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Quantum computing: physics–AI collaboration quashes quantum errors

A neural network has learnt to correct the errors that arise during quantum computation, outperforming algorithms that were designed by humans. The strategy sets out a promising path towards practical quantum computers.
  1. Nadia Haider

    1. Nadia Haider is in the Quantum Computing Division of QuTech and the Department of Microelectronics, Delft University of Technology, 2628 CD Delft, the Netherlands.

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Quantum computing is often touted as having the potential to solve problems that are beyond the capabilities of classical computers — from simulating molecules for drug development to optimizing complex logistics. Yet, a major obstacle stands in the way: quantum processors are prone to errors caused by disturbances from their environment and other sources. Overcoming this challenge is crucial to building a practical quantum computer. Writing in Nature, Bausch et al.1 introduce AlphaQubit, an approach that uses artificial intelligence (AI) to make a huge leap in correcting these quantum errors, pushing researchers closer to achieving scalable quantum computing.

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doi: https://doi.org/10.1038/d41586-024-03557-1

References

  1. Bausch, J. et al. Nature https://doi.org/10.1038/s41586-024-08148-8 (2024).

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  3. Raussendorf, R. & Harrington, J. Phys. Rev. Lett. 98, 190504 (2007).

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  4. Higgott, O. ACM Trans. Quantum Comput. 3, 16 (2022).

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Competing Interests

The author declares no competing interests.

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