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Showing 1–7 of 7 results
Advanced filters: Author: Steve Habegger Clear advanced filters

  • Typical quantum error correcting codes assign fixed roles to the underlying physical qubits. Now the performance benefits of alternative, dynamic error correction schemes have been demonstrated on a superconducting quantum processor.

    • Alec Eickbusch
    • Matt McEwen
    • Alexis Morvan
    ResearchOpen Access
    Nature Physics
    Volume: 21, P: 1994-2001

  • Experimental measurements of high-order out-of-time-order correlators on a superconducting quantum processor show that these correlators remain highly sensitive to the quantum many-body dynamics in quantum computers at long timescales.

    • Dmitry A. Abanin
    • Rajeev Acharya
    • Nicholas Zobrist
    ResearchOpen Access
    Nature
    Volume: 646, P: 825-830

  • It is hoped that quantum computers may be faster than classical ones at solving optimization problems. Here the authors implement a quantum optimization algorithm over 23 qubits but find more limited performance when an optimization problem structure does not match the underlying hardware.

    • Matthew P. Harrigan
    • Kevin J. Sung
    • Ryan Babbush
    Research
    Nature Physics
    Volume: 17, P: 332-336

  • Quantum supremacy is demonstrated using a programmable superconducting processor known as Sycamore, taking approximately 200 seconds to sample one instance of a quantum circuit a million times, which would take a state-of-the-art supercomputer around ten thousand years to compute.

    • Frank Arute
    • Kunal Arya
    • John M. Martinis
    Research
    Nature
    Volume: 574, P: 505-510

  • Two below-threshold surface code memories on superconducting processors markedly reduce logical error rates, achieving high efficiency and real-time decoding, indicating potential for practical large-scale fault-tolerant quantum algorithms.

    • Rajeev Acharya
    • Dmitry A. Abanin
    • Nicholas Zobrist
    ResearchOpen Access
    Nature
    Volume: 638, P: 920-926

  • The goal of the 1000 Genomes Project is to provide in-depth information on variation in human genome sequences. In the pilot phase reported here, different strategies for genome-wide sequencing, using high-throughput sequencing platforms, were developed and compared. The resulting data set includes more than 95% of the currently accessible variants found in any individual, and can be used to inform association and functional studies.

    • Richard M. Durbin
    • David Altshuler (Co-Chair)
    • Gil A. McVean
    ResearchOpen Access
    Nature
    Volume: 467, P: 1061-1073