Exponential improvements for superball packing upper bounds
Ashwin Sah, Mehtaab Sawhney, David Stoner, and Yufei Zhao

TL;DR
This paper establishes the first exponential improvement in upper bounds for the packing density of unit b5c1-balls in high-dimensional spaces for all fixed p > 2, advancing understanding of geometric packing limits.
Contribution
It proves a new exponential upper bound on translative packing density of b5c1-balls in b5c4-dimensional space for all p > 2, improving previous bounds since 1936.
Findings
New exponential upper bounds for packing densities
First such improvements since 1936
Bound b3_p < -1/p for all p > 2
Abstract
We prove that for all fixed , the translative packing density of unit -balls in is at most with . This is the first exponential improvement in high dimensions since van der Corput and Schaake (1936).
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Exponential improvements for
superball packing upper bounds
Ashwin Sah
Massachusetts Institute of Technology, Cambridge, MA 02139, USA
,
Mehtaab Sawhney
Massachusetts Institute of Technology, Cambridge, MA 02139, USA
,
David Stoner
Department of Mathematics, Stanford University, Stanford, CA 94305, USA
and
Yufei Zhao
Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
Abstract.
We prove that for all fixed , the translative packing density of unit -balls in is at most with . This is the first exponential improvement in high dimensions since van der Corput and Schaake (1936).
YZ was supported by NSF Awards DMS-1362326 and DMS-1764176, and the MIT Solomon Buchsbaum Fund.
1. Introduction
The sphere packing problem asks for the densest packing of non-overlapping unit balls in . This is an old and difficult problem whose exact solution is only known in dimensions 1, 2, 3, 8, and 24. The problem is already non-trivial in two dimensions (see [8] for a short proof). The three-dimensional sphere packing problem is known as Kepler’s conjecture, and it was solved by Hales [9] via a monumental computer-assisted proof. The problem in eight dimensions was recently resolved by Viazovska [23] in a stunning breakthrough, and the method was then quickly extended to solve the problem in twenty-four dimensions [3]. Dimensions 8 and 24 are special due to the existence of highly dense and symmetric lattices known as the lattice (dimension 8) and the Leech lattice (dimension 24). See the survey [2] and its references for background and recent developments.
In this paper, we study translative packings of -balls in high dimensions. Denote the -balls with radius in by and the unit -ball by . Here is the -norm. The name superball refers to -balls with [19]. Superballs are more cube-like compared to the familiar -balls. See [10, 11, 5] for studies of -ball packings in . Although -balls do not possess rotational symmetry, in this paper we only consider translations of identical -balls, not allowing rotations. The best known lower bounds on high dimensional superball packing densities do not use rotations [6] (see Section 3.2).
Let denote the maximum translative packing density of copies of in . Here density is the fraction of space occupied by these balls. For fixed , let
[TABLE]
be the exponential rate of optimal packing densities in high dimensions. The precise value of is unknown for any , and the current best upper and lower bounds are quite far apart. For Euclidean balls, , the best high dimensional upper bound (apart from constant factors) is due to Kabatiansky and Levenshtein [12]:
[TABLE]
See Cohn and Zhao [4] and Sardari and Zargar [20] for constant factor improvements over Kabatiansky and Levenshtein [12]. For lower bounds, we have for all and since every maximal packing has density at least . For , there have only been subexponential improvements, with the current best lower bound due to Venkatesh [22]. In summary, the best bounds on are .
For , the current best upper bound on the exponential rate of superball packing densities was first proved by van der Corput and Schaake [21] via Blichfeldt’s method [1] (e.g., see [24, Section 6.3]), giving
[TABLE]
There have been subsequent subexponential upper bound improvements on for , e.g., Rankin [16, 17]. We defer to Section 3 for a discussion of known bounds on in other regimes.
In this paper, we prove a new upper bound on for all , giving the first exponential improvement since 1936 on the upper bound of superball packing densities in high dimensions.
Theorem 1.1**.**
For all ,
[TABLE]
In particular, for all .
See Figure 1 for a plot of the bounds.
Remark*.*
Theorem 1.1 with recovers . Our upper bound on is continuous with , whereas the previous best bounds were not continuous111It is unknown whether is continuous. Lemma 3.1 implies that is continuous at all but at most countably many points. at . The fact that our bound at recovers the Kabatiansky–Levenshtein bound is not a coincidence, as our proof relies on the Kabatiansky–Levenshtein bound for spherical codes.
2. Proof of main theorem
2.1. Kabatiansky–Levenshtein spherical code bound
Denote the -sphere in of radius by and the unit -sphere by . Let to be the maximum number of points on with pairwise -distance at least , i.e, an -spherical code. Note that unless . Note that is the maximum size of a spherical code in with pairwise angle at least . Kabatiansky and Levenshtein [12] proved that for all222A simple geometric argument (see [13, (17)]) shows that the upper bound (2.1) can be improved for to , but this improvement does not benefit our bounds. ,
[TABLE]
where
[TABLE]
A projection argument (see [4, Section 2]) shows that
[TABLE]
so (2.1) gives
[TABLE]
The bound is obtained by choosing to minimize the upper bound above.
