In molecular dynamics (MD) simulations, the flying ice cube effect is an artifact in which the energy of high-frequency fundamental modes is drained into low-frequency modes, particularly into zero-frequency motions such as overall translation and rotation of the system. The artifact derives its name from a particularly noticeable manifestation that arises in simulations of particles in vacuum, where the system being simulated acquires high linear momentum and experiences extremely damped internal motions, freezing the system into a single conformation reminiscent of an ice cube or other rigid body flying through space. The artifact is entirely a consequence of molecular dynamics algorithms and is wholly unphysical, since it violates the principle of equipartition of energy. [1]
The flying ice cube artifact arises from repeated rescalings of the velocities of the particles in the simulation system. Velocity rescaling is a means of imposing a thermostat on the system by multiplying the velocities of a system's particles by a factor after an integration timestep is completed, as is done by the Berendsen thermostat and the Bussi–Donadio–Parrinello thermostat. [2] These schemes fail when the rescaling is done to a kinetic energy distribution of an ensemble that is not invariant under microcanonical molecular dynamics; thus, the Berendsen thermostat (which rescales to the isokinetic ensemble) exhibits the artifact, while the Bussi–Donadio–Parrinello [2] thermostat (which rescales to the canonical ensemble) does not exhibit the artifact. Rescaling to an ensemble that is not invariant under microcanonical molecular dynamics results in a violation of the balance condition that is a requirement of Monte Carlo simulations (molecular dynamics simulations with velocity rescaling thermostats can be thought of as Monte Carlo simulations with molecular dynamics moves and velocity rescaling moves), which is the artifact's underlying reason. [3]
When the flying ice cube problem was first found, the Bussi–Donadio–Parrinello [2] thermostat had not yet been developed, and it was desired to continue using the Berendsen thermostat due to the efficiency with which velocity rescaling thermostats relax systems to desired temperatures. Thus, suggestions were given to avoid the flying ice cube effect under the Berendsen thermostat, such as periodically removing the center-of-mass motions and using a longer temperature coupling time. [1] However, more recently it has been recommended that the better practice is to discontinue use of the Berendsen thermostat entirely in favor of the Bussi–Donadio–Parrinello [2] thermostat, as it has been shown that the latter thermostat does not exhibit the flying ice cube effect. [3]
In physics, statistical mechanics is a mathematical framework that applies statistical methods and probability theory to large assemblies of microscopic entities. It does not assume or postulate any natural laws, but explains the macroscopic behavior of nature from the behavior of such ensembles.
Molecular dynamics (MD) is a computer simulation method for analyzing the physical movements of atoms and molecules. The atoms and molecules are allowed to interact for a fixed period of time, giving a view of the dynamic "evolution" of the system. In the most common version, the trajectories of atoms and molecules are determined by numerically solving Newton's equations of motion for a system of interacting particles, where forces between the particles and their potential energies are often calculated using interatomic potentials or molecular mechanical force fields. The method is applied mostly in chemical physics, materials science, and biophysics.
In classical statistical mechanics, the equipartition theorem relates the temperature of a system to its average energies. The equipartition theorem is also known as the law of equipartition, equipartition of energy, or simply equipartition. The original idea of equipartition was that, in thermal equilibrium, energy is shared equally among all of its various forms; for example, the average kinetic energy per degree of freedom in translational motion of a molecule should equal that in rotational motion.
In statistical mechanics, the microcanonical ensemble is a statistical ensemble that represents the possible states of a mechanical system whose total energy is exactly specified. The system is assumed to be isolated in the sense that it cannot exchange energy or particles with its environment, so that the energy of the system does not change with time.
A property of a physical system, such as the entropy of a gas, that stays approximately constant when changes occur slowly is called an adiabatic invariant. By this it is meant that if a system is varied between two end points, as the time for the variation between the end points is increased to infinity, the variation of an adiabatic invariant between the two end points goes to zero.
In physics, Langevin dynamics is an approach to the mathematical modeling of the dynamics of molecular systems. It was originally developed by French physicist Paul Langevin. The approach is characterized by the use of simplified models while accounting for omitted degrees of freedom by the use of stochastic differential equations. Langevin dynamics simulations are a kind of Monte Carlo simulation.
Car–Parrinello molecular dynamics or CPMD refers to either a method used in molecular dynamics or the computational chemistry software package used to implement this method.
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Metadynamics is a computer simulation method in computational physics, chemistry and biology. It is used to estimate the free energy and other state functions of a system, where ergodicity is hindered by the form of the system's energy landscape. It was first suggested by Alessandro Laio and Michele Parrinello in 2002 and is usually applied within molecular dynamics simulations. MTD closely resembles a number of recent methods such as adaptively biased molecular dynamics, adaptive reaction coordinate forces and local elevation umbrella sampling. More recently, both the original and well-tempered metadynamics were derived in the context of importance sampling and shown to be a special case of the adaptive biasing potential setting. MTD is related to the Wang–Landau sampling.
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