Summary
Particle and nuclear physics (PNP) are fundamentally probabilistic due to quantum mechanics. Both fields rely on complex Monte-Carlo (MC)-based simulators that use random number sampling to make predictions for nearly all aspects of experimental design and data interpretation. In fact, most branches of science and engineering rely heavily on MC simulations for solving difficult problems, from modeling traffic flow to predicting weather patterns; in the rapidly emerging fields of machine learning and quantum computing, MC methods are essential. Progress in these areas requires developing, valid
