New algorithm enables simulation of complex quantum systems
An international team of scientists from the University of Luxembourg, Berlin Institute for the Foundations of Learning and Data (BIFOLD) at TU Berlin and Google has now successfully developed a machine learning algorithm to tackle large and complex quantum systems. The article has been published in the renowned journal Science Advances. The quantum properties of atoms shape countless biochemical and physical processes. Some of the world's greatest scientific challenges are fundamentally tied to understanding many interacting atoms over time. These interactions are governed by the laws of quantum mechanics. Examples range from the formation of nucleic acids in the genome, to the decomposition of harmful molecules in the atmosphere. Especially challenging for scientists are the correlations in space and time of such quantum systems: Their most interesting properties do not result from a simple summation of individual contributions from atoms but from intricate atomic correlations.