2.2. -twist
Fix . Define
[TABLE]
For , write , and for , write .
Observe that for all ,
[TABLE]
Indeed, without loss of generality it suffices to consider two cases: and . The former case is an immediate consequence of Hölder’s inequality (or the convexity of ). In the latter case, we have
[TABLE]
Here we use for , which can be proved by first normalizing to and noting that .
Lemma 2.1**.**
For all and , we have .
Proof.
Let with and for all distinct . We have for all , so . For distinct , we have
[TABLE]
by (2.2). Thus is a subset of whose points have pairwise -distance at least . Hence . ∎
Remark*.*
The same argument shows that for all and .
Lemma 2.2**.**
For every , , and , we have .
Proof.
Let be arbitrary. Consider a translative packing in with density greater than , where is the set of centers of the -balls. By an averaging argument333A uniform random translation of a unit -ball inside contains more than points of ., there exists some translate of a unit -ball that contains at least points of . Translating if necessary, we may assume that . Add an -st coordinate to each point in to obtain a set of points on the unit -sphere in . In other words, is obtained by projecting the points of contained in the unit ball “upward” to the hemisphere one dimension higher. Since the points in are pairwise at least apart in -distance, the same holds for . So is an -spherical code whose points are pairwise separated by -distance at least , and hence . Since can be arbitrarily close to , we obtain the claimed inequality. ∎
Remark*.*
As in [4], the above argument can be modified so that we do not need to add a new dimension when , resulting in a slightly better bound . We omit the details of this modification since this improvement does not affect the exponential asymptotics.
Proof of Theorem 1.1.
Applying Lemmas 2.2 and 2.1, we have, for every ,
[TABLE]
Applying (2.1), we obtain
[TABLE]
The main result follows by taking the infimum of the bound over .
Setting , we have, with fixed and ,
[TABLE]
So choosing sufficiently small gives for all . ∎
3. Remarks
3.1. Asymptotics
Setting , we obtain
[TABLE]
Taking gives
[TABLE]
Thus, as ,
[TABLE]
3.2. Review of other bounds on
Here we survey other existing bounds on .
For , the best known bounds are as discussed earlier.
For , the best known upper bounds are the ones given in this paper. For lower bounds, extending on methods developed by Rush [18] and Rush–Sloane [19], Elkies, Odlyzko, and Rush [6] proved for all , thereby exponentially beating the Minkowski–Hlawka lower bound. See [6] for the precise bound. Their bounds have the following asymptotics:
[TABLE]
and
[TABLE]
Here denotes the Riemann zeta function. See [14] for some later improvements using algebraic-geometric codes for some specific integers .
For , no improvement over the Minkowski–Hlawka lower bound is known. The best upper bound on is due to Rankin [15], based on Blichfeldt’s method [1]:
[TABLE]
where
[TABLE]
Recall that .
For packings of congruent cross-polytopes (i.e., unit -balls) allowing rotations, Fejes Tóth, Fodor, and Vígh [7] proved an exponentially decaying upper bound in high dimensions. For translative packing of unit -balls, the upper bound 3.1 remains best known in high dimensions.
We note that the above bound (3.1) can be improved on the region using the Kabatiansky–Levenshtein bound via the following folklore observation.
Lemma 3.1**.**
For , .
Proof.
By monotonicity of norms, we have , so . Any packing of can be shrunk into a packing of . Hence
[TABLE]
Taking log, dividing by , and letting yields the lemma. ∎
Using , we find that
[TABLE]
Thus
[TABLE]
See Figure 1 for an illustration of the above bounds.
Acknowledgments
This work began during Y.Z.’s internship at Microsoft Research New England, and he would like to thank Henry Cohn for discussions and mentorship and Microsoft Research for its hospitality.
The reference list from the paper itself. Each links out to its DOI / PubMed record.
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- 2[2] Henry Cohn, A conceptual breakthrough in sphere packing , Notices Amer. Math. Soc. 64 (2017), 102–115.
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- 5[5] M. Dostert and F. Vallentin, New dense superball packings in three dimensions , ar Xiv:1806.10878.
- 6[6] N. D. Elkies, A. M. Odlyzko, and J. A. Rush, On the packing densities of superballs and other bodies , Invent. Math. 105 (1991), 613–639.
- 7[7] G. Fejes Tóth, F. Fodor, and V. Vígh, The packing density of the n 𝑛 n -dimensional cross-polytope , Discrete Comput. Geom. 54 (2015), 182–194.
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