Dual Linear Programming Bounds for Sphere Packing via Discrete Reductions

Abstract

The Cohn-Elkies linear program for sphere packing, which was used to solve the 8 and 24 dimensional cases, is conjectured to not be sharp in any other dimension $d>2$. By mapping feasible points of this infinite-dimensional linear program into a finite-dimensional problem via discrete reduction, we provide a general method to obtain dual bounds on the Cohn-Elkies linear program. This reduces the number of variables to be finite, enabling computer optimization techniques to be applied. Using this method, we prove that the Cohn-Elkies bound cannot come close to the best packing densities known in dimensions $3\le d\le 13$ except for the solved case $d=8$. In particular, our dual bounds show the Cohn-Elkies bound is unable to solve the 3, 4, and 5 dimensional sphere packing problems.

20 pages. Updated to include non-sharpness in dimension 5

References in corpus (3)

• New upper bounds for kissing numbers from semidefinite programming
• Unique Optima of the Delsarte Linear Program
• Six-dimensional sphere packing and linear programming