Sign In

Communications of the ACM

ACM Careers

Researchers Embed Programmable Model Into Quantum Computer Chip

embedded quantum annealer

The embedding of a 468-spin Shastry-Sutherland lattice in the D-Wave quantum annealer.

Credit: PRX Quantum

A multi-institutional team generated accurate results from materials science simulations on a quantum computer that can be verified with neutron scattering experiments and other practical techniques.

Researchers from Oak Ridge National Laboratory, the University of Tennessee, Knoxville, Purdue University, and D-Wave Systems harnessed the power of quantum annealing, a form of quantum computing, by embedding an existing model into a quantum computer.  

Characterizing materials has long been a hallmark of classical supercomputers.

"The underlying method behind solving materials science problems on quantum computers had already been developed, but it was all theoretical," says Paul Kairys, a student at UT Knoxville's Bredesen Center for Interdisciplinary Research and Graduate Education. "We developed new solutions to enable materials simulations on real-world quantum devices."

This approach proves that quantum resources are capable of studying the magnetic structure and properties of these materials, which could lead to a better understanding of novel phases of matter useful for data storage and spintronics applications. The researchers describe their work in "Simulating the Shastry-Sutherland Ising Model Using Quantum Annealing," published in PRX Quantum.

"We are encouraged that the novel quantum annealing platform can directly help us understand materials with complicated magnetic phases, even those that have multiple defects," said co-corresponding author Arnab Banerjee, an assistant professor at Purdue. "This capability will help us make sense of real material data from a variety of neutron scattering, magnetic susceptibility, and heat capacity experiments, which can be very difficult otherwise."

From Oak Ridge National Laboratory
View Full Article


No entries found