Explores energy conservation in Hamiltonian systems, numerical integration, time step choices, and constraint algorithms in molecular dynamics simulations.
Covers the basics of molecular dynamics simulations, ensemble properties, classical mechanics formulations, numerical integration, energy conservation, and constraint algorithms.
Explores QM/MM simulations using the Blue Moon ensemble theory, focusing on error analysis, ionic mass rescaling, stability comparison, and temperature control.
Covers vectorization in Python using Numpy for efficient scientific computing, emphasizing the benefits of avoiding for loops and demonstrating practical applications.