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Machine learning in quantum spaces

Ordinary computers can perform machine learning by comparing mathematical representations of data. An experiment demonstrates how quantum computing could use quantum-mechanical representations instead.
  1. Maria Schuld

    1. Maria Schuld is at Xanadu Quantum Technologies, Toronto, Ontario M5V 2L7, Canada, and at the Quantum Research Group, School of Chemistry and Physics, University of KwaZulu-Natal, Durban, South Africa.

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Machine learning and quantum computing have their staggering levels of technology hype in common. But certain aspects of their mathematical foundations are also strikingly similar. In a paper in Nature, Havlíček et al.1 exploit this link to show how today’s quantum computers can, in principle, be used to learn from data — by mapping data into the space in which only quantum states exist.

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Nature 567, 179-181 (2019)

doi: https://doi.org/10.1038/d41586-019-00771-0

References

  1. Havlíček, V. et al. Nature 567, 209–212 (2019).

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  2. Schölkopf, B. & Smola, A. J. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond (MIT Press, 2002).

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  3. Schuld, M. & Killoran, N. Phys. Rev. Lett. 122, 040504 (2019).

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