We present a quantum Monte Carlo-based approach to detect and compute the most dominant correlations for many-body systems without prior knowledge. It is based on the measurement and analysis of the correlation density matrix between two (small) subsystems embedded in the full (large) sample. In order to benchmark this procedure, we investigate zero-temperature quantum phase transitions in one- and two-dimensional quantum Ising model as well as the two-dimensional bilayer Heisenberg antiferromagnet. The method paves the way for a systematic identification of unknown or exotic order parameters in unexplored phases on large systems accessible to quantum Monte Carlo methods.
Detecting the Largest Correlations using the Correlation Density Matrix: a Quantum Monte Carlo Approach
Aditya Chincholi,Sylvain Capponi,F. Alet
Published 2025 in Unknown venue
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2025
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Unknown venue
- Publication date
2025-07-29
- Fields of study
Physics
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