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Benjamin Schweinhart

Publications and source records attributed to Benjamin Schweinhart.

24 records · Page 2Linked to original sources

Persistent Homology and the Upper Box Dimension

We introduce a fractal dimension for a metric space defined in terms of the persistent homology of extremal subsets of that space. We exhibit hypotheses under which this dimension is comparable to the upper box dimension; in particular, the dimensions coincide for subsets of $\mathbb{R}^2$ whose upper box dimension exceeds $1.5.$ These results are related to extremal questions about the number of persistent homology intervals of a set of $n$ points in a metric space.

math.MG↗

Weighted Persistent Homology Sums of Random Čech Complexes

We study the asymptotic behavior of random variables of the form \begin{equation*} E_α^i\left(x_1,\ldots,x_n\right)=\sum_{\left(b,d\right)\in \mathit{PH}_i\left(x_1,\ldots,x_n\right)} \left(d-b\right)^α \end{equation*} where $\left\{x_j\right\}_{j\in\mathbb{N}}$ are i.i.d. samples from a probability measure on a triangulable metric space, and $\textit{PH}_i\left(x_1,\ldots,x_n\right)$ denotes the $i$-dimensional reduced persistent homology of the Čech complex of $\left\{x_1,\ldots,x_n\right\}.$ These quantities are a higher-dimensional generalization of the $α$-weighted sum of a minimal spanning tree; we seek to prove analogues of the theorems of Steele (1988) and Aldous and Steele (1992) in this context. As a special case of our main theorem, we show that if $\left\{x_j\right\}_{j\in\mathbb{N}}$ are distributed independently and uniformly on the $m$-dimensional Euclidean sphere, $α<m,$ and $0\leq i <n,$ then there are real numbers $γ$ and $Γ$ so that \begin{equation*} γ\leq \lim_{n\rightarrow\infty} n^{-\frac{m-α}{m}} E_i^α\left(x_1,\ldots,x_n\right) \leq Γ\end{equation*} in probability. More generally, we prove results about the asymptotics of the expectation of $E_α^i$ for points sampled from a locally bounded probability measure on a space that is the bi-Lipschitz image of an $m-$dimensional Euclidean simplicial complex, as well as measures supported on sets of fractional dimension that respect box counting.

math.PR↗

Limits of Embedded Graphs, and Universality Conjectures for the Network Flow

We define notions of local topological convergence and local geometric convergence for embedded graphs in $\mathbb{R}^n,$ and study their properties. The former is related to Benjamini-Schramm convergence, and the latter to weak convergence of probability measures with respect to a certain topology on the space of embedded graphs. These are used to state universality conjectures for the long-term behavior of the network flow, or curvature flow on embedded graphs. To provide evidence these conjectures, we develop and apply computational methods to test for local topological and local geometric convergence.

math.PR↗

Topological Similarity of Random Cell Complexes and Applications

Although random cell complexes occur throughout the physical sciences, there does not appear to be a standard way to quantify their statistical similarities and differences. The various proposals in the literature are usually motivated by the analysis of particular physical systems and do not necessarily apply to general situations. The central concepts in this paper---the swatch and the cloth---provide a description of the local topology of a cell complex that is general (any physical system that may be represented as a cell complex is admissible) and complete (any statistical question about the local topology may be answered from the cloth). Furthermore, this approach allows a distance to be defined that measures the similarity of the local topology of two cell complexes. The distance is used to identify a steady state of a model dislocation network evolving by energy minimization, and then to rigorously quantify the approach of the simulation to this steady state.

cs.CG↗

Multiscale Topology of Chromatin Folding

The three dimensional structure of DNA in the nucleus (chromatin) plays an important role in many cellular processes. Recent experimental advances have led to high-throughput methods of capturing information about chromatin conformation on genome-wide scales. New models are needed to quantitatively interpret this data at a global scale. Here we introduce the use of tools from topological data analysis to study chromatin conformation. We use persistent homology to identify and characterize conserved loops and voids in contact map data and identify scales of interaction. We demonstrate the utility of the approach on simulated data and then look data from both a bacterial genome and a human cell line. We identify substantial multiscale topology in these datasets.

q-bio.GN↗

Measuring Shape with Topology

We propose a measure of shape which is appropriate for the study of a complicated geometric structure, defined using the topology of neighborhoods of the structure. One aspect of this measure gives a new notion of fractal dimension. We demonstrate the utility and computability of this measure by applying it to branched polymers, Brownian trees, and self-avoiding random walks.

math.AT↗