TY  - JOUR
PB  - SciPost Foundation
DO  - 10.21468/SciPostPhysCore.8.1.029
TI  - Identifying quantum phase transitions with minimal prior knowledge by unsupervised learning
PY  - 2025/03/06
UR  - https://www.scipost.org/SciPostPhysCore.8.1.029
JF  - SciPost Physics Core
JA  - SciPost Phys. Core
VL  - 8
IS  - 1
SP  - 029
A1  - Marashli, Mohamad Ali
AU  - Ho Lai, Henry Lam
AU  - Mokayed, Hamam
AU  - Sandin, Fredrik
AU  - Liwicki, Marcus
AU  - Tang, Ho-Kin
AU  - Yu, Wing Chi
AB  - In this work, we proposed a novel approach for identifying quantum phase transitions in one-dimensional quantum many-body systems using AutoEncoder (AE), an unsupervised machine learning technique, with minimal prior knowledge. The training of the AEs is done with reduced density matrix (RDM) data obtained by Exact Diagonalization (ED) across the entire range of the driving parameter and thus no prior knowledge of the phase diagram is required. With this method, we successfully detect the phase transitions in a wide range of models with multiple phase transitions of different types, including the topological and the Berezinskii-Kosterlitz-Thouless transitions by tracking the changes in the reconstruction loss of the AE. The learned representation of the AE is used to characterize the physical phenomena underlying different quantum phases. Our methodology demonstrates a new approach to studying quantum phase transitions with minimal knowledge, small amount of needed data, and produces compressed representations of the quantum states.
ER  -

@Article{10.21468/SciPostPhysCore.8.1.029,
	title={{Identifying quantum phase transitions with minimal prior knowledge by unsupervised learning}},
	author={Mohamad Ali Marashli and Ho Lai Henry Lam and Hamam Mokayed and Fredrik Sandin and Marcus Liwicki and Ho-Kin Tang and Wing Chi Yu},
	journal={SciPost Phys. Core},
	volume={8},
	pages={029},
	year={2025},
	publisher={SciPost},
	doi={10.21468/SciPostPhysCore.8.1.029},
	url={https://scipost.org/10.21468/SciPostPhysCore.8.1.029},
}