3D-Printed Micro Ion Trap Technology for Scalable Quantum Information Processing
ORAL · Invited
Abstract
Modern trapped-ion quantum information processing experiments usually rely on photo-lithographic techniques to miniaturize the traps and meet scalability requirements. Using photolithography, it is challenging to fabricate the complex three-dimensional electrode structures required for optimal confinement. Here we address these limitations by adopting a high-resolution 3D printing technology based on two-photon polymerization supporting fabrication of large arrays of high-performance miniaturized 3D traps. We show that 3D-printed ion traps combine the advantages of traditionally machined 3D traps with the miniaturization provided by photolithography by confining single calcium ions in a small 3D-printed ion trap with radial trap frequencies ranging from 2 MHz to 24 MHz. The tight confinement eases ion cooling requirements and allows us to demonstrate high-fidelity coherent operations on an optical qubit after only Doppler cooling. With 3D printing technology, the design freedom is drastically expanded without sacrificing scalability and precision so that ion trap geometries can be optimized for higher performance and better functionality.
*The authors acknowledge Clemens Matthiesen's inspiration at the start of the project and James Oakdale for printing the first demonstration objects. The authors would also like to acknowledge Nicole Greene for the help on chamber assembly, Wei-Ting Chen for the useful guidance on the measurements. This work is supported by the UC Multicampus-National Lab Collaborative Research and Training under Award No.~LFR-20-653698 as well as by the Noyce initiative. Part of this work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. AJ acknowledges the support of ONR Grant No. N00014-21-1-2597.
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Publication:"3D-Printed Micro Ion Trap Technology for Scalable Quantum Information Processing" S. Xu, X. Xia, Q. Yu, S. Khan, E. Megidish, B. You, B. Hemmerling, A. Jayich, J. Biener, H. Häffner arXiv:2310.00595.
Presenters
Hartmut Haeffner
University of California, Berkeley
University of California Berkeley, and Lawrence Berkeley National Laboratory
Authors
Hartmut Haeffner
University of California, Berkeley
University of California Berkeley, and Lawrence Berkeley National Laboratory
