The CUNY Data Science and Applied Topology Reading Group is joint between the Mathematics and Computer Science programmes. We meet Fridays 11.45 -- 12.45 in GC 4419. You can contact us at firstname.lastname@example.org.
Our plan is to primarily read and discuss seminal papers in data science, in applied topology and in topological data analysis. Each seminar one participant takes the responsibility to present a paper and prepare items for discussion. We expect occasionally to be able to invite external speakers.
SEMINAR CANCELLED FOR SPRING 2020
With the fast developing situation around CUNY and NYCs reactions to the Coronavirus, we have decided to cancel the Data Science and Applied Topology seminar for the remainder of the spring semester 2020.
We expect to welcome you back for the fall seminar early September.
Current schedule can be found here.
We will be sending out announcements through a mailing list; you can subscribe here.
- Mikael Vejdemo-Johansson, Computer Science Programme, CUNY Graduate Center; Department of Mathematics, CUNY College of Staten Island
- Azita Mayeli, Mathematics Programme, CUNY Graduate Center; Department of Mathematics, CUNY Queensborough Community College
We have compiled a list of papers that might be interesting to present.
Treewidth and metric complexity for hyperbolic 3-manifolds
Treewidth is an invariant of graphs which measures how close a graph is to being a tree. A number of algorithms that are exponential over all graphs are polynomial over graphs of bounded tree width. The treewidth of a 3-manifold is the minimal treewidth of the dual graph of any triangulation of the manifold. A number of 3-manifold invariants which are exponential in the number of tetrahedra are polynomial for manifolds of bounded treewidth, for example, the Turaev-Viro invariants. We show that for hyperbolic 3-manifolds, treewidth is linearly related to a metric complexity defined in terms of Morse functions to trees. In particular, this shows that there are 3-manifolds of arbitrarily large treewidth. This is joint work with Diane Hoffoss.