Classical Simulation

Classical simulation refers to computational methods that model physical, chemical, or biological systems using classical mechanics principles, such as Newton's laws, rather than quantum mechanics. It involves solving equations of motion numerically to predict system behavior over time, often applied to molecular dynamics, fluid dynamics, or material science. These simulations help understand macroscopic properties, optimize processes, and design new materials without costly physical experiments.

Also known as: Classical Molecular Dynamics, Newtonian Simulation, Classical Mechanics Simulation, MD Simulation, Classical Modeling

Why learn Classical Simulation?

Developers should learn classical simulation when working in scientific computing, computational physics, chemistry, or engineering fields that require modeling large-scale systems where quantum effects are negligible. It is essential for applications like drug discovery (simulating protein-ligand interactions), aerospace engineering (fluid flow analysis), and materials design (predicting mechanical properties), enabling efficient prototyping and hypothesis testing in research and industry.

Learning Resources

• course: Molecular Dynamics: Theory and Practice
• docs: Classical Simulation Methods in Physics
• video: Introduction to Classical Molecular Dynamics
• book: Numerical Recipes: The Art of Scientific Computing
• tutorial: GROMACS Tutorial for Classical Simulations