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On the Transport of Atomic Ions in Linear and Multidimensional Ion Trap Arrays

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arxiv quant-ph/0702175 v3 pith:YK7GM54M submitted 2007-02-16 quant-ph

On the Transport of Atomic Ions in Linear and Multidimensional Ion Trap Arrays

classification quant-ph
keywords ionstransporttrappedmultidimensionaltraparbitraryshuttlingarrays
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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Trapped atomic ions have become one of the most promising architectures for a quantum computer, and current effort is now devoted to the transport of trapped ions through complex segmented ion trap structures in order to scale up to much larger numbers of trapped ion qubits. This paper covers several important issues relevant to ion transport in any type of complex multidimensional rf (Paul) ion trap array. We develop a general theoretical framework for the application of time-dependent electric fields to shuttle laser-cooled ions along any desired trajectory, and describe a method for determining the effect of arbitrary shuttling schedules on the quantum state of trapped ion motion. In addition to the general case of linear shuttling over short distances, we introduce issues particular to the shuttling through multidimensional junctions, which are required for the arbitrary control of the positions of large arrays of trapped ions. This includes the transport of ions around a corner, through a cross or T junction, and the swapping of positions of multiple ions in a laser-cooled crystal. Where possible, we make connections to recent experimental results in a multidimensional T junction trap, where arbitrary 2-dimensional transport was realized.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. A framework for the benchmarking of transport-induced excitations in shuttling-based ion-trap quantum processors

    quant-ph 2026-05 unverdicted novelty 6.0

    A benchmarking framework decomposes shuttling protocols into primitives whose heating contributions combine algebraically to predict total excitations in ion-trap quantum processors, shown on an 8-qubit linear-transpo...

  2. Reinforcement learning for ion shuttling on trapped-ion quantum computers

    quant-ph 2026-05 unverdicted novelty 6.0

    Reinforcement learning optimizes ion shuttling on trapped-ion quantum chips and reduces operations by up to 36.3% versus heuristics across multiple architectures.