Quantum Brain
← Back to papers

Accelerating the Assembly of Defect-Free Atomic Arrays with Maximum Parallelisms

Shuai Wang, WenJun Zhang, Zhang Tao, Shuyao Mei, Yuqing Wang, Jiazhong Hu, Wenlan Chen·October 19, 2022·DOI: 10.1103/PhysRevApplied.19.054032
Physics

AI Breakdown

Get a structured breakdown of this paper — what it's about, the core idea, and key takeaways for the field.

Abstract

Defect-free atomic arrays have been demonstrated as a scalable and fully-controllable platform for quantum simulations and quantum computations. To push the qubit size limit of this platform further, we design an integrated measurement and feedback system, based on field programmable gate array (FPGA), to quickly assemble two-dimensional defect-free atomic array using maximum parallelisms. The total time cost of the rearrangement is first reduced by processing atom detection, atomic occupation analysis, rearrangement strategy formulation, and acousto-optic deflectors (AOD) driving signal generation in parallel in time. Then, by simultaneously moving multiple atoms in the same row (column), we save rearrangement time by parallelism in space. To best utilize these parallelisms, we propose a new algorithm named Tetris algorithm to reassemble atoms to arbitrary target array geometry from two-dimensional stochastically loaded atomic arrays. For an $L \times L$ target array geometry, the number of moves scales as $L$, and the total rearrangement time scales at most as $L^2$. We present the overall performance for different target geometries, and demonstrate a significant reduction in rearrangement time and the potential to scale up defect-free atomic array system to thousands of qubits.

Related Research

Quantum Intelligence

Ask about quantum research, companies, or market developments.