4.8 Article

Preparation and measurement of three-qubit entanglement in a superconducting circuit

Journal

NATURE
Volume 467, Issue 7315, Pages 574-578

Publisher

NATURE PUBLISHING GROUP
DOI: 10.1038/nature09416

Keywords

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Funding

  1. LPS/NSA [W911NF-05-1-0365]
  2. IARPA [W911NF-09-1-0369]
  3. NSF [DMR-0653377, DMR-0603369]
  4. CNR-Istituto di Cibernetica, Pozzuoli, Italy
  5. CIFAR
  6. MITACS
  7. MRI
  8. NSERC

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Traditionally, quantum entanglement has been central to foundational discussions of quantum mechanics. The measurement of correlations between entangled particles can have results at odds with classical behaviour. These discrepancies grow exponentially with the number of entangled particles(1). With the ample experimental(2-4) confirmation of quantum mechanical predictions, entanglement has evolved from a philosophical conundrum into a key resource for technologies such as quantum communication and computation(5). Although entanglement in superconducting circuits has been limited so far to two qubits(6-9), the extension of entanglement to three, eight and ten qubits has been achieved among spins(10), ions(11) and photons(12), respectively. A key question for solid-state quantum information processing is whether an engineered system could display the multi-qubit entanglement necessary for quantum error correction, which starts with tripartite entanglement. Here, using a circuit quantum electrodynamics architecture(13,14), we demonstrate deterministic production of three-qubit Greenberger-Horne-Zeilinger (GHZ) states(15) with fidelity of 88 per cent, measured with quantum state tomography. Several entanglement witnesses detect genuine three-qubit entanglement by violating biseparable bounds by 830 +/- 80 per cent. We demonstrate the first step of basic quantum error correction, namely the encoding of a logical qubit into a manifold of GHZ-like states using a repetition code. The integration of this encoding with decoding and error-correcting steps in a feedback loop will be the next step for quantum computing with integrated circuits.

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