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arXiv:2209.08038 · Physical Review Applied

Parallel Assembly of Arbitrary Defect-Free Atom Arrays with a Multitweezer Algorithm

Weikun Tian, Wen Jun Wee, An Qu, Billy Jun Ming Lim, Prithvi Raj Datla, Vanessa P. W. Koh, Huanqian Loh

Published Mar 15, 2023• 44 citations
arXivHTMLPDF

Abstract

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.

DOI
10.1103/physrevapplied.19.034048

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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.
Defect-free atom arrays have emerged as a powerful and versatile platform for quantum sciences and technologies, offering high programmability and promising scalability. The arrays can be prepared by rearranging atoms from a partially loaded initial array to the designated target sites. However, achieving large defect-free arrays presents challenges due to atom loss during rearrangement and the vacuum-limited lifetime which is inversely proportional to the array size. Efficient rearrangement algorithms which minimize time cost and atom loss are crucial for successful atom rearrangement. Here we propose a novel parallel compression algorithm which leverages multiple mobile tweezers to transfer atoms simultaneously. The total time cost could be reduced to scale linearly with the number of target sites. This algorithm can be readily implemented in current experimental setups.
Assembling defect-free arrays of neutral atoms requires real-time rearrangement of stochastically loaded optical tweezers. Conventional rearrangement methods shuttle atoms sequentially, whereas high-speed spatial light modulators (SLMs) can move all atoms in parallel, which scales more favorably as the array size grows. For fast parallel rearrangement, the sequence of holograms displayed on the SLM should be computed more rapidly than the SLM refresh rate, and there should be phase continuity between successive holograms to minimize transient intensity fluctuations. We calculate holograms analytically by adding together the complex fields needed to produce each individual trap, and we ramp the phase of each trap linearly as it moves to its target location. Trap positions enter as continuous variables, rather than tied to points on a grid, so the method provides high positioning accuracy. Using a single GPU, we compute each intermediate hologram in 0.284 ms, considerably faster than the SLM refresh time of 0.696 ms, so the rearrangement speed is hardware-limited. In each step, we use the free processing time to iteratively optimize the holograms for equal intensity across the traps, decreasing trap non-uniformity to 1.24% during rearrangement at no cost in total time. Starting from an array of 256 sites loaded stochastically with 87^{87}87Rb atoms, we assemble a 100-atom array in under 20 ms with a rearrangement survival probability of 99.31(12)% per atom. This rearrangement increases the temperature of the atoms by 9(3) μμμK, which is small compared to the trap depth of 480 μμμK. Our method can also move individual atoms axially, enabling transport in different planes. We demonstrate this capability with a rearrangement protocol where one set of atoms leapfrogs over another.
Defect-free atom arrays provide new possibilities for exploring exotic quantum phenomena and realizing quantum computing. However, quickly and efficiently preparing defect-free atom arrays poses challenges. This paper proposes an innovative parallel rearrangement method, namely the parallel compression filling algorithm (PCFA), wherein multiple movable optical tweezers operate simultaneously. By limiting the shape of the initial loading, the method reduces movement complexity. The simulation comparisons show that this algorithm is more efficient in preparing defect-free atom arrays and can also be applied to the generation of other periodic structure arrays. The simulation results show that, in most cases, preparing a defect-free array of 400 atoms requires no more than 30 steps.
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.
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.
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.