Stochastic Processes

Stochastic processes are mathematical models used to describe systems that evolve over time in a random manner. In contexts like Hamiltonian mechanics, they help analyze systems influenced by random forces. In non-equilibrium thermodynamics, they explain how systems transition between states under uncertainty. In statistics, they provide tools for predicting outcomes based on probabilities. In theoretical computer science, they model algorithms influenced by randomness. Essentially, stochastic processes allow us to understand and predict the behavior of complex systems where chance plays a significant role, capturing the inherent unpredictability of various phenomena.