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Instead of doing tens of so-called entanglement or controlled NOT operations, the new technique allows researchers to run hundreds of such operations and still get reliable results, he explained. The new error mitigation strategy allows researchers to tease the right answer out of simulations that require a large number of operations, “Way more than what people generally have been able to do,” de Jong said. This work could have far-reaching implications for the field of quantum computing. By putting all these pieces together, they were able to obtain reliable results from an IBM quantum computer. The Berkeley Lab team combined their new approach with three other different error mitigation techniques: readout error correction using “iterative Bayesian unfolding,” a technique commonly used in high-energy physics a homegrown version of randomized compiling and error extrapolation. The noise estimation circuit approach corrects some errors, but not all. The team created a modified version of the circuit to give a predictable answer – 0 or 1 – and used the difference between the measured and predicted answer to correct the output measured of the real circuit.

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A circuit is a series of operations or a program executed on a quantum computer to calculate the answer of a scientific problem.

To get there, the Berkeley Lab researchers developed a novel approach they call noise estimation circuits. “On average, we want to be able to say what the right answer should be,” Nachman said.

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The next best thing: error mitigation – methods and software to reduce noise and minimize errors in the science outcomes of quantum simulations.

“So noise here just basically means: It’s stuff you don’t want, and it obscures the result you do want,” said Ben Nachman, a Berkeley Lab physicist and co-author on the study who also leads the cross-cutting Machine Learning for Fundamental Physics group.Īnd while error correction – which is routine in classical computers – would be ideal, it is not yet feasible on current quantum computers due to the number of qubits needed. And the prevalence of noise dramatically increases the more operations one tries to perform with a quantum computer, which makes it harder to tease out the right answer and severely limits quantum computers’ usability as they’re scaled up. The latter relates to the actual operations performed noise here means the probability of applying the wrong operation. The former has to do with reading out the result of a run on a quantum computer the more noise, the higher the chance a qubit – the quantum equivalent of a bit on a classical computer – will be measured in the wrong state. There are different types of noise, including readout noise and gate noise. This is due in large part to something known as “noise” (errors). And there's still a lot of work that has to be done to make them reliable.”įor now, one of the problems is that quantum computers are still too error-prone to be consistently useful. “But the real challenge is quantum computers are relatively new. De Jong also leads the AMCRD’s Applied Computing for Scientific Discovery Group. “Quantum computers have the potential to solve more complex problems way faster than classical computers,” said Bert de Jong, one of the lead authors of the study and the director of the AIDE-QC and QAT4Chem quantum computing projects. The research team describes this work in a paper published in Physical Review Letters, ' Mitigating Depolarizing Noise on Quantum Computers with Noise-Estimation Circuits.” Newswise - A collaboration between Lawrence Berkeley National Laboratory’s (Berkeley Lab’s) Applied Mathematics and Computational Research Division (AMCRD) and Physics Division has yielded a new approach to error mitigation that could help make quantum computing’s theoretical potential a reality.

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