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Active Ornstein-Uhlenbeck particle under stochastic resetting
Uma Shankari1, Deion Santhosh1, Mamata Sahoo1
1Department of Physics, University of Kerala, Kariavattom, Thiruvananthapuram 695581, India.
Summary
Stochastic resetting of active particles can enhance target search by increasing exploration. This study reveals how particle activity and viscoelasticity influence this enhanced search, with implications for understanding complex system dynamics.
Area of Science:
- Statistical Mechanics
- Soft Matter Physics
- Non-equilibrium Systems
Background:
- Active particles exhibit self-propulsion, leading to unique dynamic behaviors.
- Stochastic resetting introduces periodic re-localization, altering particle trajectories.
- Understanding particle dynamics in complex media like viscoelastic fluids is crucial for various applications.
Purpose of the Study:
- To investigate the dynamics of an inertial active Ornstein-Uhlenbeck particle under stochastic resetting.
- To analyze the influence of resetting rate, activity duration, and viscoelasticity on particle motion.
- To determine conditions that enhance a particle's ability to explore its environment.
Main Methods:
- Utilized the renewal approach for analytical calculations.
- Computed mean square displacement (MSD) and position probability distribution functions.
- Performed numerical simulations to validate analytical findings.
Main Results:
- Steady-state MSD is suppressed by increasing resetting rate but non-monotonically affected by activity duration.
- Intermediate activity timescales enhance steady-state MSD, promoting wider exploration.
- Viscoelasticity introduces an intermediate-time plateau in MSD, dependent on viscoelasticity strength and relaxation time.
Conclusions:
- Stochastic resetting and particle activity significantly impact steady-state dynamics.
- Optimal activity timescales can enhance target search efficiency.
- Viscoelasticity introduces memory effects that modify particle exploration, with resetting potentially overcoming these effects.
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