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Steinitz's polygonal confinement theorem: finitely many vectors of norm at most summing to can be ordered so that every partial sum has norm at most
Statement
Let with , let and let be a finite list of vectors with
Then there is a bijection (Injection, surjection, bijection) such that
where is the canonical natural of (The canonical natural of a field) and the sums are the finite sums of the vector space (Linear combination of a finite list, and the span as the smallest linear subspace containing ).
The bound depends only on the dimension, not on . That is the whole content: the triangle inequality alone gives only , 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 and ; a list with for and . Every finite list below is extended by beyond its range, so that the finite sums of Finite sums and finite products, by recursion apply verbatim; a list into is summed in the vector space (Linear combination of a finite list, and the span as the smallest linear subspace containing ).
Norm facts: is a norm on , , , and the finite triangle inequality (A norm on a real vector space, the induced metric, and the dictionary with the metric axioms, The -norms for rational , and , Each is a norm on , and the induced metrics are exactly , and of the published metric-spaces page, Cauchy-Schwarz with its equality case, the triangle inequality for , the parallelogram law and polarisation, The finite and reverse triangle inequalities for a norm; and for every norm on satisfies and is Lipschitz, hence continuous, for clause 1).
Laws of finite sums of reals (Laws of finite sums and finite products, Finite sums and finite products, by recursion): additivity, scaling, splitting for with , monotonicity, , and the fact that a single term of a sum of nonnegative terms is at most the sum.
Finite sums in are computed pointwise: for (The standard list with and for is an ordered basis of ; hence , and is the zero space with basis and dimension clause 1), so every identity between real finite sums yields the corresponding identity between -valued ones; and two elements of are equal exactly when all their coordinates are (The vector space of all functions with pointwise operations, and as the case , Vector space over a field, In any vector space , , , , and forces or ).
The induction principle (The principle of mathematical induction) and the well-ordering principle: every nonempty subset of has a least element (The well-ordering principle).
A nonempty finite set of reals has a maximum and a minimum, each an element of the set (Every nonempty finite set of reals has a maximum and a minimum, Maximum and minimum of a set, The nonempty finite subsets of are exactly the listable ones).
Dimension count: has a basis with elements (The standard list with and for is an ordered basis of ; hence , and is the zero space with basis and dimension clauses 2 and 4, Finite-dimensional vector space, and its dimension ; infinite-dimensional means having no finite basis), so every linearly independent subset of is finite with at most elements (If has a spanning set with elements, then every linearly independent subset of is finite with at most elements; in particular has no linearly independent subset equinumerous with , Linear independence: a finite list is independent when forces every , and a subset is independent when every injective finite list into is independent, Finite, countably infinite, countable, uncountable, Equinumerous sets, and , The pigeonhole principle on ).
The canonical natural (The canonical natural of a field, Canonical naturals are positive and strictly increasing): by the recursion clause, for by claim 3 there and trivially when or , is strictly increasing, and for .
Order arithmetic: gives ; an inequality may be multiplied by a nonnegative real; and trichotomy (Inverses of positives are positive, and reciprocation reverses order).
Proof
Deleting one entry from a finite sum. Let , let , let , and let be the list with for and for . Then : splitting the left side at and again at gives , and splitting the right side at gives , and the two agree.
The easy case . Take to be the identity of , a bijection. For the finite triangle inequality and give , since and is increasing. So the theorem holds in this case, and we assume from here on.
Stage data. For call a pair admissible at when is injective, vanishes at every , satisfies for , and satisfies and .
Stage is admissible. Take the identity of and for , for ; here because , and gives . Then and .
The estimate for , for an arbitrary ordering. For every bijection and every , the finite triangle inequality gives .
The reindexing identity. For every , every , every injective and every vanishing at every outside the image of , one has . This is proved by induction on , with , and universally quantified. At the only injective has and both sums are empty. At , write : if is not in the image of then and maps into , so the inductive hypothesis applies directly; and if for the unique such , then and the list of step 1.1 is an injective map off whose image vanishes on , so the inductive hypothesis gives , while step 1.1 applied to gives ; adding to the first identity yields the claim.
