Scientists beat supercomputers with quantum tech that simulates electron motion

A Chinese research team has achieved a significant milestone in quantum computing by successfully building a device that can simulate the movement of electrons within a solid-state material.

This research, published in the journal Nature , showcases the potential of quantum computers to surpass even the most powerful supercomputers.

Understanding electron behavior is crucial for scientific advancements, particularly in the fields of magnetism and high-temperature superconducting materials. These materials could revolutionize electricity transmission and transportation, leading to significant energy savings and technological progress.

“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,” said team leader Pan Jianwei from the University of Science and Technology of China.

For reference, the second stage of quantum computing focuses on developing specialized quantum simulators. These simulators are designed to tackle specific scientific problems that are too complex for classical computers to handle efficiently.

A complex challenge

The research team focused on simulating the fermionic Hubbard model (FHM). It is a theoretical model describing electron motion within lattices, proposed by British physicist John Hubbard in 1963.

However, despite its importance in explaining high-temperature superconductivity, this model is notoriously difficult to simulate due to its complexity.

Besides, there is no exact solution for this model in two or three dimensions, and even the most powerful supercomputers struggle to explore its full parameter space due to high computational demands.

Chen Yuao, a co-author of the paper, explained that simulating the movement of 300 electrons using classical computers would require storage space exceeding the total number of atoms in the universe.

Overcoming challenges in quantum simulation

Quantum simulation involves using ultracold fermionic atoms in optical lattices to map out the low-temperature phase diagram of the FHM.

However, previous quantum simulation experiments faced challenges in realizing the antiferromagnetic phase transition due to the difficulty in cooling fermionic atoms and the inhomogeneity introduced by standard Gaussian-profile lattice lasers.

To overcome the challenges associated with simulating the Hubbard model, the team combined machine-learning optimization techniques with their previous work on homogeneous Fermi superfluids.

This enabled them to create optical lattices with uniform intensity distribution, achieve ultra-low temperatures, and develop new measurement techniques to characterize the states of the quantum simulator accurately.

Breakthrough observation, promising future

The research culminated in the observation of a switch in a material from a paramagnetic state (weakly attracted to a magnet) to an antiferromagnetic state (largely insensitive to a magnet). This finding can further our 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,” stated Chen while emphasizing the potential impact of this research.

This breakthrough marks a significant step forward in quantum computing research. It can immensely contribute to developing specialized quantum simulators to tackle scientific problems beyond the capabilities of classical computers.