Generalizations of the Rips filtration for quasi-metric spaces with persistent homology stability results
Generalizations of the Rips filtration for quasi-metric spaces with persistent homology stability results
复制标题
具有持久同源稳定性结果的准度量空间 Rips 过滤的推广
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发表时间:
2016
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通讯作者:
Katharine Turner
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作者:
Katharine Turner
Rips filtrations over a finite metric space and their corresponding persistent homology are prominent methods in Topological Data Analysis to summarize the "shape" of data. Crucial to their use is the stability result that says if $X$ and $Y$ are finite metric space then the (bottleneck) distance between persistence diagrams, barcodes or persistence modules constructed by the Rips filtration is bounded by $2d_{GH}(X,Y)$ (where $d_{GH}$ is the Gromov-Hausdorff distance). Using the asymmetry of the distance function we construct four different constructions analogous to the Rips filtration that capture different information about the quasi-metric spaces. The first method is a one-parameter family of objects where, for a quasi-metric space $X$ and $a\in [0,1]$, we have a filtration of simplicial complexes $\{\mathcal{R}^a(X)_t\}_{t\in [0,\infty)}$ where $\mathcal{R}^a(X)_t$ is clique complex containing the edge $[x,y]$ whenever $a\min \{d(x,y), d(y,x) \}+ (1-a)\max \{d(x,y), d(y,x)\}\leq t$. The second method is to construct a filtration $\{\mathcal{R}^{dir}(X)_t\}$ of ordered tuple complexes where tuple $(x_0, x_2, \ldots x_p)\in \mathcal{R}^{dir}(X)_t$ if $d(x_i, x_j)\leq t$ for all $i\leq j$. Both our first two methods agree with the normal Rips filtration when applied to a metric space. The third and fourth methods use the associated filtration of directed graphs $\{D(X)_t\}$ where $x\to y$ is included in $D(X)_t$ when $d(x,y)\leq t$. Our third method builds persistence modules using the the connected components of the graphs $D(X)_t$. Our fourth method uses the directed graphs $D_t$ to create a filtration of posets (where $x\leq y$ if there is a path from $x$ to $y$) and corresponding persistence modules using poset topology.