在高维度的统一跨度树的 GHP 缩放限制
Eleanor Archer1,2, Asaf Nachmias1, Matan Shalev1
1Department of Mathematical Sciences, Tel Aviv University, 69978 Tel Aviv, Israel.
概括
布朗连续随机树是高维图上统一跨度树的缩放极限. 这一发现扩展到诸如直径和高度之类的相关量,揭示了它们的连续类比.
科学领域:
- 概率理论的概率理论是什么
- 图形理论是指图形的理论.
- 随机过程是指随机的过程.
背景情况:
- 统一跨度树 (UST) 是统计物理学和概率论中的基本对象.
- 了解像图表上的 UST 这样的离散结构的缩放极限对于将离散和连续模型相结合至关重要.
- 高维图,包括托里,超立方体和扩展图,作为研究非对称行为的重要测试台.
研究的目的:
- 在各种高维图上建立布朗连续随机树作为 UST 的格罗莫夫-豪斯多夫-普罗霍罗夫缩放极限.
- 推断有关联的USTT数量与连续性的对应数量的趋同的相关结果.
- 提供一个严格的数学框架,以理解高维度的USTs的大规模几何.
主要方法:
- 利用概率理论和几何分析的技术.
- 将格罗莫夫 - 豪斯多夫 - 普罗霍罗夫收的概念应用于随机度量空间.
- 在特定类型的高维图 (d-dimensional torus,超立方,扩展器图) 上分析 UST 的结构.
主要成果:
- 布朗连续的随机树被证明是USTs在高维的托里,超立方体和扩展图上的缩放极限.
- 对于这些 UST 的重新缩放的直径和高度,分布的趋同被显示为它们的连续类型.
- 简单的随机步行在这些USTs的行为也被证明是汇聚到他们的连续性对应物.
结论:
- 这项研究建立了在高维图上的离散UST和连续的布朗连续随机树之间的深层联系.
- 结果提供了对高维度极限中的随机树的通用几何性质的见解.
- 这项工作为进一步研究其他随机图结构的缩放极限提供了基础.
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