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TheoremStatement: AI-adaptedProof: AI-generatedprecheck passjudge pass (z-ai/glm-5.2)audited 2026-07-29
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Steinitz's polygonal confinement theorem: finitely many vectors of norm at most 1 summing to 0 can be ordered so that every partial sum has norm at most n

Statement

Let n∈N with n≥1, let m∈N and let v:m→Rn be a finite list of vectors with

∥vi∥2≤1  for every i<m,∑i<mvi=0.

Then there is a bijection π:m→m (Injection, surjection, bijection) such that

∥∑j<kvπ(j)∥2  ≤  ι(n)for every k≤m,

where ι is the canonical natural of R (The canonical natural ι(n)=n⋅1F of a field) and the sums are the finite sums of the vector space Rn (Linear combination of a finite list, and the span span⁡(S) as the smallest linear subspace containing S).

The bound depends only on the dimension, not on m. That is the whole content: the triangle inequality alone gives only ι(k), which grows with the number of vectors used.

Which Steinitz result this is. This is Steinitz's polygonal confinement lemma, the rearrangement lemma of his 1913 paper on conditionally convergent series. It is not the Steinitz exchange lemma of linear algebra, which is published in this library as thm-steinitz-exchange and carries the alias lem-steinitz. The two are unrelated results by the same author, and no item on this page uses the bare alias.

Facts & Assumptions

Given: Naturals n≥1 and m; a list v:m→Rn with ∥vi∥2≤1 for i<m and ∑i<mvi=0. Every finite list below is extended by 0 beyond its range, so that the finite sums of Finite sums and finite products, by recursion apply verbatim; a list into Rn is summed in the vector space Rn (Linear combination of a finite list, and the span span⁡(S) as the smallest linear subspace containing S).

[L2]

Laws of finite sums of reals (Laws of finite sums and finite products, Finite sums and finite products, by recursion): additivity, scaling, splitting ∑i<rbi=∑i<qbi+∑i=qr−1bi for q≤r with ∑i=qr−1bi=∑l<r−qbq+l, monotonicity, ∑j<pλ=ι(p)λ, and the fact that a single term of a sum of nonnegative terms is at most the sum.

[L4]

The induction principle (The principle of mathematical induction) and the well-ordering principle: every nonempty subset of N has a least element (The well-ordering principle).

[L7]

The canonical natural (The canonical natural ι(n)=n⋅1F of a field, Canonical naturals are positive and strictly increasing): ι(0)=0 by the recursion clause, ι(p+q)=ι(p)+ι(q) for p,q≥1 by claim 3 there and trivially when p=0 or q=0, ι is strictly increasing, and ι(p)>0 for p≥1.

[L8]

Order arithmetic: u>0 gives u−1>0; an inequality may be multiplied by a nonnegative real; and trichotomy (Inverses of positives are positive, and reciprocation reverses order).

Proof

technique · constructive
1.1

Deleting one entry from a finite sum. Let b:N→R, let r≥1, let q<r, and let b∧q be the list with bi∧q:=bi for i<q and bi∧q:=bi+1 for q≤i<r−1. Then ∑i<rbi=∑i<r−1bi∧q+bq: splitting the left side at q and again at q+1 gives ∑i<qbi+bq+∑l<r−1−qbq+1+l, and splitting the right side at q gives ∑i<qbi+∑l<r−1−qbq+l+1, and the two agree.

L2
1.2

The easy case m≤n. Take π to be the identity of m, a bijection. For k≤m the finite triangle inequality and ∥vj∥2≤1 give ∥∑j<kvj∥2≤∑j<k∥vj∥2≤∑j<k1=ι(k)≤ι(n), since k≤m≤n and ι is increasing. So the theorem holds in this case, and we assume m>n from here on.

constructL1L2L7
1.3

Stage data. For n≤k≤m call a pair (b,μ) admissible at k when b:k→m is injective, μ:N→R vanishes at every j≥k, satisfies 0≤μj≤1 for j<k, and satisfies ∑j<kμjvb(j)=0 and ∑j<kμj=ι(k−n).

construct
1.4

Stage m is admissible. Take bm:= the identity of m and μjm:=ι(m−n)/ι(m) for j<m, μjm:=0 for j≥m; here ι(m)>0 because m>n≥1, and 0≤ι(m−n)≤ι(m) gives 0≤μjm≤1. Then ∑j<mμjmvj=(ι(m−n)/ι(m))∑j<mvj=0 and ∑j<mμjm=ι(m)⋅ι(m−n)/ι(m)=ι(m−n).

constructL2L7L8
1.5

The estimate for k<n, for an arbitrary ordering. For every bijection ρ:m→m and every k<n, the finite triangle inequality gives ∥∑j<kvρ(j)∥2≤∑j<k∥vρ(j)∥2≤∑j<k1=ι(k)≤ι(n).

