Quantum Simulations as a Tool for Predictive Nanoscience

Abstract

In the last two decades, the coming of age of first principles theories of condensed and molecular systems, and the continuous increase in computer power have positioned physicists to address anew the complexity of matter at the microscopic level. Theoretical and algorithmic developments in ab initio molecular dynamics [ 1 ] and quantum Monte Carlo methods [ 2 ], together with optimized codes running on high-performance computers, have allowed many properties of matter to be inferred from the fundamental laws of quantum mechanics, without input from experiment.