A quantum processor based on coherent transport of entangled atom arrays

By D. Bluvstein, H. Levine, G. Semeghini, Tout T. Wang, S. Ebadi, Marcin Kalinowski, A. Keesling, N. Maskara, Hannes Pichler, Markus Greiner and 2 more. Nature, 2021

832 citations recorded by the source corpus.

The ability to engineer parallel, programmable operations between desired qubits within a quantum processor is key for building scalable quantum information systems1,2. In most state-of-the-art approaches, qubits interact locally, constrained by the connectivity associated with their fixed spatial layout. Here we demonstrate a quantum processor with dynamic, non-local connectivity, in which entangled qubits are coherently transported in a highly parallel manner across two spatial dimensions, between layers of single- and two-qubit operations. Our approach makes use of neutral atom arrays trapped and transported by optical tweezers; hyperfine states are used for robust quantum information storage, and excitation into Rydberg states is used for entanglement generation3–5. We use this architecture to realize programmable generation of entangled graph states, such as cluster states and a seven-qubit Steane code state6,7. Furthermore, we shuttle entangled ancilla arrays to realize a surface code state with thirteen data and six ancillary qubits8 and a toric code state on a torus with sixteen data and eight ancillary qubits9. Finally, we use this architecture to realize a hybrid analogue–digital evolution2 and use it for measuring entanglement entropy in quantum simulations10–12, experimentally observing non-monotonic entanglement dynamics associated with quantum many-body scars13,14. Realizing a long-standing goal, these results provide a route towards scalable quantum processing and enable applications ranging from simulation to metrology. A quantum processer is realized using arrays of neutral atoms that are transported in a parallel manner by optical tweezers during computations, and used for quantum error correction and simulations.

Subfields: Artificial Intelligence

View Paper: https://www.semanticscholar.org/paper/149f7dd113dffe8783a80045f242e82ede280def

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

  1. William D. Oliver
  2. Youngkyu Sung
  3. Alec Jenkins
  4. J. Wang
  5. Felix Rönchen
  6. Aruku Senoo
  7. Joanna W. Lis
  8. W. McGrew

Citations in the corpus