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| + | <p>A model category of tame parametrised chain complexes <br> | ||
| + | Barbara Giunti (University of Modena) </p> | ||
| + | <p> Tue, July 7th, 16-18h <br> | ||
| + | Zoom <small>([mailto:structures-hiwi@mathi.uni-heidelberg.de email us for ])</small><br> </p> | ||
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| + | <b>Abstract:</b> Persistent theory is a useful tool to extract information from real-world data sets, and profits of techniques from different mathematical disciplines, such as Morse theory and quiver representation. In this seminar, I am going to present a new approach for studying persistence theory using model categories. I will briefly introduce model categories and then describe how to define a model structure on the category of the tame parametrised chain complexes, which are chain complexes that evolve in time, describing why such an approach can be useful in topological data analysis. In particular, I will use the model category structure to retrieve two invariants that extract homotopical and homological information from any tame parametrised chain complex. | ||
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Revision as of 08:52, 2 July 2020
A model category of tame parametrised chain complexes
Barbara Giunti (University of Modena)
Tue, July 7th, 16-18h
Zoom (email us for )
Barbara Giunti (University of Modena)
Zoom (email us for )
Abstract: Persistent theory is a useful tool to extract information from real-world data sets, and profits of techniques from different mathematical disciplines, such as Morse theory and quiver representation. In this seminar, I am going to present a new approach for studying persistence theory using model categories. I will briefly introduce model categories and then describe how to define a model structure on the category of the tame parametrised chain complexes, which are chain complexes that evolve in time, describing why such an approach can be useful in topological data analysis. In particular, I will use the model category structure to retrieve two invariants that extract homotopical and homological information from any tame parametrised chain complex.