Computer simulation

A computer-executed model that imitates a real or hypothetical system under specified conditions. It can represent change over time, interactions, or outcomes across scenarios.

Mathematical model: A representation of a system using mathematical objects and relationships. A simulation turns a mathematical description into executable steps.
Climate model: A mathematical representation of Earth's climate system used to study its behavior and change. Climate simulations project interactions among atmosphere, ocean, land, and ice.
Physical model: A material or scaled representation of an object or system. Unlike a computer simulation, it reproduces selected features through a physical artifact.
Algorithm: A finite sequence of precise instructions for solving a problem or performing a computation. A simulation is implemented as algorithms that update model state and produce outputs.
Scientific method: A systematic approach to developing and testing explanations through observation and evidence. Simulation supports experiments on models, but its findings still depend on empirical checks.
Numerical analysis: The study of algorithms for approximate solutions to mathematical problems. Numerical methods make continuous equations computable on finite machines.
Flight simulator: A system that reproduces aircraft controls and flight conditions for training or evaluation. Pilots can practice procedures and emergencies without risking an aircraft.
Analytical solution: An exact or symbolic solution expressed through mathematical formulas. It can provide a direct result where a simulation may require approximations and computation.
State variable: A variable whose value describes part of a system's condition at a given time. State variables record the simulated system's changing condition.
Reproducibility: The ability to obtain consistent results by repeating a study or computational procedure. Documented code, inputs, and random seeds help make simulation results reproducible.

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