L1L2L7
2.1

The reindexing identity. For every k∈N, every r∈N, every injective f:r→k and every c:N→R vanishing at every j<k outside the image of f, one has ∑j<kcj=∑i<rcf(i). This is proved by induction on k, with r, f and c universally quantified. At k=0 the only injective f:r→0 has r=0 and both sums are empty. At k+1, write ∑j<k+1cj=∑j<kcj+ck: if k is not in the image of f then ck=0 and f maps into k, so the inductive hypothesis applies directly; and if k=f(q) for the unique such q<r, then r≥1 and the list g:=f∧q of step 1.1 is an injective map r−1→k off whose image c vanishes on {j:j<k}, so the inductive hypothesis gives ∑j<kcj=∑i<r−1cg(i), while step 1.1 applied to bi:=cf(i) gives ∑i<rcf(i)=∑i<r−1cg(i)+cf(q); adding ck=cf(q) to the first identity yields the claim.

step 1.1L2L4
2.2

The feasible set at k−1 is nonempty. Let (b,μ) be admissible at k with n<k≤m, and let Λ be the set of all μ′:N→R vanishing at every j≥k, with 0≤μj′≤1 for j<k, ∑j<kμj′vb(j)=0 and ∑j<kμj′=ι(k−1−n). The scalar ρ:=ι(k−1−n)/ι(k−n) is defined and lies in [0,1], since ι(k−n)>0 and 0≤ι(k−1−n)≤ι(k−n); and ρμ lies in Λ.

step 1.3L2L7L8
3.1

Both identities hold verbatim for lists with values in Rn, since a vector identity is the conjunction of its n coordinate identities and the coordinates of a vector finite sum are the real finite sums of the coordinates.

step 1.1step 2.1L3
3.2

The minimal number of fractional coordinates. Call μ′∈Λ r-simple when there is an injective f:r→k with μj′∈{0,1} for every j<k outside the image of f. The set R:={ r∈N:some μ′∈Λ is r-simple } contains k, taking f to be the identity of k, so R is a nonempty set of naturals and has a least element r0; fix μ∈Λ and an injective f:r0→k witnessing it.

step 2.2L4
4.1

Two consequences used repeatedly. Taking k=r and f a bijection of k in step 2.1 gives ∑j<kcf(j)=∑j<kcj for every c; and taking c to vanish off the image of an injective f:r→k gives ∑j<kcj=∑i<rcf(i), both in R and in Rn.

step 2.1step 3.1
4.2

Every marked coordinate is strictly fractional. For every i<r0 one has 0<μf(i)<1: otherwise μf(i)∈{0,1}, and then f∧i, an injective map r0−1→k off whose image μ takes values in {0,1}, would witness that μ is (r0−1)-simple, contradicting minimality of r0.

step 1.1step 3.2
4.3

Suppose r0≥n+2, towards a contradiction. Define w:r0→Rn+1 by wi(t):=(vb(f(i)))(t) for t<n and wi(n):=1.

step 3.2
5.1

The list w is linearly dependent: there is λ:r0→R, not identically 0, with ∑i<r0λiwi=0. If w is not injective, say wi1=wi2 with i1≠i2, take λi1:=1, λi2:=−1 and λi:=0 otherwise; the list i↦λiwi then vanishes off {i1,i2} and sums to wi1−wi2=0 by step 4.1. If w is injective, its image is a subset of Rn+1 equinumerous with r0≥n+2, hence not linearly independent by [L6]; so some injective list h:p→im⁡(w) is linearly dependent, giving ν:p→R not identically 0 with ∑l<pνlh(l)=0, and setting λi:=νl when wi=h(l) and λi:=0 otherwise turns that into ∑i<r0λiwi=0 by step 4.1, the list i↦λiwi vanishing off the image of the injective map l↦ the unique i with wi=h(l).

