A groundbreaking large-scale quantum simulator has the potential to unveil the mechanisms of exotic quantum materials and pave the way for their optimization in future applications.

Quantum computers are set to leverage unique quantum phenomena to perform calculations that are currently unmanageable for even the most advanced classical computers. Similarly, quantum simulators can aid researchers in accurately modeling materials and molecules that remain poorly understood.

This holds particularly true for superconductors, which conduct electricity with remarkable efficiency. The efficiency of superconductors arises from quantum effects, making it feasible to implement their properties directly in quantum simulators, unlike classical devices that necessitate extensive mathematical transformations.

Michelle Simmons and her team at Australia’s Silicon Quantum Computing have successfully developed the largest quantum simulator to date, known as Quantum Twin. “The scale and precision we’ve achieved with these simulators empower us to address intriguing challenges,” Simmons states. “We are pioneering new materials by crafting them atom by atom.”

The researchers designed multiple simulators by embedding phosphorus atoms into silicon chips. Each atom acts as a quantum bit (qubit), the fundamental component of quantum computers and simulators. The team meticulously configured the qubits into grids that replicate the atomic arrangement found in real materials. Each iteration of the Quantum Twin consisted of a square grid containing 15,000 qubits, surpassing any previous quantum simulator in scale. While similar configurations have been built using thousands of cryogenic atoms in the past, Quantum Twin breaks new ground.

By integrating electronic components into each chip via a precise patterning process, the researchers managed to control the electron properties within the chips. This emulates the electron behavior within simulated materials, crucial for understanding electrical flow. Researchers can manipulate the ease of adding an electron at specific grid points or the “hop” between two points.

Simmons noted that while conventional computers struggle with large two-dimensional simulations and complex electron property combinations, the Quantum Twin simulator shows significant potential for these scenarios. The team tested the chip by simulating the transition between conductive and insulating states—a critical mathematical model explaining how impurities in materials influence electrical conductivity. Additionally, they recorded the material’s “Hall coefficient” across different temperatures to assess its behavior in magnetic fields.

With its impressive size and variable control, the Quantum Twins simulator is poised to tackle unconventional superconductors. While conventional superconductors function well at low temperatures or under extreme pressure, some can operate under milder conditions. Achieving a deeper understanding of superconductors at ambient temperature and pressure is essential—knowledge that quantum simulators are expected to furnish in the future.

Moreover, Quantum Twins can also facilitate the investigation of interfaces between various metals and polyacetylene-like molecules, holding promise for advancements in drug development and artificial photosynthesis technologies, Simmons highlights.