论文标题
在矩形可分配的2参数持久性模块上
On rectangle-decomposable 2-parameter persistence modules
论文作者
论文摘要
本文解决了两个问题:(a)我们可以确定一组明智的2参数持久性模块,该模块在该模块上不变了吗? (b)我们可以有效地确定给定的2参数持久性模块是否属于此类?我们为这两个问题提供了积极的答案,而我们的兴趣类别是矩形可解释的模块。我们的贡献包括:一方面,证明了矩形可分离模块的等级不变性,以及用于计算汇总多重性的包含 - 排斥公式;另一方面,算法要检查通过分叉在同源物中诱导的模块是否可以矩形解释,并以肯定性分解,其复杂性比对一般2参数仪持续模块的总体分解方法更好。我们的算法得到了一个新的结构定理的支持,因此,当它的2参数持久模块可矩形解释时,并且只有当它的正方形限制为限制时。这种局部表征是我们算法效率的关键,它概括了针对较小类别可分配模块的先前条件。它还承认了一种代数配方,该公式被证明是块可分配性的较弱版本。相比之下,我们表明,即使从广义上理解了当地,一般的间隔可分配性也不承认这种局部特征。我们的分析重点是在有限网格上索引的模块的情况下,作为将来的工作,较为一般的情况。
This paper addresses two questions: (a) can we identify a sensible class of 2-parameter persistence modules on which the rank invariant is complete? (b) can we determine efficiently whether a given 2-parameter persistence module belongs to this class? We provide positive answers to both questions, and our class of interest is that of rectangle-decomposable modules. Our contributions include: on the one hand, a proof that the rank invariant is complete on rectangle-decomposable modules, together with an inclusion-exclusion formula for counting the multiplicities of the summands; on the other hand, algorithms to check whether a module induced in homology by a bifiltration is rectangle-decomposable, and to decompose it in the affirmative, with a better complexity than state-of-the-art decomposition methods for general 2-parameter persistence modules. Our algorithms are backed up by a new structure theorem, whereby a 2-parameter persistence module is rectangle-decomposable if, and only if, its restrictions to squares are. This local characterization is key to the efficiency of our algorithms, and it generalizes previous conditions derived for the smaller class of block-decomposable modules. It also admits an algebraic formulation that turns out to be a weaker version of the one for block-decomposability. By contrast, we show that general interval-decomposability does not admit such a local characterization, even when locality is understood in a broad sense. Our analysis focuses on the case of modules indexed over finite grids, the more general cases are left as future work.