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Demonstration of two-qubit algorithms with a superconducting quantum processor

Author

Listed:
  • L. DiCarlo

    (Yale University, New Haven, Connecticut 06511, USA)

  • J. M. Chow

    (Yale University, New Haven, Connecticut 06511, USA)

  • J. M. Gambetta

    (University of Waterloo, Waterloo, Ontario N2L 3G1, Canada)

  • Lev S. Bishop

    (Yale University, New Haven, Connecticut 06511, USA)

  • B. R. Johnson

    (Yale University, New Haven, Connecticut 06511, USA)

  • D. I. Schuster

    (Yale University, New Haven, Connecticut 06511, USA)

  • J. Majer

    (Atominstitut der Österreichischen Universitäten, TU-Wien, A-1020 Vienna, Austria)

  • A. Blais

    (Université de Sherbrooke, Sherbrooke, Québec J1K 2R1, Canada)

  • L. Frunzio

    (Yale University, New Haven, Connecticut 06511, USA)

  • S. M. Girvin

    (Yale University, New Haven, Connecticut 06511, USA)

  • R. J. Schoelkopf

    (Yale University, New Haven, Connecticut 06511, USA)

Abstract

Solid progress By exploiting two key aspects of quantum mechanics — the superposition and entanglement of physical states — quantum computers may eventually outperform their classical equivalents. A team based at Yale has achieved an important step towards that goal — the demonstration of the first solid-state quantum processor, which was used to execute two quantum algorithms. Quantum processors based on a few quantum bits have been demonstrated before using nuclear magnetic resonance, cold ion traps and optical systems, all of which bear little resemblance to conventional computers. This new processor is based on superconducting quantum circuits fabricated using conventional nanofabrication technology. There is still a long way to go before quantum computers can challenge the classical type. The processor is very basic, containing just two quantum bits, and operates at a fraction of a degree above absolute zero. But the chip contains all the essential features of a miniature working quantum computer and may prove scalable to more quantum bits and more complex algorithms.

Suggested Citation

  • L. DiCarlo & J. M. Chow & J. M. Gambetta & Lev S. Bishop & B. R. Johnson & D. I. Schuster & J. Majer & A. Blais & L. Frunzio & S. M. Girvin & R. J. Schoelkopf, 2009. "Demonstration of two-qubit algorithms with a superconducting quantum processor," Nature, Nature, vol. 460(7252), pages 240-244, July.
    • Handle: RePEc:nat:nature:v:460:y:2009:i:7252:d:10.1038_nature08121
    DOI: 10.1038/nature08121
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    Cited by:

    1. Suhas Ganjam & Yanhao Wang & Yao Lu & Archan Banerjee & Chan U Lei & Lev Krayzman & Kim Kisslinger & Chenyu Zhou & Ruoshui Li & Yichen Jia & Mingzhao Liu & Luigi Frunzio & Robert J. Schoelkopf, 2024. "Surpassing millisecond coherence in on chip superconducting quantum memories by optimizing materials and circuit design," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    2. Johannes Herrmann & Sergi Masot Llima & Ants Remm & Petr Zapletal & Nathan A. McMahon & Colin Scarato & François Swiadek & Christian Kraglund Andersen & Christoph Hellings & Sebastian Krinner & Nathan, 2022. "Realizing quantum convolutional neural networks on a superconducting quantum processor to recognize quantum phases," Nature Communications, Nature, vol. 13(1), pages 1-7, December.
    3. Paul V. Klimov & Andreas Bengtsson & Chris Quintana & Alexandre Bourassa & Sabrina Hong & Andrew Dunsworth & Kevin J. Satzinger & William P. Livingston & Volodymyr Sivak & Murphy Yuezhen Niu & Trond I, 2024. "Optimizing quantum gates towards the scale of logical qubits," Nature Communications, Nature, vol. 15(1), pages 1-8, December.

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