Description
We consider computer generated configurations of quantized vortices in planar superfluid Bose–Einstein condensates. We show that unsupervised machine learning technology can successfully be used for classifying such vortex configurations to identify prominent vortex phases of matter [1]. The machine learning approach could thus be applied for automatically classifying large data sets of vortex on figurations obtainable by experiments on two-dimensional quantum turbulence.
[1] R. Sharma and T.P. Simula, Machine-learning classification of two-dimensional
vortex configurations, Physical Review A, 105, 033301 (2022).
| Presenter name | RAMA SHARMA |
|---|
Primary authors
Mrs
RAMA SHARMA
(THE SWINBURNE UNIVERSITY OF TECHNOLOGY)
Prof.
TAPIO SIMULA
(The SWINBURNE UNIVERSITY OF TECHNOLOGY)
