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The Science

Newswise — Simulations of quantum many-body systems are an important goal for nuclear and high-energy physics. Many-body problems involve systems that consist of many microscopic particles interacting at the level of . They are much more difficult to describe than simple systems with just two particles. This means that even the most powerful conventional computers cannot simulate these problems.  has the potential to address this challenge using an approach called analog quantum simulation. To succeed, these simulations need theoretical approximations of how quantum computers represent many-body systems. In this research, nuclear physicists developed a new framework to analyze  these approximations and minimize their effects.

The Impact

This method provides a new tool for quantifying the uncertainties in analog quantum simulations of dynamical processes. Quantum computers are becoming more and more reliable and resilient to noise. However, to make reliable predictions, scientists need to understand and quantify sources of error and their effects on analog quantum simulations. Researchers can use the techniques developed in this work to improve the precision of future simulations.

Summary

In an analog quantum simulation, a highly controllable quantum system replicates the behavior of a more exotic system. A leading architecture for such simulations is Rydberg-atom quantum computers, which are scalable arrays of Rydberg atoms that support a universal quantum gate set. Scientists expect that with rapidly improving control, analog quantum computers will enable near-term advantages in uncovering new physics.

To make these simulations scientifically useful, researchers need robust theoretical approximations in representing systems of interest on quantum computers. Nuclear physicists at the University of Washington developed a new framework to systematically analyze the interplay of these approximations. They showed that the impact of such approximations can be minimized by tuning simulation parameters. Such optimizations are demonstrated in the context of spin models sharing key features with nuclear interactions.

Funding

This work was supported in part by the Department of Energy (DOE) Office of Science, Office of Nuclear Physics, InQubator for Quantum Simulation (IQuS) via the Quantum Horizons: QIS Research and Innovation for Nuclear Science; in part by the DOE QuantISED program through the “Intersections of QIS and Theoretical Particle Physics” theory consortium at Fermilab; and in part by the Department of Physics and the College of Arts and Sciences at the University of Washington.