Random Number Generator

Random number generators (RNGs) are fundamental tools across numerous scientific fields, with current research focusing on improving their quality, efficiency, and applicability in diverse contexts. This includes developing novel RNG architectures, such as those based on neural networks and quasirandom sequences, to enhance performance in machine learning and improve the generation of diverse and diffuse outputs for tasks like synthetic data creation. The reliability and security of RNGs are also critical areas of investigation, with studies exploring methods to detect manipulated or compromised generators and to create robust watermarking schemes for protecting generated data. Ultimately, advancements in RNG technology are crucial for ensuring reproducibility, security, and efficiency in various computational applications.