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Updated: Oct 14, 2025

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Published on: February 4, 2017
Direction reversing active Brownian particle in a harmonic potential.
Ion Santra1, Urna Basu1,2, Sanjib Sabhapandit1
1Raman Research Institute, Bengaluru 560080, India.
We identified four distinct phases in active Brownian particle motion within a harmonic trap, driven by rotational diffusion, reversal rate, and trap strength. These phases, active-I/II and passive-I/II, exhibit unique positional distributions.
Area of Science:
- Soft Matter Physics
- Statistical Mechanics
- Non-Equilibrium Systems
Background:
- Active Brownian particles exhibit complex dynamics due to self-propulsion and rotational diffusion.
- Confining potentials, like harmonic traps, influence the spatial distribution of active particles.
- Directional reversals introduce intermittent behavior, further modifying steady-state properties.
Purpose of the Study:
- To investigate the steady-state positional distributions of a driven active Brownian particle in a 2D harmonic trap.
- To identify and characterize distinct phases arising from the interplay of rotational diffusion, reversal rate, and trap strength.
- To analytically and numerically explore the phase transitions and their underlying mechanisms.
Main Methods:
- Analytical calculations of steady-state distributions in limiting cases.
- Characterization of phase shapes: annular, Mexican hat-like, and centrally peaked (Boltzmann and non-Boltzmann).
- Numerical simulations to complement analytical findings and construct a qualitative phase diagram.
Main Results:
- Four distinct phases (active-I/II, passive-I/II) were identified based on the shape of the positional distribution.
- Active-I: Annular distribution; Active-II: Mexican hat-like distribution with a central peak.
- Passive-I: Boltzmann-like central peak; Passive-II: Non-Boltzmann central peak with origin divergence.
- A phase transition from active-II to passive-II occurs at $\mu = \gamma$ for $D_R \ll \gamma$.
Conclusions:
- The interplay between particle activity, diffusion, and confinement leads to rich phase behavior.
- Analytical and numerical methods reveal distinct steady-state distributions and phase transitions.
- A qualitative phase diagram maps the observed phases in parameter space ($D_R$, $\gamma$, $\mu^{-1}$).
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