All posts by Mikael Vejdemo-Johansson

ATMCS 6: Day 1

Day 1 of ATMCS 6 is now (mostly) over. Small groups of applied topologists are roaming the streets of Vancouver looking for sights, food or drink, while the less hardy of us have already eaten and retired to our rooms for a quiet night, or a night full of last-minute preparations.

Vin de Silva talked about his currently ongoing research into interesting new perspectives on persistence stability theorems and foundational models for persistence modules. One thing that really caught my attention was the idea of metric certificates: many metrics are defined as the supremum or infimum over a range of potential comparison points. The certificates idea summarizes all these approaches under a common header - a comparison point is a certificate, and the metric is produced by optimizing across certificates.

This is put to use to produce extension theorems of the form
If A is a subspace of B, and there is a 1-Lipschitz map A \to M, then we can construct a 1-Lipschitz map B \toM.
These theorems turn out to hold in a bunch of situations, and to be highly relevant for persistent homology.

Amit Patel talked about his work on Quillen 2-categories and their relationship to persistent homology. It turns out there are ways of talking about persistent homology that pull in some sheaf-theoretic perspectives and naturally produce a Quillen 2-category that encodes much of the structure.

Sarah Day talked about Conley index theory and symbolic dynamics; with some research geared towards using symbolic dynamics approximations of dynamical systems to discover models and pick out cycles and stable behaviors. Within this project, Conley indices turn out to be useful tools.

Tamal Dey talked about the Graph induced complex, and work with Fengtao Fan and Yusu Wang on data sparsification by building topological models and simplifying the computational complexity of generating topological inferences.

I'll see if I can recruit volunteers from the audience to keep a stream of conference updates flowing here.

ATMCS 6 open for registration


Algebraic Topology- Methods, Computation and Science 6 (ATMCS6) is now open for registration. The conference takes place at PIMS University of British Columbia May 26-30.

Confirmed speakers include:

Amit Patel
Donald Sheehy
Jeff Erickson
Jose Perea
Liz Munch
Michael Robinson
Omer Bobrowski
Peter Bubenik
Radmilla Sazdanovic
Sayan Mukerjhee
Vanessa Robbins
Yuliy Baryshnikov
Tamal Dey
Shmuel Weinberger
Raul Rabadan
Chris Hoffman
Vin de Silva

For more details, see:

Applied and computational topology refers to the adaptation of topological ideas and techniques to study problems in science and engineering. A particular focus is on using invariants and methods of algebraic topology to understand large high-dimensional data sets. The further development of topological techniques for use in applications and the creation of new areas of application in the subject are amongst the goals of this workshop.

The workshop will bring together leading researchers in this emerging discipline as well as providing an opportunity for young mathematicians to get involved in it. In past years, the ATMCS conference has been very successful in providing a forum for cutting-edge research to be disseminated; attendance tends to represent a broad swath of the diverse research community which works in this area.

Workshop Format:
The workshop will feature lectures and discussion in the morning and afteroon. Mid-Morning and Afternoon refreshments will be provided during the conference.

On behalf of the organizers
Andrew Blumberg, U Texas
Matthew Kahle, Ohio State
Mikael Vejdemo-Johansson, KTH / IMA / IJS

Source material for Topological Data Analysis

To start off the feature articles at, I figured it might be worth while collecting good entry points to the field. One of the most common questions I get about persistent homology and topological data analysis is how to get started with our techniques and ideas.

Overview articles and books

First off in the list of entry points is the written word. There are survey articles, overview articles and books written about topological data analysis as a whole, as well as focusing on specific parts.

Topology and Data by Gunnar Carlsson. This survey article came soon after Ghrist's survey, and covers persistent homology, as well as Mapper for topological simplification and modeling. It also comes with a good discussion of the underlying philosophy of the field.
Start here.

Barcodes: the persistent topology of data by Robert Ghrist. This is the first major survey article to come out, and covers persistent homology and some of its applications.

Topology for computing by Afra Zomorodian. This is the first book format exposition of persistent homology for applied and computational topology. It is a good and self-contained introduction to the field, if ever so slightly dated: in particular, it does not cover anything about zigzag persistence or multi-dimensional persistence.

Computational Topology: an introduction by Herbert Edelsbrunner and John Harer. This book covers the state of the art as of 2010 of computational topology, with some focus on persistent homology: one third of the book is devoted to persistence and its applications. Throughout, the book discusses the underlying theory, the most obvious algorithm, and the fastest known algorithm.

Software packages

So you understand what the underlying ideas of the field are. Next up, you'll want to try them out on your own data. There are some ways you can go to do this, and they all have their specific strengths and weaknesses.

Plex, jPlex, javaPlex: this sequence of libraries were developed in the Stanford group, and with an explicit aim at always interoperating smoothly and easily with Matlab. Of the three, we currently recommend javaPlex unless this library does not cover your exact use case — in which case some methods may exist in jPlex. Plex is written in C++, and connects to Matlab through a MEX interface, while jPlex and javaPlex are both Java libraries.

Dionysus: this library, written and maintained by Dmitriy Morozov, provides a platform for developing and experimenting with computational topology algorithms in C++ or in Python. It interfaces with CGAL for low dimensional geometric constructions, and has example applications provided for persistent homology, cohomology, vineyards, alphashapes and numerous other common techniques.

Perseus: this package, developed by Vidit Nanda, provides a platform for computing persistent homology for cubical and simplicial complexes generated in a number of different ways. It specifically uses methods based on discrete morse theory for speeding up computations.

pHat: this package, created by Ulrich Bauer, Michael Kerber and Jan Reininghaus builds on results by the authors that speeds up persistence computation by specific tricks that use structures in a persistence boundary matrix. Currently only using Z/2-coefficients and not constructing the complex for you, it seems to be the fastest publicly available package.

CHomP: this software package came out of the CHomP research project, and consists of a rich collection of tools to work persistently or statically with cubical complex data. For homology on image or voxel collection data, CHomP forms the fastest and most complete analysis system available right now.

We warmly appreciate suggestions for more papers, software, or other resources if you have anything to add to this list.

Move of the site

After over a year of mostly inactivity, we have moved platform: away from and to a WebFaction-based server. Kudos to Ryan Lewis for taking over hosting.

In addition to Mikael and Ryan, we would like to invite more members of the community to help build up to a good gathering point for the community of applied and computational topology. If you want to help out, or have opinions on what should be done, drop us an email at and we'll work it all out.