Anomalous Directed Percolation on a Dynamic Network Using Rydberg Facilitation

Area of Science:

• Atomic physics
• Complex systems
• Statistical mechanics

Background:

• Rydberg excitations in atomic gases offer a unique model for studying complex phenomena.
• Understanding epidemic evolution on dynamic networks and self-organization is crucial for complex systems research.

Purpose of the Study:

• To investigate the universality class of nonequilibrium phase transitions in Rydberg-excited atomic gases.
• To determine if the universality class can be tuned and its robustness against decay.

Main Methods:

• Monte Carlo simulations were employed to model the system.
• A machine learning algorithm was utilized to analyze the simulation data.
• The study considered both static (frozen gas) and dynamic (moving atoms) network scenarios.

Main Results:

• The universality class of the phase transition can be tuned and is robust against decay.
• In a frozen gas, directed percolation (DP) universality was predicted.
• Atomic motion and long-range excitations lead to anomalous directed percolation (ADP) with continuously varying critical exponents.
• These results explain recent experimental observations of Rydberg facilitation.

Conclusions:

• Rydberg excitation systems provide a versatile platform for studying critical phenomena and self-organization.
• The findings demonstrate the tunability and robustness of universality classes in dynamic networks.
• The study bridges theoretical models with experimental observations in ultracold atomic gases.