Source code for ase.md.andersen

"""Andersen dynamics class."""
from typing import IO, Optional, Union

from numpy import cos, log, ones, pi, random, repeat

from ase import Atoms, units
from ase.md.md import MolecularDynamics
from ase.parallel import DummyMPI, world


[docs]class Andersen(MolecularDynamics): """Andersen (constant N, V, T) molecular dynamics.""" def __init__( self, atoms: Atoms, timestep: float, temperature_K: float, andersen_prob: float, fixcm: bool = True, trajectory: Optional[str] = None, logfile: Optional[Union[IO, str]] = None, loginterval: int = 1, communicator=world, rng=random, append_trajectory: bool = False, ): """" Parameters: atoms: Atoms object The list of atoms. timestep: float The time step in ASE time units. temperature_K: float The desired temperature, in Kelvin. andersen_prob: float A random collision probability, typically 1e-4 to 1e-1. With this probability atoms get assigned random velocity components. fixcm: bool (optional) If True, the position and momentum of the center of mass is kept unperturbed. Default: True. rng: RNG object (optional) Random number generator, by default numpy.random. Must have a random_sample method matching the signature of numpy.random.random_sample. logfile: file object or str (optional) If *logfile* is a string, a file with that name will be opened. Use '-' for stdout. trajectory: Trajectory object or str (optional) Attach trajectory object. If *trajectory* is a string a Trajectory will be constructed. Use *None* (the default) for no trajectory. communicator: MPI communicator (optional) Communicator used to distribute random numbers to all tasks. Default: ase.parallel.world. Set to None to disable communication. append_trajectory: bool (optional) Defaults to False, which causes the trajectory file to be overwritten each time the dynamics is restarted from scratch. If True, the new structures are appended to the trajectory file instead. The temperature is imposed by stochastic collisions with a heat bath that acts on velocity components of randomly chosen particles. The algorithm randomly decorrelates velocities, so dynamical properties like diffusion or viscosity cannot be properly measured. H. C. Andersen, J. Chem. Phys. 72 (4), 2384–2393 (1980) """ self.temp = units.kB * temperature_K self.andersen_prob = andersen_prob self.fix_com = fixcm self.rng = rng if communicator is None: communicator = DummyMPI() self.communicator = communicator MolecularDynamics.__init__(self, atoms, timestep, trajectory, logfile, loginterval, append_trajectory=append_trajectory) def set_temperature(self, temperature_K): self.temp = units.kB * temperature_K def set_andersen_prob(self, andersen_prob): self.andersen_prob = andersen_prob def set_timestep(self, timestep): self.dt = timestep def boltzmann_random(self, width, size): x = self.rng.random_sample(size=size) y = self.rng.random_sample(size=size) z = width * cos(2 * pi * x) * (-2 * log(1 - y))**0.5 return z def get_maxwell_boltzmann_velocities(self): natoms = len(self.atoms) masses = repeat(self.masses, 3).reshape(natoms, 3) width = (self.temp / masses)**0.5 velos = self.boltzmann_random(width, size=(natoms, 3)) return velos # [[x, y, z],] components for each atom def step(self, forces=None): atoms = self.atoms if forces is None: forces = atoms.get_forces(md=True) self.v = atoms.get_velocities() # Random atom-wise variables are stored as attributes and broadcasted: # - self.random_com_velocity # added to all atoms if self.fix_com # - self.random_velocity # added to some atoms if the per-atom # - self.andersen_chance # andersen_chance <= andersen_prob # a dummy communicator will be used for serial runs if self.fix_com: # add random velocity to center of mass to prepare Andersen width = (self.temp / sum(self.masses))**0.5 self.random_com_velocity = (ones(self.v.shape) * self.boltzmann_random(width, (3))) self.communicator.broadcast(self.random_com_velocity, 0) self.v += self.random_com_velocity self.v += 0.5 * forces / self.masses * self.dt # apply Andersen thermostat self.random_velocity = self.get_maxwell_boltzmann_velocities() self.andersen_chance = self.rng.random_sample(size=self.v.shape) self.communicator.broadcast(self.random_velocity, 0) self.communicator.broadcast(self.andersen_chance, 0) self.v[self.andersen_chance <= self.andersen_prob] \ = self.random_velocity[self.andersen_chance <= self.andersen_prob] x = atoms.get_positions() if self.fix_com: old_com = atoms.get_center_of_mass() self.v -= self._get_com_velocity(self.v) # Step: x^n -> x^(n+1) - this applies constraints if any atoms.set_positions(x + self.v * self.dt) if self.fix_com: atoms.set_center_of_mass(old_com) # recalc velocities after RATTLE constraints are applied self.v = (atoms.get_positions() - x) / self.dt forces = atoms.get_forces(md=True) # Update the velocities self.v += 0.5 * forces / self.masses * self.dt if self.fix_com: self.v -= self._get_com_velocity(self.v) # Second part of RATTLE taken care of here atoms.set_momenta(self.v * self.masses) return forces