Optimizing active work: Dynamical phase transitions, collective motion, and jamming.

Area of Science:

• Physics of active matter
• Statistical mechanics
• Complex systems

Background:

• Active work quantifies the relationship between self-propulsion and resultant motion in active particles.
• Understanding collective behaviors and phase transitions in active systems is crucial for designing novel materials and understanding biological processes.

Purpose of the Study:

• To investigate the large deviations in active work for repulsive active Brownian disks.
• To identify the conditions leading to dynamical arrest versus collective motion in active particle systems.

Main Methods:

• Population Monte Carlo simulations were employed to study the system's behavior.
• Heuristic and analytical arguments were used to explain observed phenomena.

Main Results:

• Minimizing active work typically results in dynamical arrest.
• High active work trajectories correspond to a collectively moving and aligned state, even without aligning interactions.
• Dynamical phase transitions were identified, separating arrested, typical, and aligned regimes.

Conclusions:

• Active work serves as a key indicator of emergent collective behavior in active particle systems.
• The study reveals a mechanism for self-organization and collective motion driven by active work, independent of explicit aligning forces.