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Competitive nucleation in reversible probabilistic cellular automata
Emilio N M Cirillo1, Francesca R Nardi, Cristian Spitoni
1Dipartimento Me. Mo. Mat., Università degli Studi di Roma La Sapienza, via A. Scarpa 16, Rome, Italy.
This study examines competitive nucleation using probabilistic cellular automata, revealing a unique metastable phase dependent on magnetic fields and self-interaction. The findings show behaviors analogous to the stochastic Blume-Capel model.
Area of Science:
- Statistical Mechanics
- Computational Physics
- Dynamical Systems
Background:
- Competitive nucleation is a critical phenomenon in phase transitions.
- Probabilistic cellular automata (PCA) offer a framework for modeling complex dynamics.
- Understanding metastability is key to predicting system behavior.
Purpose of the Study:
- To investigate competitive nucleation dynamics within PCA.
- To analyze the influence of self-interaction on metastability.
- To identify emergent phases and their dependence on system parameters.
Main Methods:
- Utilizing a dynamical approach to study PCA.
- Analyzing the interplay between magnetic field and self-interaction.
- Observing system evolution through configurations.
Main Results:
- An intermediate metastable phase was identified.
- This phase consists of two flip-flopping chessboard configurations.
- The phase emergence is contingent on the ratio of magnetic field to self-interaction.
Conclusions:
- The study elucidates a novel metastable phase in PCA.
- The observed behavior parallels that of the stochastic Blume-Capel model with Glauber dynamics.
- Findings contribute to the understanding of nucleation and phase transitions in complex systems.
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