A high-fidelity quantum matter-link between ion-trap microchip modules

Akhtar, Mariam; Bonus, F.; Lebrun-Gallagher, Foni R.; Johnson, N. I.; Siegele-Brown, M.; Hong, Seok‐Jun; Hile, Samuel J.; Kulmiya, S. A.; Weidt, Sebastian; Hensinger, W. K.

doi:10.1038/s41467-022-35285-3

Cited by 27 publications

(14 citation statements)

References 48 publications

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“…Algorithms amenable to quantum speedup are those with a potentially large set of parallelizable tasks relative to se-quences of iterative control flow. Similarly, the ability to use modular (quantum) chip architectures has the potential to achieve similar parallel speedups to those observed in classical computing [127].…”

Section: Providermentioning

confidence: 96%

A Survey of Quantum Alternatives to Randomized Algorithms: Monte Carlo Integration and Beyond

Intallura¹,

Korpas²,

Chakraborty³

et al. 2023

Preprint

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Monte Carlo sampling is a powerful toolbox of algorithmic techniques widely used for a number of applications wherein some noisy quantity, or summary statistic thereof, is sought to be estimated. In this paper, we survey the literature for implementing Monte Carlo procedures using quantum circuits, focusing on the potential to obtain a quantum advantage in the computational speed of these procedures. We revisit the quantum algorithms that could replace classical Monte Carlo and then consider both the existing quantum algorithms and the potential quantum realizations that include adaptive enhancements as alternatives to the classical procedure.

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Section: Providermentioning

confidence: 96%

A Survey of Quantum Alternatives to Randomized Algorithms: Monte Carlo Integration and Beyond

Intallura¹,

Korpas²,

Chakraborty³

et al. 2023

Preprint

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“…While this design involves passing ions from one trap to another vertically and in the process turning one trap on and another off, a demonstration of passing ions from one trap to another in the same plane by abutting (but not contacting) the separate RF electrodes has been successfully achieved [26]. In this case the RF pseudo-potential provides nominally undisturbed confinement across chips.…”

Section: Basic Junction Designmentioning

confidence: 99%

Bilayer ion trap design for 2D arrays

Nop,

Smith,

Stick

et al. 2024

Quantum Sci. Technol.

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Junctions are fundamental elements that support qubit locomotion in two-dimensional ion traparrays and enhance connectivity in emerging trapped-ion quantum computers. In surface ion trapsthey have typically been implemented by shaping radio frequency (RF) electrodes in a single planeto minimize the disturbance to the pseudopotential. However, this method introduces issues relatedto RF lead routing that can increase power dissipation and the likelihood of voltage breakdown.Here, we propose and simulate a novel two-layer junction design incorporating two perpendicularlyrotoreflected (rotated, then reflected) linear ion traps. The traps are vertically separated, and create a trapping potentialbetween their respective planes. The orthogonal orientation of the RF electrodes of each trap relativeto the other provides perpendicular axes of confinement that can be used to realize transport intwo dimensions. While this design introduces manufacturing and operating challenges, as now twoseparate structures have to be precisely positioned relative to each other in the vertical directionand optical access from the top is obscured, it obviates the need to route RF leads below the topsurface of the trap and eliminates the pseudopotential bumps that occur in typical junctions. Inthis paper the stability of idealized ion transfer in the new configuration is demonstrated, both bysolving the Mathieu equation analytically to identify the stable regions and by numerically modelingion dynamics. Our novel junction layout enhances the flexibility of microfabricated ion trap controlto enable large-scale trapped-ion quantum computing.

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“…[5] Emerging quantum DOI: 10.1002/advs.202304449 technologies based on hybrid quantum systems [6] combine research from two or more experimental settings: such as coupling spins in silicon to superconducting resonators and qubits, [7,8] interfacing remote NV centers in diamond with photonic qubits, [9] and using nanomechanics to interface with spins [10] or superconducting qubits. [11] As these proof-of-principle devices become more sophisticated and start to scale in size and complexity, established lab infrastructure such as translation stages and solenoid coils will no longer provide the flexibility, speed, and precision to meet these constrained [12] and sometimes competing experimental requirements. In contrast, the field of robotics has long adapted to operate robots in challenging conditions, such as at the microscale [13] or in very low temperature environments.…”

Section: Introductionmentioning

confidence: 99%

Robotic Vectorial Field Alignment for Spin‐Based Quantum Sensors

Smith,

Zhang,

Balram

2023

Advanced Science

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Developing practical quantum technologies will require the exquisite manipulation of fragile systems in a robust and repeatable way. As quantum technologies move toward real world applications, from biological sensing to communication in space, increasing experimental complexity introduces constraints that can be alleviated by the introduction of new technologies. Robotics has shown tremendous progress in realizing increasingly smart, autonomous, and highly dexterous machines. Here, a robotic arm equipped with a magnet is demonstrated to sensitize an NV center quantum magnetometer in challenging conditions unachievable with standard techniques. Vector magnetic fields are generated with 1° angular and 0.1 mT amplitude accuracy and determine the orientation of a single stochastically‐aligned spin‐based sensor in a constrained physical environment. This work opens up the prospect of integrating robotics across many quantum degrees of freedom in constrained settings, allowing for increased prototyping speed, control, and robustness in quantum technology applications.

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A high-fidelity quantum matter-link between ion-trap microchip modules

Cited by 27 publications

References 48 publications

A Survey of Quantum Alternatives to Randomized Algorithms: Monte Carlo Integration and Beyond

A Survey of Quantum Alternatives to Randomized Algorithms: Monte Carlo Integration and Beyond

Bilayer ion trap design for 2D arrays

Robotic Vectorial Field Alignment for Spin‐Based Quantum Sensors

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