Monte Carlo Simulation

Monte Carlo simulation is a computational technique that uses repeated random sampling to obtain numerical results for problems that are difficult to solve analytically. Current research focuses on improving efficiency and accuracy, particularly through the integration of machine learning models like generative adversarial networks (GANs) and deep neural networks (DNNs) to accelerate simulations and enhance precision, especially in computationally intensive fields like high-energy physics and astrophysics. These advancements are significantly impacting various scientific domains by enabling faster and more accurate analyses of complex systems, ranging from particle collisions to the spread of misinformation, ultimately leading to more robust and reliable scientific conclusions.