1,257 research outputs found
Computing Topological Persistence for Simplicial Maps
Algorithms for persistent homology and zigzag persistent homology are
well-studied for persistence modules where homomorphisms are induced by
inclusion maps. In this paper, we propose a practical algorithm for computing
persistence under coefficients for a sequence of general
simplicial maps and show how these maps arise naturally in some applications of
topological data analysis.
First, we observe that it is not hard to simulate simplicial maps by
inclusion maps but not necessarily in a monotone direction. This, combined with
the known algorithms for zigzag persistence, provides an algorithm for
computing the persistence induced by simplicial maps.
Our main result is that the above simple minded approach can be improved for
a sequence of simplicial maps given in a monotone direction. A simplicial map
can be decomposed into a set of elementary inclusions and vertex collapses--two
atomic operations that can be supported efficiently with the notion of simplex
annotations for computing persistent homology. A consistent annotation through
these atomic operations implies the maintenance of a consistent cohomology
basis, hence a homology basis by duality. While the idea of maintaining a
cohomology basis through an inclusion is not new, maintaining them through a
vertex collapse is new, which constitutes an important atomic operation for
simulating simplicial maps. Annotations support the vertex collapse in addition
to the usual inclusion quite naturally.
Finally, we exhibit an application of this new tool in which we approximate
the persistence diagram of a filtration of Rips complexes where vertex
collapses are used to tame the blow-up in size.Comment: This is the revised and full version of the paper that is going to
appear in the Proceedings of 30th Annual Symposium on Computational Geometr
Linear-Size Approximations to the Vietoris-Rips Filtration
The Vietoris-Rips filtration is a versatile tool in topological data
analysis. It is a sequence of simplicial complexes built on a metric space to
add topological structure to an otherwise disconnected set of points. It is
widely used because it encodes useful information about the topology of the
underlying metric space. This information is often extracted from its so-called
persistence diagram. Unfortunately, this filtration is often too large to
construct in full. We show how to construct an O(n)-size filtered simplicial
complex on an -point metric space such that its persistence diagram is a
good approximation to that of the Vietoris-Rips filtration. This new filtration
can be constructed in time. The constant factors in both the size
and the running time depend only on the doubling dimension of the metric space
and the desired tightness of the approximation. For the first time, this makes
it computationally tractable to approximate the persistence diagram of the
Vietoris-Rips filtration across all scales for large data sets.
We describe two different sparse filtrations. The first is a zigzag
filtration that removes points as the scale increases. The second is a
(non-zigzag) filtration that yields the same persistence diagram. Both methods
are based on a hierarchical net-tree and yield the same guarantees
Approximating Persistent Homology in Euclidean Space Through Collapses
The \v{C}ech complex is one of the most widely used tools in applied
algebraic topology. Unfortunately, due to the inclusive nature of the \v{C}ech
filtration, the number of simplices grows exponentially in the number of input
points. A practical consequence is that computations may have to terminate at
smaller scales than what the application calls for.
In this paper we propose two methods to approximate the \v{C}ech persistence
module. Both are constructed on the level of spaces, i.e. as sequences of
simplicial complexes induced by nerves. We also show how the bottleneck
distance between such persistence modules can be understood by how tightly they
are sandwiched on the level of spaces. In turn, this implies the correctness of
our approximation methods.
Finally, we implement our methods and apply them to some example point clouds
in Euclidean space
Algebraic Topology
The chapter provides an introduction to the basic concepts of Algebraic
Topology with an emphasis on motivation from applications in the physical
sciences. It finishes with a brief review of computational work in algebraic
topology, including persistent homology.Comment: This manuscript will be published as Chapter 5 in Wiley's textbook
\emph{Mathematical Tools for Physicists}, 2nd edition, edited by Michael
Grinfeld from the University of Strathclyd
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