Simplified Molecular Dynamics Simulation in Python

The following code implements a simplified molecular dynamics simulation in Python.

Constants

The simulation includes the following constants:

  • mass: Mass of the particles in the system.
  • dt: Time step size that determines the interval at which the simulation progresses.
  • steps: Total number of simulation steps to perform.

Initial Positions and Velocities

The initial positions and velocities of the particles are represented by numpy arrays:

  • positions: Numpy array representing the initial positions of the particles in the system.
  • velocities: Numpy array representing the initial velocities of the particles.

Force Calculation

The code includes a calculate_forces function that calculates the forces acting between particles based on their positions. The forces are stored in a numpy array called forces. Please note that the implementation of the force calculation and interaction potential is not provided in this simplified example.

Molecular Dynamics Simulation

The simulation loop iterates over the specified number of steps. Within each step:

  • Forces are calculated by calling the calculate_forces function, passing the current positions of the particles.
  • Particle positions and velocities are updated using the equations of motion.
  • Additional tasks or calculations specific to the simulation can be included within the loop.
  • Information about the current step number and particle positions is printed.
  • Post-simulation Analysis
  • After the simulation loop, additional analysis or visualization based on the simulation results can be performed.

Please note that this code serves as a basic demonstration and should not be used for complex or realistic simulations. For more accurate and advanced molecular dynamics simulations, specialized software packages like GROMACS, NAMD, or LAMMPS are recommended.

import numpy as np

# Constants
mass = 1.0
dt = 0.001
steps = 1000

# Initial positions and velocities
positions = np.array([[0.0, 0.0, 0.0],
                     [1.0, 0.0, 0.0]])
velocities = np.array([[0.0, 0.0, 0.0],
                       [0.0, 1.0, 0.0]])

# Force calculation
def calculate_forces(positions):
    forces = np.zeros_like(positions)
    # Implement force calculation based on the interaction potential
    # This can be a simplified potential function for demonstration purposes
    return forces

# Molecular dynamics simulation
for step in range(steps):
    # Calculate forces
    forces = calculate_forces(positions)
    
    # Update positions and velocities
    positions += velocities * dt + 0.5 * forces * dt**2
    velocities += forces * dt / mass
    
    # Perform additional tasks at each step if needed

    # Output information
    print(f"Step: {step+1}, Positions: {positions}")

# Additional post-simulation analysis or visualization can be done here