Speaker
Mr
Bart Olsthoorn
( NORDITA - Nordic Institute for Theoretical Physics)
Description
Persistent homology (PH) is a relatively new method from algebraic topology that can be used to find features in discrete datasets. The PH algorithms are distributed in a number of popular Python packages, making it easy to start with data analysis. We have shown that this method is useful in Monte Carlo simulations of Heisenberg spins and can reveal the phase diagram. The barcode (a concept in PH) visualizes at which length scales the data has interesting features. The method also has applicability for experimental data, such as post processing the neutron count rate.
| Scientist Profile | I am a PhD student |
|---|
Primary authors
Mr
Bart Olsthoorn
( NORDITA - Nordic Institute for Theoretical Physics)
Johan Hellsvik
Prof.
Alexander Balatsky
( NORDITA - Nordic Institute for Theoretical Physics)
