makes no claim about the optimal constant either.

  • What the bad ordering shows. Without the theorem there is no reason to expect any ordering to stay bounded independently of mm: the third partial sum of the bad ordering already exceeds ι(2)\iota(2), and lists of many unit vectors summing to 00 can be ordered so that a partial sum has norm of order mm.

  • Why one step of the construction is traced. An example that only asserted the bound would say nothing about how it is obtained. The step above exhibits the object the proof actually manipulates — a feasible vector of coefficients with as few fractional coordinates as possible — and checks the support bound #suppk1\#\operatorname{supp} \le k-1 that the descending construction turns on.

Depends on

Used by

Nothing in the library uses this result yet.

Dependency tree · next 3 levels

Direct dependencies and their dependencies through the next three levels: 189 results over 37 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