step 4.3L6
5.2

The step length. Let i0 be the least i<r0 with λi≠0, which exists because λ is not identically 0. Define s:r0→R by si:=(1−μf(i))/λi if λi>0, by si:=μf(i)/(−λi) if λi<0, and by si:=si0 if λi=0; every si is a positive real by step 4.2. Put t∗:=min⁡{s0,…,sr0−1}, a minimum over a nonempty finite set of reals, so t∗>0 and t∗=si for some i<r0; choosing that i if λi≠0 and i0 otherwise, there is i∗<r0 with λi∗≠0 and t∗=si∗.

step 4.2L4L5L8
6.1

Reading the coordinates of step 5.1. The coordinate n gives ∑i<r0λi=0, and the coordinates t<n give ∑i<r0λivb(f(i))=0 in Rn.

step 4.3step 5.1L3
6.2

The moved point. Define μ′:N→R by μj′:=μj+t∗λi if j=f(i) for the unique i<r0 with that property, and μj′:=μj otherwise. Then 0≤μj′≤1 for every j<k: outside the image of f nothing changes; at j=f(i) with λi>0 one has μf(i)<μj′≤μf(i)+siλi=1; with λi<0 one has 0=μf(i)+siλi≤μj′<μf(i); and with λi=0 the value is unchanged.

step 4.2step 5.2L8
7.1

The moved point is feasible. The list j↦μj′−μj vanishes at every j<k off the image of f and takes the value t∗λi at f(i), so step 4.1 gives ∑j<k(μj′−μj)=∑i<r0t∗λi=t∗⋅0=0; likewise the Rn-valued list j↦(μj′−μj)vb(j) vanishes off that image and takes the value t∗λivb(f(i)) at f(i), so ∑j<k(μj′−μj)vb(j)=t∗∑i<r0λivb(f(i))=0. Hence ∑j<kμj′=ι(k−1−n) and ∑j<kμj′vb(j)=0, so μ′∈Λ.

step 4.1step 6.1step 6.2L2L3
8.1

The contradiction. By step 5.2, μf(i∗)′=μf(i∗)+t∗λi∗∈{0,1}. So f∧i∗, an injective map r0−1→k, witnesses that μ′ is (r0−1)-simple: off the image of f the value μj′=μj lies in {0,1}, and at f(i∗) it lies in {0,1} as just shown. This contradicts the minimality of r0, so the supposition of step 4.3 is untenable and r0≤n+1.

step 1.1step 3.2step 5.2step 6.2step 7.1
9.1

The support bound. There is j0<k with μj0=0. Suppose instead that μj>0 for every j<k; then off the image of f the value μj lies in {0,1} and is positive, hence equals 1. Put νj:=1−μj for j<k and νj:=0 for j≥k, so ν vanishes at every j<k off the image of f and satisfies 0<νf(i)<1 for i<r0 by step 4.2, while ∑j<kνj=ι(k)−ι(k−1−n)=ι(n+1) by [L7].

step 4.2step 8.1L2L7
10.1

By step 4.1, ∑j<kνj=∑i<r0νf(i). If r0=0 this is the empty sum 0, contradicting ι(n+1)>0. If r0≥1 then every term of ∑i<r0(1−νf(i)) is positive, so that sum is at least its term at index 0 and hence positive, whence ∑i<r0νf(i)=ι(r0)−∑i<r0(1−νf(i))<ι(r0)≤ι(n+1) using step 8.1. Either way ι(n+1)<ι(n+1) or ι(n+1)=0, both impossible; so some μj0 is 0.

step 4.1step 8.1step 9.1L2L7L8
11.1

Descending one stage. With j0 as in step 9.1, put b′:=b∧j0:k−1→m and μ′′:=μ∧j0, extended by 0 beyond k−1. Then b′ is injective with image im⁡(b)∖{b(j0)}, 0≤μj′′≤1 for j<k−1, and by step 1.1 in both its real and its vector form, ∑j<k−1μj′′=∑j<kμj−μj0=ι(k−1−n) and ∑j<k−1μj′′vb′(j)=∑j<kμjvb(j)−μj0vb(j0)=0. So (b′,μ′′) is admissible at k−1.

