论文标题
离散且连续的muttalib--核苷过程I:硬边缘
Discrete and continuous Muttalib--Borodin processes I: the hard edge
论文作者
论文摘要
在本说明中,我们研究了对平面分区的自然度量,从而导致一定的离散时间muttalib-borodin工艺(MBP):每个时间片是muttalib-borodin集合(MBE)的离散版本。该过程是确定性的,具有明确的时间依赖性相关内核。此外,在$ q \至1 $限制中,它会收敛到连续的类似雅各比的MBP,并在单位间隔内支撑的Muttalib-Borodin边缘。这种连续的过程也是确定性的,具有显式相关内核。我们研究其硬边缩放限制(左右),以获得随机矩阵理论的经典连续贝塞尔内核的离散时间依赖性概括(实际上,也是meijer $ g $ -KERNEL的)。最后,我们讨论了两个相关的应用程序:从此类过程中进行的随机抽样及其解释为指向最后一段渗透模型(LPP)。在此过程中,我们引入了一种与Jacobi流程自然相关的角增长模型,该模型的版本是对数坐标中Forrester Rains的“通常”角增长。上述Mbps的硬边限制为这些LPP模型带来了有趣的渐近性。特别是,我们的LPP渐近学的特殊情况会产生(通过随机矩阵Bessel内核并遵循Johansson的领先),达到了Tracy-Widom Gue和Gumbel分布之间的极端统计分布。
In this note we study a natural measure on plane partitions giving rise to a certain discrete-time Muttalib-Borodin process (MBP): each time-slice is a discrete version of a Muttalib-Borodin ensemble (MBE). The process is determinantal with explicit time-dependent correlation kernel. Moreover, in the $q \to 1$ limit, it converges to a continuous Jacobi-like MBP with Muttalib-Borodin marginals supported on the unit interval. This continuous process is also determinantal with explicit correlation kernel. We study its hard-edge scaling limit (around 0) to obtain a discrete-time-dependent generalization of the classical continuous Bessel kernel of random matrix theory (and, in fact, of the Meijer $G$-kernel as well). We lastly discuss two related applications: random sampling from such processes, and their interpretations as models of directed last passage percolation (LPP). In doing so, we introduce a corner growth model naturally associated to Jacobi processes, a version of which is the "usual" corner growth of Forrester-Rains in logarithmic coordinates. The aforementioned hard edge limits for our MBPs lead to interesting asymptotics for these LPP models. In particular, a special cases of our LPP asymptotics give rise (via the random matrix Bessel kernel and following Johansson's lead) to an extremal statistics distribution interpolating between the Tracy-Widom GUE and the Gumbel distributions.