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arXiv:2305.03828 · Physical Review X

A Race-Track Trapped-Ion Quantum Processor

Steven A. Moses, Charles H. Baldwin, M. S. Allman, R. Ancona, Leonardo Ascarrunz, C. H. W. Barnes, John P. Bartolotta, Bryce Bjork, P. Blanchard, Matthew J. Bohn, Justin Bohnet, N. C. Brown, Nathaniel Burdick, William Cody Burton, Sara Campbell, J. P. Campora, C. Carron, J. Chambers, J. W. Chan, Y. H. Chen, Alexander Chernoguzov, Eli Chertkov, J. Colina, J. P. Curtis, R. Daniel, Matthew P. DeCross, David A. Deen, Conor Patrick Delaney, Joan Dreiling, Christopher T. Ertsgaard, J. Esposito, Brian Estey, Maya Fabrikant, Caroline Figgatt, Clémence Foltz, Michael Foss‐Feig, David Francois, John Gaebler, Thomas M. Gatterman, C. N. Gilbreth, J. Giles, Erin Glynn, A. Hall, Aaron M. Hankin, A. Hansen, David Hayes, Bob Higashi, Ian M. Hoffman, B. Horning, J. J. Hout, Ryan T. Jacobs, J. Johansen, L. Jones, J. Karcz, T. Klein, P. Lauria, P. Lee, David Liefer, Shih-Wen Lu, Dominic Lucchetti, C. Lytle, A. Malm, Mitchell Matheny, Brian Mathewson, Karl Mayer, D. B. Miller, M. Mills, Brian Neyenhuis, Lora Nugent, S. Jay Olson, J. Parks, Gabriel Price, Z. Price, M. Pugh, Anthony Ransford, Adam Reed, Conrad Roman, M. Rowe, Ciarán Ryan-Anderson, S. Sanders, Jonathon A. Sedlacek, Peter Shevchuk, P. Siegfried, Thomas Skripka, B. Spaun, R. Tucker Sprenkle, Russell Stutz, Matthew D. Swallows, Ra'anan I. Tobey, A. Tran, T. Tran, E. Vogt, Curtis Volin, J. Walker, A. M. Zolot, J. M. Pino

Published Dec 18, 2023• 391 citations
arXivHTMLPDF

Abstract

We describe and benchmark a new quantum charge-coupled device (QCCD) trapped-ion quantum computer based on a linear trap with periodic boundary conditions, which resembles a race track.The new system successfully incorporates several technologies crucial to future scalability-including electrode broadcasting, multilayer rf routing, and magneto-optical trap (MOT) loading-while maintaining, and in some cases exceeding, the gate fidelities of previous QCCD systems.The system is initially operated with 32 qubits, but future upgrades will allow for more.We benchmark the performance of primitive operations, including an average state preparation and measurement error of 1.6ð1Þ × 10 -3 , an average single-qubit gate infidelity of 2.5ð3Þ × 10 -5 , and an average two-qubit gate infidelity of 1.84ð5Þ × 10 -3 .The systemlevel performance of the quantum processor is assessed with mirror benchmarking, linear cross-entropy benchmarking, a quantum volume measurement of QV ¼ 2 16 , and the creation of 32-qubit entanglement in a GHZ state.We also tested application benchmarks, including Hamiltonian simulation, QAOA, error correction on a repetition code, and dynamics simulations using qubit reuse.We also discuss future upgrades to the new system aimed at adding more qubits and capabilities.

DOI
10.1103/physrevx.13.041052

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Abstract We report on Quantinuum Helios, a 98-qubit trapped-ion quantum processor based on the quan- tum charge-coupled device (QCCD) architecture. Helios features 137Ba+ hyperfine qubits, all-to-all connectivity enabled by a rotatable ion storage ring connecting two quantum operation regions by a junction, speed improvements from parallelized operations, and a new software stack with real-time compilation of dynamic programs. Averaged over all operational zones in the system, we achieve average infidelities of 2.5(1) × 10−5 for single-qubit gates, 7.9(2) × 10−4 for two-qubit gates, and 4.8(6) × 10−4 for state preparation and measurement, none of which are fundamentally limited and likely able to be improved. These component infidelities are predictive of system-level performance in both random Clifford circuits and random circuit sampling, the latter demonstrating that Helios operates well beyond the reach of classical simulation and establishes a new frontier of fidelity and complexity for quantum computers.
Ion trap is one of the leading physical platforms to implement quantum computation. Currently, high-fidelity elementary quantum operations above the fault-tolerant threshold, including state preparation, measurement and universal gates, have been demonstrated for tens of ionic qubits. One important future research direction is to further enlarge the qubit number to the scale required for solving practical problems while maintaining the high performance of individual qubits. This paper introduces the current mainstream schemes for scalable ion trap quantum computation like quantum charge-coupled device (QCCD) and ion-photon quantum network, and describes the main limiting factors in current research. Then we further explore new schemes to scale up the qubit number like two-dimensional ion crystals and dual-type qubit, and discuss the future research directions.
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 experiments3–5 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.
Quantum computers are rapidly becoming more capable, with dramatic increases in both qubit count \cite{kim2023evidence} and quality \cite{moses2023race}. Among different hardware approaches, trapped-ion quantum processors are a leading technology for quantum computing, with established high-fidelity operations and architectures with promising scaling. Here, we demonstrate and thoroughly benchmark the IonQ Forte system: configured as a single-chain 30-qubit trapped-ion quantum computer with all-to-all operations. We assess the performance of our quantum computer operation at the component level via direct randomized benchmarking (DRB) across all 30 choose 2 = 435 gate pairs. We then show the results of application-oriented \cite{IonQ_AQ20_2022}\cite{qedcPeerReviewed} benchmarks and show that the system passes the suite of algorithmic qubit (AQ) benchmarks up to #AQ 29. Finally, we use our component-level benchmarking to build a system-level model to predict the application benchmarking data through direct simulation. While we find that the system-level model correlates with the experiment in predicting application circuit performance, we note quantitative discrepancies indicating significant out-of-model errors, leading to higher predicted performance than what is observed. This highlights that as quantum computers move toward larger and higher-quality devices, characterization becomes more challenging, suggesting future work required to push performance further.