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Analog Quantum Hardware Tackles Unsolvable Physics Problems

Purpose-built quantum simulator could model superconducting materials

Berenice Baker

February 8, 2023

1 Min Read
A portrait image of Andrew Mitchell with short hair and bears, wearing a suit
Study co-author Andrew Mitchell is the director of the UCD Center for Quantum Engineering, Science, and TechnologyUCD

The notion of using code on classical computers to simulate quantum computing circuits until the hardware can catch up is well established, but there are some problems that they may not be powerful enough to tackle.

Researchers have developed an analog hardware approach to model physics problems that quantum simulation software running on even the most powerful digital classical supercomputer cannot.

The scientists, from University College Dublin (UCD) and Stanford University, said their ‘quantum simulator’ can simulate interactions between two quantum objects, and can be scaled for more complicated systems.

The new tool could be used to investigate materials that are superconducting at room temperature. The superconducting materials currently used in MRI machines, high-speed trains and long-distance, energy-efficient power networks can only operate at extremely low temperatures.

The findings were published in the journal Nature Physics.

“Certain problems are simply too complex for even the fastest digital classical computers to solve,” said Andrew Mitchell, director of the UCD Center for Quantum Engineering, Science, and Technology and a co-author of the study.

“The accurate simulation of complex quantum materials such as the high-temperature superconductors is a really important example. That kind of computation is far beyond current capabilities because of the exponential computing time and memory requirements needed to simulate the properties of realistic models.”

He added that the analog quantum simulators the team developed solve specific models in quantum physics by using the inherent quantum mechanical properties of its nanoscale components.

"We're always making mathematical models that we hope will capture the essence of phenomena we’re interested in, but even if we believe they're correct, they're often not solvable in a reasonable amount of time,” said David Goldhaber-Gordon, creator of the device at Stanford’s Experimental Nanoscience Group.

About the Author(s)

Berenice Baker

Editor, Enter Quantum

Berenice is the editor of Enter Quantum, the companion website and exclusive content outlet for The Quantum Computing Summit. Enter Quantum informs quantum computing decision-makers and solutions creators with timely information, business applications and best practice to enable them to adopt the most effective quantum computing solution for their businesses. Berenice has a background in IT and 16 years’ experience as a technology journalist.

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