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arXiv:2210.10364 · Physical Review Applied

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

Shuai Wang, Wenjun Zhang, Tao Zhang, Shuyao Mei, Yuqing Wang, Jiazhong Hu, Wenlan Chen

Published May 9, 2023• 23 citations
arXivHTMLPDF

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 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 an alternative algorithm named the Tetris algorithm to reassemble atoms to arbitrary target array geometry from two-dimensional stochastically loaded atomic arrays. For an $L\ifmmode\times\else\texttimes\fi{}L$ target array geometry, the number of moves scales as $L$, and the total rearrangement time scales at most as ${L}^{2}$. Although in this work we do not test on actual atoms, we simulate the performance of our FPGA system experimentally with all components integrated except for the atoms. We present the overall performance for different target geometries, and demonstrate a dramatic boost in rearrangement time cost and the potential to scale up defect-free atomic array to 1000 atoms in room-temperature platform and 10 000 atoms in cryogenic environment.

DOI
10.1103/physrevapplied.19.054032

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Neutral atoms have emerged as a promising technology for implementing quantum computers due to their scalability and long coherence times. However, the execution frequency of neutral atom quantum computers is constrained by image processing procedures, particularly the assembly of defect-free atom arrays, which is a crucial step in preparing qubits (atoms) for execution. To optimize this assembly process, we propose a novel quadrant-based rearrangement algorithm that employs a divide-and-conquer strategy and also enables the simultaneous movement of multiple atoms, even across different columns and rows. We implement the algorithm on Field Programmable Gate Arrays (FPGAs) to handle each quadrant independently (hardware-level optimization) while maximizing parallelization. To the best of our knowledge, this is the first hardware acceleration work for atom rearrangement, and it significantly reduces the processing time. This achievement also contributes to the ongoing efforts of tightly integrating quantum accelerators into High-Performance Computing (HPC) systems. Tested on a Zynq RFSoC FPGA at 250 MHz, our hardware implementation is able to complete the rearrangement process of a 30 × 30 compact target array, derived from a 50 × 50 initial loaded array, in approximately 1.0 μs. Compared to a comparable CPU implementation and to state-of-the-art FPGA work, we achieved about 54 x and 300 x speedups in the rearrangement analysis time, respectively. Additionally, the FPGA-based acceleration demonstrates good scalability, allowing for seamless adaptation to varying sizes of the atom array, which makes this algorithm a promising solution for large-scale quantum systems.
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The defect-free neutral atom array has emerged as an ideal platform to investigate complex many-body physics of interacting quantum particles, offering the opportunities for quantum simulation and quantum-enhanced metrology.To fast build a large-scale quantum system, we design a sorting-atom algorithm with maximum parallelisms.Compared with previous protocols, our method saves the rearrangement time by sorting row-by-row and is also universal to arbitrary periodic patterns with no need to change the hardware.We present the generation of a defect-free square and other periodic geometries and demonstrate the potential to scale up a defect-free array to 2500 atoms with only about 180 steps of rearrangement.
Defect-free atom arrays are a precursor for quantum information processing and quantum simulation with neutral atoms.Yet, large-scale defect-free atom arrays can be challenging to realize, due to the losses encountered when rearranging stochastically loaded atoms to achieve a desired target array.Here, we demonstrate a parallel rearrangement algorithm that uses multiple mobile tweezers to independently sort and compress atom arrays in a way that naturally avoids atom collisions.With a high degree of parallelism, our algorithm offers a reduced move complexity compared to both single-tweezer algorithms and existing multitweezer algorithms.We further determine the optimal degree of parallelism to be a balance between an algorithmic speedup and multitweezer inhomogeneity effects.The defect-free probability for a 225atom array is demonstrated to be as high as 33(1)% in a room-temperature setup after multiple cycles of rearrangement.The algorithm presented here can be implemented for any target array geometry with an underlying periodic structure.
Neutral-atom quantum computers encode qubits in individually trapped atoms arranged in optical lattices. Achieving defect-free atom configurations is essential for high-fidelity quantum gates and scalable error correction, yet stochastic loading and atom loss during rearrangement hinder reliable large-scale assembly. This work presents ATLAS, an open-source atom transport algorithm that efficiently converts a randomly loaded W×WW \times WW×W lattice into a defect-free L×LL \times LL×L subarray while accounting for realistic physical constraints, including finite acceleration, transfer time, and per-move loss probability. In the planning phase, optimal batches of parallel moves are computed on a lossless virtual array; during execution, these moves are replayed under probabilistic atom loss to maximize the expected number of retained atoms. Monte Carlo simulations across lattice sizes W=10W=10W=10--100100100, loading probabilities pocc=0.5p_{\mathrm{occ}}=0.5pocc​=0.5--0.90.90.9, and loss rates ploss=0p_{\mathrm{loss}}=0ploss​=0--0.050.050.05 demonstrate fill rates above 99%99\%99% within six iterations and over 90%90\%90% atom retention at low loss. The algorithm achieves sublinear move scaling (∝M0.55\propto M^{0.55}∝M0.55) and linear growth of required initial size with target dimension, outperforming prior methods in robustness and scalability -- offering a practical path toward larger neutral-atom quantum arrays.
Precisely controllable, defect-free neutral atom arrays have emerged as an outstanding platform for exploring complex quantum many-body systems and advancing quantum simulation and quantum computing. A method that boosts the rapid and efficient rearrangement is of great significance for expanding the scale of atomic arrays. Here, we present a fast parallel atomic array assembly method based on a PPM algorithm, i.e., position matching, path planning, and move in parallel. By optimizing atom-to-target trajectories using reduced position matching and introducing trajectory correction and target exchange in path planning, the PPM method can effectively minimize movement steps and displacement. The simulation of assembling atoms in parallel into arbitrary geometries shows a reduction of 49% and 35% in steps and displacement compared with the previous parallel algorithm, respectively. Our PPM simulation demonstrates the achievement of a defect-free arrangement of 1,024 atoms in only 35 steps.