Abstract
The trapped-ion quantum charge-coupled device (QCCD) proposal1,2 lays out a blueprint for a universal quantum computer that uses mobile ions as qubits. Analogous to a charge-coupled device (CCD) camera, which stores and processes imaging information as movable electrical charges in coupled pixels, a QCCD computer stores quantum information in the internal state of electrically charged ions that are transported between different processing zones using dynamic electric fields. The promise of the QCCD architecture is to maintain the low error rates demonstrated in small trapped-ion experiments3,4,5 by limiting the quantum interactions to multiple small ion crystals, then physically splitting and rearranging the constituent ions of these crystals into new crystals, where further interactions occur. This approach leverages transport timescales that are fast relative to the coherence times of the qubits, the insensitivity of the qubit states of the ion to the electric fields used for transport, and the low crosstalk afforded by spatially separated crystals. However, engineering a machine capable of executing these operations across multiple interaction zones with low error introduces many difficulties, which have slowed progress in scaling this architecture to larger qubit numbers. Here we use a cryogenic surface trap to integrate all necessary elements of the QCCD architecture—a scalable trap design, parallel interaction zones and fast ion transport—into a programmable trapped-ion quantum computer that has a system performance consistent with the low error rates achieved in the individual ion crystals. We apply this approach to realize a teleported CNOT gate using mid-circuit measurement6, negligible crosstalk error and a quantum volume7 of 26 = 64. These results demonstrate that the QCCD architecture provides a viable path towards high-performance quantum computers.
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The data presented in this manuscript are available from the corresponding author upon reasonable request.
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Acknowledgements
This work was made possible by a large group of people, and we thank the entire Honeywell Quantum Solutions team for their many contributions.
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J.M.P., J.M.D., C.F., J.P.G., S.A.M., M.S.A. and B.N. all contributed to the experimental design, construction and data collection. C.H.B. and K.M. contributed to the theory, quantum circuit design and data analysis. All authors contributed to this manuscript.
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Extended data figures and tables
Extended Data Fig. 1 System details.
a, Close-up schematic of the trap region used in this work. Dimensions are in micrometres. We refer to the orange gating region on the left as zone 1 and the blue gating region as zone 2. b, Transport primitive library and associated heating estimates. For the estimates, we fit four ion-crystal spin-flip data to a model that assumes that all modes are at the same temperature. The fitted temperature increases are converted to units of quanta/mode (we note that the inequality holds for all modes). The times shown do not include interpolation between different operations or small delays in the electronics, which increase the time for every operation by ~10%. The interzone shift is a linear shift between the two gate zones, whereas an intrazone shift moves ions within a single gate zone by 110 μm for single-qubit addressing. c, Times for qubit operations, transport and cooling. Circuits can be run using two different measurement protocols. For circuits in which all measurements are made at the end, we use the high-fidelity measurement setting. Circuits containing mid-circuit measurements use shorter-duration measurements to minimize the crosstalk error on idle qubits. The shorter detection time measurement error is ~7 × 10−3, about twice as large as those reported in Table 1. Mid-circuit measurements induce an error of ~1% on neighbouring idle qubits, as measured by a Ramsey experiment. There are three different cooling stages used during transport (stages 1 and 2) and before gates (stage 3) and are either implemented through Doppler or sideband (SB) cooling. d, Construction of a phase-insensitive TQ gate. The Mølmer–Sørensen interaction generates the unitary \({U}_{{\rm{MS}}}=\exp [-{\rm{i}}\frac{{\rm{\pi }}}{4}{(X\sin \varphi +Y\cos \varphi )}^{\otimes 2}]\) (orange), whose basis is determined by the optical phase ϕ. SQ operations driven by the same laser beams generate the unitary \({U}_{{\rm{SQ}}}=\exp [-{\rm{i}}\frac{{\rm{\pi }}}{4}(X\cos \,\varphi +Y\sin \,\varphi )]\) (blue) and are applied globally to both qubits. The resulting composite gate is, up to a global phase, given by \({U}_{zz}=\exp (-{\rm{i}}\frac{{\rm{\pi }}}{4}Z\otimes Z)\) (green).
Extended Data Fig. 2 Estimated gate errors and randomized benchmarking results.
a, SQ RB for all four qubits. b, TQ RB results for zone 1. c, TQ RB results for zone 2. d, An estimated error budget for a single TQ gate operation. e, Correlation parameters for simultaneous TQ RB. Each square represents a value of δi,j with the numbers being scaled by 10−4. All are within one standard deviation of zero. f, Addressability error estimates for simultaneous RB. The quantities \({\alpha }_{z}^{{\rm{both}}}\) and γz refer to simultaneous RB decay rates and their deviation from individual RB decay rates, as described in the text.
Extended Data Fig. 3 Teleported CNOT gate experiment results.
a, Circuit implementing a teleported CNOT gate, with q0 and q3 the control and target qubit, respectively. b, Bar plots showing the distribution of measurement outcomes when qubits q0 and q3 are prepared and measured in the {|0⟩, |1⟩} and {|+⟩, |−⟩} bases. c, The teleported CNOT gate time budget.
Extended Data Fig. 4 QV N = 4 results.
a, Example of the transport operations needed for part of an N = 4 QV circuit. Trap regions are labelled as load zone (L); auxiliary zone 1 (A1); gate zone 1, left (G1L); gate zone 1, centre (G1C); gate zone 1, right (G1R); auxiliary zone 2 (A2); gate zone 2, left (G2L); gate zone 2, centre (G2C); and gate zone 2, right (G2R). b, An N = 4 QV circuit time budget.
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Pino, J.M., Dreiling, J.M., Figgatt, C. et al. Demonstration of the trapped-ion quantum CCD computer architecture. Nature 592, 209–213 (2021). https://doi.org/10.1038/s41586-021-03318-4
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DOI: https://doi.org/10.1038/s41586-021-03318-4
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