nve_step¶
- torch_sim.integrators.nve.nve_step(state, model, *, dt, **_kwargs)[source]¶
Perform one complete NVE (microcanonical) integration step.
This function implements the velocity Verlet algorithm for NVE dynamics, which provides energy-conserving time evolution. The integration sequence is: 1. Half momentum update using current forces 2. Full position update using updated momenta 3. Force update at new positions 4. Half momentum update using new forces
- Parameters:
model (ModelInterface) – Neural network model that computes energies and forces. Must return a dict with ‘energy’ and ‘forces’ keys.
state (MDState) – Current system state containing positions, momenta, forces
dt (Tensor) – Integration timestep, either scalar or shape [n_systems]
_kwargs (Any)
- Returns:
- Updated state after one complete NVE step with new positions,
momenta, forces, and energy
- Return type:
Notes
Uses velocity Verlet algorithm for time reversible integration
Conserves energy in the absence of numerical errors
Handles periodic boundary conditions if enabled in state
Symplectic integrator preserving phase space volume