The feasible set at is nonempty. Let be admissible at with , and let be the set of all vanishing at every , with for , and . The scalar is defined and lies in , since and ; and lies in .
Both identities hold verbatim for lists with values in , since a vector identity is the conjunction of its coordinate identities and the coordinates of a vector finite sum are the real finite sums of the coordinates.
The minimal number of fractional coordinates. Call -simple when there is an injective with for every outside the image of . The set contains , taking to be the identity of , so is a nonempty set of naturals and has a least element ; fix and an injective witnessing it.
Two consequences used repeatedly. Taking and a bijection of in step 2.1 gives for every ; and taking to vanish off the image of an injective gives , both in and in .
Every marked coordinate is strictly fractional. For every one has : otherwise , and then , an injective map off whose image takes values in , would witness that is -simple, contradicting minimality of .
Suppose , towards a contradiction. Define by for and .
The list is linearly dependent: there is , not identically , with . If is not injective, say with , take , and otherwise; the list then vanishes off and sums to by step 4.1. If is injective, its image is a subset of equinumerous with , hence not linearly independent by [L6]; so some injective list is linearly dependent, giving not identically with , and setting when and otherwise turns that into by step 4.1, the list vanishing off the image of the injective map the unique with .
The step length. Let be the least with , which exists because is not identically . Define by if , by if , and by if ; every is a positive real by step 4.2. Put , a minimum over a nonempty finite set of reals, so and for some ; choosing that if and otherwise, there is with and .
Reading the coordinates of step 5.1. The coordinate gives , and the coordinates give in .
The moved point. Define by if for the unique with that property, and otherwise. Then for every : outside the image of nothing changes; at with one has ; with one has ; and with the value is unchanged.
The moved point is feasible. The list vanishes at every off the image of and takes the value at , so step 4.1 gives ; likewise the -valued list vanishes off that image and takes the value at , so . Hence and , so .
The contradiction. By step 5.2, . So , an injective map , witnesses that is -simple: off the image of the value lies in , and at it lies in as just shown. This contradicts the minimality of , so the supposition of step 4.3 is untenable and .
The support bound. There is with . Suppose instead that for every ; then off the image of the value lies in and is positive, hence equals . Put for and for , so vanishes at every off the image of and satisfies for by step 4.2, while by [L7].
By step 4.1, . If this is the empty sum , contradicting . If then every term of is positive, so that sum is at least its term at index and hence positive, whence using step 8.1. Either way or , both impossible; so some is .
Descending one stage. With as in step 9.1, put and , extended by beyond . Then is injective with image , for , and by step 1.1 in both its real and its vector form, and . So is admissible at .
Iterating. Starting from the admissible pair of step 1.4 at and applying step 11.1 once for each from down to , one obtains admissible pairs for every with , with and a single element. This is a recursion of length , 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.
The ordering. Define by for and, for each with , the unique element of . The images increase from , of size , to , gaining exactly one element at each stage, so is injective with image , that is a bijection, and for every with the set is exactly .
Both enumerations give the same partial sum. Fix with and let be for and otherwise. Then vanishes at every off the image of the injective list on , and also off the image of , so step 4.1 applied twice gives .
The estimate for . Since , additivity gives ; each coefficient is nonnegative, so the finite triangle inequality and give .
By steps 14.1 and 15.1 the bound holds for , and by step 1.5 it holds for ; together with the case of step 1.2, the required bijection has been exhibited in every case.
Remarks
-
The support bound of steps 9.1 and 10.1 is the step most write-ups omit. From one gets only that the support of has at most elements, which is no information at all. What rules out equality is that the quantities would then be strictly positive at each of at most marked indices while summing to ; that is exactly the computation in steps 9.1 and 10.1, and without a coordinate the descending construction does not start.
-
Where the dimension enters, and only there. The single place the number is used is step 5.1, where vectors in are linearly dependent. The extra coordinate constantly is what converts the constraint into a linear condition, so that one dependence delivers both identities of step 6.1 at once.
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No choice principle is used. The construction is a recursion of length ; 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 of step 3.2 is a single selection from a nonempty set at each of finitely many stages.
