Lindsey LeBlanc, National Institute of Standards and Technology
Abstract
Quantum mechanics manifests itself at the macroscopic scale through a variety of phenomena, including magnetism and superconductivity. To model this behaviour, microscopic simulations must include the correlations and many-body relationships that exist between the particles involved, which, when considering the multiplicity of possible states and the extent of correlations in a quantum mechanical ensemble, quickly consumes all available classical computational power. In response to this challenge, quantum simulation has emerged in the quest to understand the mechanisms underlying these and other strongly correlated systems. This “analogue” approach to computation takes quantum mechanical constituents particles and places them in an environment where their behaviour will mimic that of the system of interest. During the computation, the quantum mechanical correlations and superpositions are automatically included, and results are found by measuring the ensemble’s final state after a controlled evolution. Neutral ultracold atoms,whose internal states, interactions, motion, and environment can be precisely engineered and whose properties can be accurately measured, are an ideal medium in which to implement quantum simulation. Among the many recent cold atom experiments demonstrating quantum simulation, techniques that modify the spin and momentum degrees of freedom were used to subject neutral atoms to an “artificial” magnetic field and associated Lorentz force. Adding these methods to the quantum simulation toolbox opens up new possibilities for studying the behavior of many-body systems, including a recent demonstration that used the Hall effect to extract information about a superfluid Bose-Einstein condensate. Through the continued development and implementation of these quantum simulation tools, new models of quantum matter can be constructed to answer questions about the emergence and behaviour of many-body systems that cannot be answered via classical computation.