Multifractal and Network Analysis of Phase Transition

TL;DR

This paper combines multifractal analysis and complex network methods to study magnetization time series near the critical point of the 2D Ising model, providing early warning indicators of phase transitions.

Contribution

It introduces a novel integrated approach using MF-DFA and visibility graphs to analyze phase transitions in complex systems, highlighting early warning indicators.

Findings

Hurst exponent effectively indicates phase transition.

Multifractality increases near critical point.

Network topology metrics serve as early warnings.

Abstract

Many models and real complex systems possess critical thresholds at which the systems shift from one sate to another. The discovery of the early warnings of the systems in the vicinity of critical point are of great importance to estimate how far a system is from a critical threshold. Multifractal Detrended Fluctuation analysis (MF-DFA) and visibility graph method have been employed to investigate the fluctuation and geometrical structures of magnetization time series of two-dimensional Ising model around critical point. The Hurst exponent has been confirmed to be a good indicator of phase transition. Increase of the multifractality of the time series have been observed from generalized Hurst exponents and singularity spectrum. Both Long-term correlation and broad probability density function are identified to be the sources of multifractality of time series near critical regime. Heterogeneous nature of the networks constructed from magnetization time series have validated the fractal properties of magnetization time series from complex network perspective. Evolution of the topology quantities such as clustering coefficient, average degree, average shortest path length, density, assortativity and heterogeneity serve as early warnings of phase transition. Those methods and results can provide new insights about analysis of phase transition problems and can be used as early warnings for various complex systems.