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The reindexing identity of step 2.1 is proved here rather than cited. Laws of finite sums and finite products is stated for sums over an initial segment of and carries no invariance clause, and no lemma available to this page gives the form step 2.1 needs — an injective with the summand vanishing at every off its image. That form is therefore proved here. Step 2.1 contains permutation invariance as the special case with a bijection.
-
The constant is not claimed to be optimal. What is proved is that some ordering keeps every partial sum inside the ball of radius ; on an explicit list of six unit vectors in 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.
Depends on
- Series of vectors in $\mathbb{R}^n$, absolute convergence, rearrangement, and the set of rearrangement sums
- The Euclidean inner product $\langle x,y\rangle = \sum_{k<n} x_k y_k$ on $\mathbb{R}^n$
- The $p$-norms $\lVert x\rVert_p$ for rational $p \ge 1$, and $\lVert x\rVert_\infty$
- Each $\lVert\cdot\rVert_p$ is a norm on $\mathbb{R}^n$, and the induced metrics are exactly $d_1$, $d_2$ and $d_\infty$ of the published metric-spaces page
- Cauchy-Schwarz $\lvert\langle x,y\rangle\rvert \le \lVert x\rVert_2\lVert y\rVert_2$ with its equality case, the triangle inequality for $\lVert\cdot\rVert_2$, the parallelogram law and polarisation
- The finite and reverse triangle inequalities for a norm; and for $n \ge 1$ every norm $N$ on $\mathbb{R}^n$ satisfies $N(x) \le C\lVert x\rVert_1$ and is Lipschitz, hence continuous, for $d_2$
- A norm on a real vector space, the induced metric, and the dictionary with the metric axioms
- If $V$ has a spanning set with $n$ elements, then every linearly independent subset of $V$ is finite with at most $n$ elements; in particular $V$ has no linearly independent subset equinumerous with $\mathbb{N}$
- Linear independence: a finite list $v : n \to V$ is independent when $\sum_{i<n} \lambda_i v_i = 0_V$ forces every $\lambda_i = 0_F$, and a subset $S \subseteq V$ is independent when every injective finite list into $S$ is independent
- Finite-dimensional vector space, and its dimension $\dim_F V$; infinite-dimensional means having no finite basis
- The standard list $e : n \to F^{n}$ with $e_i(i) = 1_F$ and $e_i(j) = 0_F$ for $j \ne i$ is an ordered basis of $F^{n}$; hence $\dim_F F^{n} = n$, and $F^{0}$ is the zero space with basis $\varnothing$ and dimension $0$
- Linear combination of a finite list, and the span $\operatorname{span}(S)$ as the smallest linear subspace containing $S$
- The well-ordering principle
- Every nonempty finite set of reals has a maximum and a minimum
- Maximum and minimum of a set
- Laws of finite sums and finite products
- Finite sums and finite products, by recursion
- The nonempty finite subsets of $\mathbb{R}$ are exactly the listable ones
- Finite, countably infinite, countable, uncountable
- The pigeonhole principle on $\mathbb{N}$
- Injection, surjection, bijection
- The canonical natural $\iota(n) = n \cdot 1_F$ of a field
- Canonical naturals are positive and strictly increasing
- The vector space $F^{X}$ of all functions $X \to F$ with pointwise operations, and $F^{n}$ as the case $X = n = \{0, 1, \dots, n-1\}$
- Vector space over a field
- The principle of mathematical induction
- Inverses of positives are positive, and reciprocation reverses order
- Equinumerous sets, $A \approx B$ and $A \preceq B$
- In any vector space $0_F v = 0_V$, $\lambda 0_V = 0_V$, $(-\lambda)v = -(\lambda v)$, $(-1_F)v = -v$, and $\lambda v = 0_V$ forces $\lambda = 0_F$ or $v = 0_V$
Used by
Dependency tree · next 3 levels
Direct dependencies and their dependencies through the next three levels: 202 results over 36 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
- Levy-Steinitz theorem (Wikipedia) (standard reference, not scraped)
- Ernst Steinitz (Wikipedia), for the 1913 paper in which the rearrangement lemma appears (standard reference, not scraped)
- T. Oertel, J. Paat and R. Weismantel, A Colorful Steinitz Lemma with Applications to Block Integer Programs (standard reference, not scraped)