constructstep 1.1step 3.1step 3.2step 10.1
12.1

Iterating. Starting from the admissible pair of step 1.4 at k=m and applying step 11.1 once for each k from m down to n+1, one obtains admissible pairs (bk,μk) for every k with n≤k≤m, with im⁡(bk−1)⊆im⁡(bk) and im⁡(bk)∖im⁡(bk−1) a single element. This is a recursion of length m−n, each stage determined by the previous one together with finitely many determinations (a least natural, a minimum of a finite set of reals), so no choice principle is involved.

constructstep 1.4step 11.1L4L5
13.1

The ordering. Define π:m→m by π(j):=bn(j) for j<n and, for each k with n<k≤m, π(k−1):= the unique element of im⁡(bk)∖im⁡(bk−1). The images im⁡(bk) increase from im⁡(bn), of size n, to im⁡(bm)=m, gaining exactly one element at each stage, so π is injective with image m, that is a bijection, and for every k with n≤k≤m the set {π(j):j<k} is exactly im⁡(bk).

constructstep 12.1L4L6
14.1

Both enumerations give the same partial sum. Fix k with n≤k≤m and let c:N→Rn be ci:=vi for i∈im⁡(bk) and ci:=0 otherwise. Then c vanishes at every i<m off the image of the injective list j↦π(j) on k, and also off the image of bk, so step 4.1 applied twice gives ∑j<kvπ(j)=∑i<mci=∑j<kvbk(j).

step 4.1step 13.1
15.1

The estimate for n≤k≤m. Since ∑j<kμjkvbk(j)=0, additivity gives ∑j<kvbk(j)=∑j<k(1−μjk)vbk(j); each coefficient 1−μjk is nonnegative, so the finite triangle inequality and ∥vi∥2≤1 give ∥∑j<kvbk(j)∥2≤∑j<k(1−μjk)∥vbk(j)∥2≤∑j<k(1−μjk)=ι(k)−ι(k−n)=ι(n).

step 12.1step 14.1L1L2L7
16.1

By steps 14.1 and 15.1 the bound ∥∑j<kvπ(j)∥2≤ι(n) holds for n≤k≤m, and by step 1.5 it holds for k<n; together with the case m≤n of step 1.2, the required bijection π has been exhibited in every case.

step 1.2step 13.1step 14.1step 15.1step 1.5discharge-construct∎

Remarks

  • The support bound of steps 9.1 and 10.1 is the step most write-ups omit. From r0≤n+1 one gets only that the support of μ has at most (k−1−n)+(n+1)=k elements, which is no information at all. What rules out equality is that the quantities 1−μf(i) would then be strictly positive at each of at most n+1 marked indices while summing to ι(n+1); that is exactly the computation in steps 9.1 and 10.1, and without a coordinate μj0=0 the descending construction does not start.

  • Where the dimension enters, and only there. The single place the number n is used is step 5.1, where n+2 vectors in Rn+1 are linearly dependent. The extra coordinate constantly 1 is what converts the constraint ∑iλi=0 into a linear condition, so that one dependence delivers both identities of step 6.1 at once.

  • No choice principle is used. The construction is a recursion of length m−n; at each stage the objects produced are a least natural number (The well-ordering principle) and a minimum of a nonempty finite set of reals (Every nonempty finite set of reals has a maximum and a minimum), both determined rather than selected, and the pair (μ,f) of step 3.2 is a single selection from a nonempty set at each of finitely many stages.

  • The reindexing identity of step 2.1 is proved here rather than cited. Laws of finite sums and finite products is stated for sums ∑k<nak over an initial segment of N and carries no invariance clause, and no lemma available to this page gives the form step 2.1 needs — an injective f:r→k with the summand vanishing at every j<k off its image. That form is therefore proved here. Step 2.1 contains permutation invariance as the special case r=k with f a bijection.

  • The constant ι(n) is not claimed to be optimal. What is proved is that some ordering keeps every partial sum inside the ball of radius ι(n); on an explicit list of six unit vectors in R2 the companion page exhibits one ordering that meets the bound — with room to spare, so the bound is not attained there — and another that violates it, so the theorem is seen to say something.

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