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arXiv 2407.10697math.MGcs.ITmath.COmath.IT
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Stiefel流形与球面编码和堆积的上界

Stiefel manifolds and upper bounds for spherical codes and packings

Masoud Zargar

AI总结:

该研究利用Stiefel流形构造通用函数类,将高维球体堆积密度和球面编码规模的Kabatyanskii-Levenshtein上界改进了1/e因子,证明该常数最优且改进与特殊角度无关,球面编码情形几何平均改进达0.2304倍。

摘要:

我们改进了高维空间中球体堆积密度和球面编码规模的上界。具体而言,我们证明了对于大的n,n维欧氏空间ℝⁿ中的最大球体堆积密度δₙ满足δₙ ≤ (1+o(1))/e · δₙ^KL,其中δₙ^KL是Kabatyanskii和Levenshtein在20世纪70年代得到、经多年改进的δₙ的最优上界。我们还对(n-1)维单位球面S^{n-1}中θ-球面编码的最大规模M(n,θ)得到了相同的改进因子:对于角度0<θ<θ'≤π/2,当n很大时,M(n,θ) ≤ (1+o(1))/e · M_Lev(n-1,θ')/μₙ(θ,θ'),其中μₙ(θ,θ')是S^{n-1}中半径为sin(θ/2)/sin(θ'/2)的球冠的质量,M_Lev(n-1,θ')是将Delsarte线性规划方法应用于Levenshtein最优多项式时得到的M(n-1,θ')的Levenshtein上界。事实上,我们证明了论证中不存在解析损耗,且常数1/e=0.367…对于所考虑的函数类是最优的。我们的结果还表明改进因子不依赖于特殊角度θ*=62.997…度,这解释了arXiv:2001.00185中的数值结果。在球面编码情形下,上述不等式将Kabatyanskii–Levenshtein上界的几何平均改进了0.2304…倍。在此过程中,我们利用Stiefel流形构造了一类通用函数,证明了关于这类函数的一般性结果,并研究了在不同设定下从中得到的改进因子。

英文摘要:

We improve upper bounds on sphere packing densities and sizes of spherical codes in high dimensions. In particular, we prove that the maximal sphere packing densities $δ_n$ in $\mathbb{R}^n$ satisfy \[δ_n\leq \frac{1+o(1)}{e}\cdot δ^{\text{KL}}_{n}\] for large $n$, where $δ^{\text{KL}}_{n}$ is the best bound on $δ_n$ obtained essentially by Kabatyanskii and Levenshtein from the 1970s with improvements over the years. We also obtain the same improvement factor for the maximal size $M(n,θ)$ of $θ$-spherical codes in $S^{n-1}$: for angles $0<θ<θ'\leq\fracπ{2}$, \[M(n,θ)\leq \frac{1+o(1)}{e}\cdot \frac{M_{\text{Lev}}(n-1,θ')}{μ_n(θ,θ')}\] for large $n$, where $μ_n(θ,θ')$ is the mass of the spherical cap in the unit sphere $S^{n-1}$ of radius $\frac{\sin(θ/2)}{\sin(θ'/2)}$, and $M_{\text{Lev}}(n-1,θ')$ is Levenshtein's upper bound on $M(n-1,θ')$ when applying the Delsarte linear programming method to Levenshtein's optimal polynomials. In fact, we prove that there are no analytic losses in our arguments and that the constant $\frac{1}{e}=0.367...$ is optimal for the class of functions considered. Our results also show that the improvement factor does not depend on the special angle $θ^*=62.997...^{\circ}$, explaining the numerics in arXiv:2001.00185. In the spherical codes case, the above inequality improves the Kabatyanskii--Levenshtein bound by a factor of $0.2304...$ on geometric average. Along the way, we construct a general class of functions using Stiefel manifolds for which we prove general results and study the improvement factors obtained from them in various settings.and study the improvement factors obtained from them in various settings.

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