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Superadiabatic dynamical density functional study of Brownian hard-spheres in time-dependent external potentials
S M Tschopp1, H D Vuijk2, J M Brader1
1Department of Physics, University of Fribourg, CH-1700 Fribourg, Switzerland.
Superadiabatic dynamical density functional theory (superadiabatic-DDFT) accurately predicts how interacting particles respond to external forces. This first-principles method bypasses simulations and parameters for reliable dynamics predictions.
Area of Science:
- Statistical Mechanics
- Computational Physics
- Soft Matter Physics
Background:
- Understanding the dynamics of interacting particles is crucial in condensed matter physics.
- Traditional methods often require extensive simulations or adjustable parameters.
- Dynamical density functional theory (DDFT) offers a promising first-principles approach.
Purpose of the Study:
- To investigate the response of interacting Brownian particles to time-dependent external driving using superadiabatic-DDFT.
- To directly predict the dynamics of the one-body density from interparticle interactions.
- To compare superadiabatic-DDFT predictions with adiabatic DDFT and Brownian dynamics simulations.
Main Methods:
- Employed superadiabatic dynamical density functional theory (superadiabatic-DDFT), a first-principles approach.
- Utilized inhomogeneous two-body correlation functions to model particle interactions.
- Investigated external potentials designed to probe structural relaxation in dense liquids.
Main Results:
- Superadiabatic-DDFT accurately predicts the time-evolution of the one-body density for interacting Brownian particles.
- Predictions were made directly from interparticle interactions, without adjustable parameters or simulation input.
- Nonequilibrium density profiles from superadiabatic-DDFT showed good agreement with simulation data.
Conclusions:
- Superadiabatic-DDFT is a reliable and efficient first-principles method for studying nonequilibrium dynamics.
- The theory accurately captures the response of interacting particle systems to external driving.
- This approach provides a parameter-free alternative to traditional simulation methods.
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