Quantum computing enables unprecedented materials science simulations
Multi-institutional team provides a foundation for unraveling the mysteries of magnetic materials.
The Science
Researchers have for the first time used a quantum computer to generate accurate results from materials science simulations that can be verified with practical techniques. The team used a form of quantum computing called quantum annealing. This approach uses quantum physics to simplify a computer model. The team overcame quantum hardware limitations by programming various parameters into a materials science model. Next, they embedded the model into team member D-Wave’s 2000Q quantum computer.
The Impact
The results from the simulation strongly resembled the output from real-world experiments. This demonstrates that quantum resources are capable of studying the magnetic structure and properties of magnetic materials. Eventually, such simulations on quantum computers could be more accurate and complex than simulations on classical digital computers. This would provide precise answers to materials science questions instead of approximations. It would also lead to a better understanding of spin liquids and spin ices. These are quantum states of matter that are potentially useful for data storage and other applications.
Summary
Using the largest quantum computer available at the time, researchers completed the largest simulation possible for the Ising model, a mathematical model of ferromagnetism. The research provides a foundation to streamline future efforts on next-generation quantum computers. Although quantum resources have previously simulated small molecules to examine chemical or material systems, studying massive magnetic materials containing thousands of atoms would not have been possible on a smaller system. By using a Monte Carlo simulation technique powered by the quantum evolution of the Ising model, the team gained valuable insights into the formation of a phenomenon known as fractional magnetization plateaus within materials called rare earth tetraborides in microscopic detail. This exotic phenomenon occurs in frustrated materials when an applied magnetic field, which normally causes all spins in a material to point in one direction, affects only some spins in the usual way while others point in the opposite direction instead.
Funding
This work was funded by the Department of Energy (DOE) Office of Science Early Career Research Program. Access to the D-Wave 2000Q system was provided through the Quantum Computing User Program managed by the Oak Ridge Leadership Computing Facility, a DOE Office of Science user facility located at Oak Ridge National Laboratory (ORNL). Research performed at ORNL’s Spallation Neutron Source, also a DOE Office of Science user facility located at ORNL, was supported by the DOE Office of Science. All the individuals and institutions involved with this research are members of the Quantum Science Center, a DOE Quantum Information Science Research Center established at ORNL in 2020.
DOI: https://doi.org/10.1103/PRXQuantum.1.020320
Method of Research: Computational simulation/modeling
Subject of Research: Not applicable
Article Title: Simulating the Shastry-Sutherland Ising Model Using Quantum Annealing
Article Publication Date: 14-Dec-2020
Media Contact
Michael Church
michael.church@science.doe.gov
Office: 505-358-1481
All latest news from the category: Materials Sciences
Materials management deals with the research, development, manufacturing and processing of raw and industrial materials. Key aspects here are biological and medical issues, which play an increasingly important role in this field.
innovations-report offers in-depth articles related to the development and application of materials and the structure and properties of new materials.
Newest articles
First-of-its-kind study uses remote sensing to monitor plastic debris in rivers and lakes
Remote sensing creates a cost-effective solution to monitoring plastic pollution. A first-of-its-kind study from researchers at the University of Minnesota Twin Cities shows how remote sensing can help monitor and…
Laser-based artificial neuron mimics nerve cell functions at lightning speed
With a processing speed a billion times faster than nature, chip-based laser neuron could help advance AI tasks such as pattern recognition and sequence prediction. Researchers have developed a laser-based…
Optimising the processing of plastic waste
Just one look in the yellow bin reveals a colourful jumble of different types of plastic. However, the purer and more uniform plastic waste is, the easier it is to…