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Published in: Foundations of Computational Mathematics 5/2015

01-10-2015

Zigzag Zoology: Rips Zigzags for Homology Inference

Authors: Steve Y. Oudot, Donald R. Sheehy

Published in: Foundations of Computational Mathematics | Issue 5/2015

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Abstract

For \(n\) points sampled near a compact set \(X\), the persistence barcode of the Rips filtration built from the sample contains information about the homology of \(X\) as long as \(X\) satisfies some geometric assumptions. The Rips filtration is prohibitively large; however, zigzag persistence can be used to keep the size linear in \(n\), with a constant factor depending only (exponentially) on the intrinsic dimension of \(X\). We present several species of Rips-like zigzags and compare them with respect to the signal-to-noise ratio, a measure of how well the underlying homology is represented in the persistence barcode relative to the noise in the barcode at the relevant scales. Some of these Rips-like zigzags have been available as part of the Dionysus library for several years while others are new. Interestingly, we show that some species of Rips zigzags will exhibit less noise than the (nonzigzag) Rips filtration itself. Thus, Rips zigzags can offer improvements in both size complexity and signal-to-noise ratio. Along the way, we develop new techniques for manipulating and comparing persistence barcodes from zigzag modules. In particular, we give methods for reversing arrows and removing spaces from a zigzag while controlling the changes occurring in its barcode. These techniques were developed to provide our theoretical analysis of the signal-to-noise ratio of Rips-like zigzags, but they are of independent interest as they apply to zigzag modules generally.

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Appendix
Available only for authorised users
Footnotes
1
See, for example, [13] for a proof. Our definition of the Rips complex differs from that in [13] by a factor of two in the parameter value. This explains the slight discrepancy between our chain of inclusions and the one in [13].
 
2
We are in fact using an extended version of the Persistent Nerve Lemma, stated in [9], where the index sets of the open covers may differ.
 
3
Note that we follow [5] and depart from the traditional persistence barcode representation by using closed intervals instead of half-open intervals.
 
4
Arbitrary orderings may lead to local oversampling and thus to an uncontrolled local growth of the complex, regardless of the zigzag considered.
 
5
This idea was suggested in [6], where it led to further tweaking of the data.
 
6
The analysis is even simpler in this case since Čech complexes of a suitable parameter carry the same homological information as \(X\), as opposed to the images of inclusions between Čech complexes.
 
7
With the notable exception of compositions as in Lemma 3.3, which canonically induce a functor.
 
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Metadata
Title
Zigzag Zoology: Rips Zigzags for Homology Inference
Authors
Steve Y. Oudot
Donald R. Sheehy
Publication date
01-10-2015
Publisher
Springer US
Published in
Foundations of Computational Mathematics / Issue 5/2015
Print ISSN: 1615-3375
Electronic ISSN: 1615-3383
DOI
https://doi.org/10.1007/s10208-014-9219-7

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