论文标题

吸收整数及其Darboux转换的出生死亡链的反射因素化

Absorbing-reflecting factorizations for birth-death chains on the integers and their Darboux transformations

论文作者

de la Iglesia, Manuel D., Juarez, Claudia

论文摘要

我们考虑了一种新的方法,可以通过吸收和反射到状态0和Viceversa的反射出生死亡链来分解整数上离散时间死亡链的过渡概率矩阵。首先,我们将考虑反映整数上出生死亡链的吸收性因素。我们给出两个自由参数的条件,使每个因素都是随机矩阵。通过颠倒这些因素的顺序(也称为Darboux转型),我们在整数上获得了新的“几乎”出生死亡链的新家庭,唯一的差异是我们从国家$ 1 $到州$ -1 $和Viceversa的新概率。另一方面,只有在两个因素将两个因素拆分为两个分离的出生死亡链$ 0 $的情况下,才有可能将出生死亡链的吸收反射分解。因此,考虑吸收“几乎”出生死亡链的反射因素化,并在各州之间进行额外过渡,并在某些情况下进行额外的过渡。现在,这种分解是独一无二的,并且通过颠倒整数上的生育死亡链的顺序。在这两种情况下,我们都会确定与Darboux转换相关的光谱矩阵,第一个是Geronimus转换,第二个是原始频谱矩阵的基督教转换。我们将结果应用于具有恒定过渡概率的链的示例。

We consider a new way of factorizing the transition probability matrix of a discrete-time birth-death chain on the integers by means of an absorbing and a reflecting birth-death chain to the state 0 and viceversa. First we will consider reflecting-absorbing factorizations of birth-death chains on the integers. We give conditions on the two free parameters such that each of the factors is a stochastic matrix. By inverting the order of the factors (also known as a Darboux transformation) we get new families of "almost" birth-death chains on the integers with the only difference that we have new probabilities going from the state $1$ to the state $-1$ and viceversa. On the other hand an absorbing-reflecting factorization of birth-death chains on the integers is only possible if both factors are splitted into two separated birth-death chains at the state $0$. Therefore it makes more sense to consider absorbing-reflecting factorizations of "almost" birth-death chains with extra transitions between the states $1$ and $-1$ and with some conditions. This factorization is now unique and by inverting the order of the factors we get a birth-death chain on the integers. In both cases we identify the spectral matrices associated with the Darboux transformation, the first one being a Geronimus transformation and the second one a Christoffel transformation of the original spectral matrix. We apply our results to examples of chains with constant transition probabilities.

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