A Chinese research team has constructed a quantum computer capable of simulating the movement of electrons in a solid-state material, a task far beyond the capabilities of the world’s fastest supercomputers. Tracking these subatomic particles is crucial for answering fundamental scientific questions, such as the nature of magnetic attraction. Unlocking this knowledge could pave the way for high-temperature superconducting materials, potentially revolutionizing electricity transmission and transport.

“Our achievement demonstrates the capabilities of quantum simulators to exceed those of classical computers, marking a milestone in the second stage of China’s quantum computing research,” stated team leader Pan Jianwei in an announcement from the Chinese Academy of Sciences.

Groundbreaking Research

The research, published in Nature, was co-authored by Pan, from the University of Science and Technology of China (USTC), along with colleagues Chen Yuao and Yao Xingcan. The Nature reviewers described the work as “an important step forward for the field.”

Quantum computing research is currently focused on three stages. The first, known as “quantum supremacy,” involves quantum computers outperforming classical supercomputers on specific tasks. This goal has been achieved by developments such as Google’s Sycamore processor and China’s Jiuzhang and Zu Chongzhi quantum prototypes.

The second stage, which is the current focus of academic research, aims to create specialized quantum simulators that can tackle significant scientific problems beyond the reach of classical computers. The third stage will strive for universal, fault-tolerant quantum computing with the help of quantum error correction.

Quantum Simulation Milestone

Pan’s team reached the second stage by simulating the fermionic Hubbard model, a simplified model of electron motion in lattices proposed by British physicist John Hubbard in 1963. This model is useful for explaining high-temperature superconductivity, which has applications in power transmission, information technology, and transport. Even the most advanced supercomputers struggle to simulate this model.

“Simulating the movement of 300 electrons using classical computers would require storage space exceeding the total number of atoms in our universe,” Chen explained in the CAS statement.

Overcoming Challenges

To achieve their goal, Pan, known for leading the construction of the world’s first quantum satellite, and his team had to overcome three major challenges: creating optical lattices with uniform intensity distribution, achieving sufficiently low temperatures, and developing new measurement techniques to accurately characterize the states of the quantum simulator.

The team combined machine-learning optimization techniques with their previous work on homogeneous Fermi superfluids in box-shaped optical traps to prepare degenerate Fermi gases at ultra-low temperatures. This enabled them to observe a switch in a material from a paramagnetic to an antiferromagnetic state, or from being weakly attracted to a magnet to largely insensitive to one.

Future Implications

The research lays the groundwork for a deeper understanding of high-temperature superconductivity mechanisms. “Once we fully understand the physical mechanisms of high-temperature superconductivity, we can scale up the design, production, and application of new high-temperature superconducting materials, potentially revolutionizing fields such as electric power transmission, medicine, and supercomputing,” Chen said.

By Impact Lab