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Quantum Thermodynamics
Learning phase transitions in ferrimagnetic GdFeCo alloys
arXiv
Authors: N. A. Koritsky, S. V. Solov'yov, A. K. Fedorov, A. K. Zvezdin
Year
2020
Paper ID
19847
Status
Preprint
Abstract Read
~2 min
Abstract Words
110
Citations
N/A
Abstract
We present results on the identification of phase transitions in ferrimagnetic GdFeCo alloys using machine learning. The approach for finding phase transitions in the system is based on the `learning by confusion' scheme, which allows one to characterize phase transitions using a universal W-shape. By applying the `learning by confusion' scheme, we obtain 2D W-a shaped surface that characterizes a triple phase transition point of the GdFeCo alloy. We demonstrate that our results are in the perfect agreement with the procedure of the numerical minimization of the thermodynamical potential, yet our machine-learning-based scheme has the potential to provide a speedup in the task of the phase transition identification.
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- This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
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- We present results on the identification of phase transitions in ferrimagnetic GdFeCo alloys using machine learning.
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