• Open Access

Scalable and Parallel Tweezer Gates for Quantum Computing with Long Ion Strings

Tobias Olsacher, Lukas Postler, Philipp Schindler, Thomas Monz, Peter Zoller, and Lukas M. Sieberer
PRX Quantum 1, 020316 – Published 2 December 2020

Abstract

Trapped-ion quantum computers have demonstrated high-performance gate operations in registers of about ten qubits. However, scaling up and parallelizing quantum computations with long one-dimensional (1D) ion strings is an outstanding challenge due to the global nature of the motional modes of the ions, which mediate qubit-qubit couplings. Here, we devise methods to implement scalable and parallel entangling gates by using engineered localized phonon modes. We propose to tailor such localized modes by tuning the local potential of individual ions with programmable optical tweezers. Localized modes of small subsets of qubits form the basis to perform entangling gates on these subsets in parallel. We demonstrate the inherent scalability of this approach by presenting analytical and numerical results for long 1D ion chains and even for infinite chains of uniformly spaced ions. Furthermore, we show that combining our methods with optimal coherent control techniques allows realization of maximally dense universal parallelized quantum circuits.

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  • Received 26 August 2020
  • Accepted 4 November 2020

DOI:https://doi.org/10.1103/PRXQuantum.1.020316

Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.

Published by the American Physical Society

Physics Subject Headings (PhySH)

Quantum Information, Science & Technology

Authors & Affiliations

Tobias Olsacher1,2,*, Lukas Postler3, Philipp Schindler3, Thomas Monz3, Peter Zoller1,2, and Lukas M. Sieberer1,2,†

  • 1Center for Quantum Physics University of Innsbruck, Innsbruck, Austria
  • 2Institute for Quantum Optics and Quantum Information of the Austrian Academy of Sciences, Innsbruck, Austria
  • 3Institut für Experimentalphysik, Universität Innsbruck, Innsbruck, Austria

  • *tobias.olsacher@uibk.ac.at
  • lukas.sieberer@uibk.ac.at

Popular Summary

Quantum computers hold the promise of accomplishing computational tasks that exceed the capabilities of conventional classical computers. Trapped atomic ions are a leading platform for quantum-information processing, and have demonstrated high-performance gate operations in registers of about ten qubits. While state-of-the-art ion traps can sustain quantum registers of more than a hundred qubits, scaling up and, in particular, parallelizing gate operations remains an outstanding challenge. This is because gate operations use collective modes of oscillation of the crystal structure, which is formed by the ions, to mediate the transfer of quantum information between qubits, and these phonon modes become increasingly complex in large ion crystals. In our work, we develop new methods to address this challenge.

We propose to use optical tweezers to pin individual ions and in this way shape the structure of the phonon modes. In particular, localized phonon modes, which correspond to coupled oscillations of pairs of neighboring ions, can be used to implement parallel entangling two-qubit gates on these pairs. We demonstrate the inherent scalability of this approach by presenting analytical and numerical results for long one-dimensional ion crystals and even for infinite crystals of uniformly spaced ions. Our methods enable the implementation of universal parallelized quantum circuits, with a wide range of applications in quantum computation and simulation.

An intriguing perspective opened up by our work is to utilize localized phonon modes for the design of Hamiltonians in analog quantum simulation. Further, the optical segmentation of long ion chains through optical tweezers can lead to the realization of one-dimensional quantum networks.

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Vol. 1, Iss. 2 — December - December 2020

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