Gate operations in sympathetically-cooled Yb<sup>+</sup> chains
POSTER
Abstract
Preserving high gate fidelity while maintaining qubit connectivity is a major goal in scaling up quantum computers and simulators. In systems based on long chains of trapped ions, this is challenging due to heating via the coupling of ions to noisy electric fields, especially in the weakly-confined axial direction. In systems based on 171Yb+, this challenge can be countered by sympathetic cooling using 172Yb+ coolants [1].
We present progress towards an algorithmically useful implementation of this scheme in a room-temperature Yb+ system based on the Sandia HOA-2.1.1 trap. We demonstrate isotope-selective loading of 172Yb+ ions, protocols for reordering mixed-isotope chains to counter background-gas collisions, 3D sympathetic cooling, and integration of sympathetic cooling with gate operations.
This work is supported by the ARO with funding from the IARPA LogiQ program, the NSF QLCI program, and the DOE QSA program.
References
[1] M. Cetina et.al., PRX QUANTUM 3, 010334 (2022).
We present progress towards an algorithmically useful implementation of this scheme in a room-temperature Yb+ system based on the Sandia HOA-2.1.1 trap. We demonstrate isotope-selective loading of 172Yb+ ions, protocols for reordering mixed-isotope chains to counter background-gas collisions, 3D sympathetic cooling, and integration of sympathetic cooling with gate operations.
This work is supported by the ARO with funding from the IARPA LogiQ program, the NSF QLCI program, and the DOE QSA program.
References
[1] M. Cetina et.al., PRX QUANTUM 3, 010334 (2022).
Presenters
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Tianyi Wang
Duke University
Authors
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Tianyi Wang
Duke University
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Andrew Van Horn
Duke University
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Or Katz
Duke Quantum Center and Department Electrical and Computer Engineering (and Physics), Duke University, Durham, NC, Duke University
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Jungsang Kim
Duke University
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Marko Cetina
Duke Quantum Center and Department of Physics, Duke University, Durham, NC, JQI/QuICS/UMD Physics, DQC/Duke ECE, Duke University