Quantum Leaps Ahead: IBM’s Error Mitigation Strategy Outperforms Classical Supercomputers

Quantum Leaps Ahead: IBM’s Error Mitigation Strategy Outperforms Classical Supercomputers

IBM Eagle Quantum Computer

An interior view of the cryostat that cools the IBM Eagle, a utility-scale quantum processor containing 127 qubits. Utility scale is a point at which quantum computers could serve as a scientific tool to explore a new scale of problems that classical methods may not be able to solve. Credit: IBM Research

Quantum computer barely edged out supercomputer, showing utility of noisy quantum computers.

Researchers from IBM Quantum and collaborating institutions have demonstrated that a 127-qubit quantum computer can outperform classical supercomputers in specific calculations. The study revealed a novel error mitigation strategy and opened new possibilities for

Cori Supercomputer

Launched in 2017, Cori, a model from the Cray XC40 line, boasted an impressive peak performance of roughly 30 petaflops, securing its position as the fifth most dominant supercomputer globally at the time. Equipped with 2,388 Intel Xeon “Haswell” processor nodes, 9,688 Intel Xeon Phi “Knight’s Landing” nodes, and a substantial 1.8 PB Cray Data Warp Burst Buffer solid-state device, its name pays tribute to the renowned biochemist Gerty Cori. Notably, Gerty Cori was the first American woman to receive a Nobel Prize in the sciences and broke ground as the inaugural female recipient of the Nobel Prize in Physiology or Medicine. The Cori supercomputer was decommissioned on May 31, 2023. Credit: Berkeley Lab

Quantum vs. Classical: The Experiment

Over a period of several weeks, Youngseok Kim and Andrew Eddins at IBM Quantum ran increasingly complex quantum calculations on the advanced IBM Quantum Eagle processor, and then Anand attempted the same calculations using state-of-the-art classical methods on the Cori supercomputer and Lawrencium cluster at Berkeley Lab and the Anvil supercomputer at Purdue University. When Quantum Eagle was rolled out in 2021, it had the highest number of high-quality qubits of any quantum computer, seemingly beyond the ability of classical computers to simulate.

In fact, exactly simulating all 127 entangled qubits on a classical computer would require an astronomical amount of memory. The quantum state would need to be represented by 2 to the power of 127 separate numbers. That’s 1 followed by 38 zeros; typical computers can store around 100 billion numbers, 27 orders of magnitude too small. To simplify the problem, Anand, Wu, and Zaletel used approximation techniques that allowed them to solve the problem on a classical computer in a reasonable amount of time, and at a reasonable cost. These methods are somewhat like jpeg image compression, in that they get rid of less important information and keep only what’s required to achieve accurate answers within the limits of the memory available.

Anvil Supercomputer

Anvil, a powerful supercomputer that provides advanced computing capabilities to support a wide range of computational and data-intensive research is housed at Purdue University. Credit: Purdue University

Anand confirmed the accuracy of the quantum computer’s results for the less complex calculations, but as the depth of the calculations grew, the results of the quantum computer diverged from those of the classical computer. For certain specific parameters, Anand was able to simplify the problem and calculate exact solutions that verified the quantum calculations over the classical computer calculations. At the largest depths considered, exact solutions were not available, yet the quantum and classical results disagreed.

The researchers caution that, while they can’t prove that the quantum computer’s final answers for the hardest calculations were correct, Eagle’s successes on the previous runs gave them confidence that they were.

“The success of the quantum computer wasn’t like a fine-tuned accident. It actually worked for a whole family of circuits it was being applied to,” Zaletel said.

Friendly Competition and Future Perspectives

While Zaletel is cautious about predicting whether this error mitigation technique will work for more qubits or calculations of greater depth, the results were nonetheless inspiring, he said.

“It sort of spurred a feeling of friendly competition,” he said. “I have a sense that we should be able to simulate on a classical computer what they’re doing. But we need to think about it in a clever and better way — the quantum device is in a regime where it suggests we need a different approach.”

One approach is to simulate the ZNE technique developed by IBM.

“Now, we’re asking if we can take the same error mitigation concept and apply it to classical tensor network simulations to see if we can get better classical results,” Anand said. “This work gives us the ability to maybe use a quantum computer as a verification tool for the classical computer, which is flipping the script on what’s usually done.”

Reference: “Evidence for the utility of quantum computing before fault tolerance” by Youngseok Kim, Andrew Eddins, Sajant Anand, Ken Xuan Wei, Ewout van den Berg, Sami Rosenblatt, Hasan Nayfeh, Yantao Wu, Michael Zaletel, Kristan Temme and Abhinav Kandala, 14 June 2023, Nature.
DOI: 10.1038/s41586-023-06096-3

Anand and Zaletel’s work was supported by the U.S. Department of Energy under an Early Career Award (DE-SC0022716). Wu’s work was supported by a RIKEN iTHEMS fellowship. Cori is part of the National Energy Research Scientific Computing Center (NERSC), the primary scientific computing facility for the Office of Science in the U.S. Department of Energy.

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