Creating perfect randomness is surprisingly difficult. Even modern random number generators never generate completely ideal random numbers: small systematic errors can result in some numbers appearing slightly more frequently than others. For many applications, this does not matter. In cryptography, however, even the tiniest deviations can be problematic.

Ultra-fast data transfer and superconductivity: Quantum materials offer significant technological prospects—if we can understand them at the atomic scale. A team from the University of Geneva (UNIGE), in collaboration with the University of Salerno, the Institute of Materials Science of Barcelona, and the National Research Council of Italy, has succeeded in observing the “quantum metric” in a topological insulator—a unique geometric property of these materials, which conduct electricity only on their surface.

Researchers have created a new theoretical framework that shows how memory-preserving “memtransistors” could overcome the intrinsic limits in efficiency faced by conventional semiconductor transistors, imposed by the laws of thermodynamics.

Whether the dust borne on the violent winds of a tornado or the sugar grains in a swirled cup of coffee, the behavior of particles carried along in turbulence is subject to some similarities—all of them difficult to predict at scale. As described in a recent publication in the Proceedings of the National Academy of Sciences, a research team led by Los Alamos National Laboratory scientists has developed a first-of-its-kind machine learning framework that models chaotic particle motions in a turbulent flow.