Atomistic Computer Modelling of Materials: Simulating and Sampling

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Explores sampling the canonical ensemble, temperature fluctuations, extended Lagrangian, and Maxwell-Boltzmann distribution in molecular dynamics simulations.

Molecular dynamics and integrators

Explores molecular dynamics, integrators, trajectory generation, and error monitoring in atomistic modeling.

Monte Carlo Simulations

Covers the theory and practical aspects of Monte Carlo simulations in molecular dynamics, including ensemble averages and Metropolis algorithm.

Quantum to Classical Mechanics: Fundamentals

Covers the transition from quantum to classical mechanics, statistical mechanics, Monte Carlo simulations, and molecular dynamics simulations.

Markov Chain: Configuration Sampling

Introduces the concept of a Markov process and chain in configuration sampling.

Molecular dynamics under constraints

Explores molecular dynamics simulations under holonomic constraints, focusing on numerical integration and algorithm formulation.

Statistical Physics: Isolated Systems and Entropy

Covers statistical physics, isolated systems, entropy, and the Boltzmann distribution.

Path integrals and statistical mechanics

Explores path integral methods, partition functions, Trotter factorization, quantum-classical isomorphism, and multidimensional generalization in statistical mechanics.

Canonical Ensemble: Probability Distribution

Explores the probability distribution in the canonical ensemble and the Boltzmann distribution.

Molecular Dynamics: Sampling and Thermostats

Explores molecular dynamics sampling, conservation laws, energy fluctuations, and various thermostats used for simulations.