Digital Quantum Simulation of Spin Models with Circuit Quantum Electrodynamics

Quantum simulations are expected to vastly outperform classical simulations when modeling the dynamics of interacting spin systems. Researchers have used a digital quantum simulation to show that spin dynamics can be studied and predicted, which lays the groundwork for applications in quantum magnetism and strongly correlated systems.

The properties of magnets and strongly correlated systems are ultimately determined by the interactions of elementary particles possessing a spin that can be imagined to be a small subatomic-sized magnet. However, as opposed to classical magnets, the exact dynamics of these spins can only be described by quantum mechanics, which can be simulated only for a few tens of particles on a classical computer. A quantum simulator – a well-controlled quantum system that mimics the behavior of a less-controllable system – may provide the solution to this problem.

Here, we develop a quantum simulator based on superconducting circuits that are fabricated much like conventional computer chips. We extract the dynamics of spin models on a circuit operating at 30 mK in a dilution refrigerator. Our quantum simulation is digital in the sense that it makes use of a mathematical expansion of the time evolution of the simulated system into small steps containing  identical sequences of one- and two-qubit gates. This approach is in principle not limited to spin systems but can be applied to general quantum systems with local interactions.

By scaling up our method using optimized pulse shapes and cryogenic components for multiplexed readout and control, our approach holds promise for accurately predicting the features and dynamics of larger spin systems. Based on our results, we expect that larger quantum simulators will be built, which will enable the study of a wide range of physics, chemistry, or biology problems such as quantum magnetism, chemical reactions, and high-energy physics, in regimes that are inaccessible to classical simulations.

Full article:  http://link.aps.org/doi/10.1103/PhysRevX.5.021027, also in arXiv:1502.06778

References: 
Y. Salathé, M. Mondal, M. Oppliger, J. Heinsoo, P. Kurpiers, A. Potočnik, A. Mezzacapo, U. Las Heras, L. Lamata, E. Solano, S. Filipp, and A. Wallraff, Phys. Rev. X 5, 021027 (2015)