Master Equation

Master equations describe the time evolution of probability distributions in stochastic systems, a fundamental problem across diverse fields like physics, chemistry, and economics. Current research focuses on developing efficient numerical solutions, particularly for high-dimensional systems, employing techniques like neural networks (including recurrent and Boltzmann machine architectures), normalizing flows, and reinforcement learning algorithms. These advancements enable the study of complex systems previously intractable due to computational limitations, impacting fields ranging from quantum dynamics and chemical kinetics to macroeconomic modeling.