Center for Advanced Intelligence Project

Speaker: Kei Hagihara

Date and Time: 11th July 2019, 13:00 – 14:00 + 30min.

Place: Keio University, Yagami-campus Bldg.14th, Room 631 A/B

Title: A derived isometry theorem of Berkouk-Ginot

Abstract: To define a good distance between “topological datasets” is
one of the most important themes in topological data analysis.

With this motivation, Kashiwara and Schapira introduced the convolution distance
between complexes of sheaves with the language of sheaves and derived categories,
in the paper “Persistent homology and microlocal sheaf theory”.

In this talk, we give an overview of Berkouk-Ginot’s preprint
“A derived isometry theorem for sheaves”(arXiv: 1805:09694),
where they give an explicit way for the computations of the convolution distance

in terms of the combinatorial objects called “graded barcodes”.

If you are interested, please feel free to join.

Best regards,
Kei Hagihara