IBM quantum computer with 127 qubits out-performs traditional computers

One of the ultimate goals of quantum computing is to simulate components of materials that classical computers have never efficiently simulate.

But today’s quantum systems are inherently noisy and they produce a significant number of errors that hamper performance. This is due to the fragile nature of quantum bits or qubits and disturbances from their environment.

IBM has demonstrated that it is possible for a quantum computer to outperform leading classical simulations by learning and mitigating errors in the system.

The team used the IBM Quantum ‘Eagle’ quantum processor composed of 127 superconducting qubits on a chip to generate large, entangled states that simulate the dynamics of spins in a model of material and accurately predict properties such as its magnetization.

To verify the accuracy of this modeling, a team of scientists at UC Berkeley simultaneously performed these simulations on advanced classical computers located at Lawrence Berkeley National Lab’s National Energy Research Scientific Computing Center (NERSC) and Purdue University.

As the scale of the model increased, the quantum computer continued to turn out accurate results with the help of advanced error mitigation techniques, even while the classical computing methods eventually faltered and did not match the IBM Quantum system.

“This is the first time we have seen quantum computers accurately model a physical system in nature beyond leading classical approaches,” said Darío Gil, Senior Vice President and Director of IBM Research. “To us, this milestone is a significant step in proving that today’s quantum computers are capable, scientific tools that can be used to model problems that are extremely difficult – and perhaps impossible – for classical systems, signaling that we are now entering a new era of utility for quantum computing.”

To learn more about the details of the demonstration and the results, read the IBM Research blog.