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arXiv 2211.00536math.COmath.PR
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概率停车函数

Probabilistic Parking Functions

Irfan Durmić, Alex Han, Pamela E. Harris, Rodrigo Ribeiro, Mei Yin

摘要:

我们考虑经典的停车功能的概念,通过引入随机性和一个新的停车协议,在论文“停车功能:选择你自己的冒险,”(arXiv:2001.04817)卡尔森,克里斯滕森,哈里斯,琼斯和罗德里格斯提出的工作的启发。在我们的结果中,我们证明了从长度$n$偏好向量获得停车函数的概率与概率参数$p$无关。我们还探讨了属性的偏好向量,它是一个停车功能,并讨论了概率参数$p$的效果。特别感兴趣的是当$p=1/2$,在那里我们证明了一些停车统计急剧转变。我们还提出了几个有趣的组合后果的停车协议。特别是,我们为OEIS A220884中描述的数组提供了一个组合解释,作为具有与占用停车位相关的特定属性的偏好序列的预期数量,这解决了Novelli和Thibon在2020年提出的一个开放问题(arXiv:1209.5959)。最后,我们将我们的结果连接到组合数学中的其他加权现象,并提供进一步的研究方向。

英文摘要:

We consider the notion of classical parking functions by introducing randomness and a new parking protocol, as inspired by the work presented in the paper ``Parking Functions: Choose your own adventure,'' (arXiv:2001.04817) by Carlson, Christensen, Harris, Jones, and Rodríguez. Among our results, we prove that the probability of obtaining a parking function, from a length $n$ preference vector, is independent of the probabilistic parameter $p$. We also explore the properties of a preference vector given that it is a parking function and discuss the effect of the probabilistic parameter $p$. Of special interest is when $p=1/2$, where we demonstrate a sharp transition in some parking statistics. We also present several interesting combinatorial consequences of the parking protocol. In particular, we provide a combinatorial interpretation for the array described in OEIS A220884 as the expected number of preference sequences with a particular property related to occupied parking spots, which solves an open problem of Novelli and Thibon posed in 2020 (arXiv:1209.5959). Lastly, we connect our results to other weighted phenomena in combinatorics and provide further directions for research.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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