Introduces path integral molecular dynamics and its applications in quantum mechanics, focusing on nuclear quantum effects and their implications for molecular simulations.
Explores Car-Parrinello molecular dynamics, a unified approach combining molecular dynamics and density-functional theory for simulating various systems, with a focus on historical background, technical details, and challenges in atomistic simulations.
Explores machine learning in molecular dynamics simulations, addressing the curse of dimensionality, neural network representation, and force-field estimation.
Delves into Heisenberg's Uncertainty Principle and the wave-particle duality of quantum objects, including recent matter-wave interference experiments.
