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arXiv:2412.14647 · Physical Review Letters

AI-Enabled Parallel Assembly of Thousands of Defect-Free Neutral Atom Arrays

Rui Lin, Han-Sen Zhong, Li You, Zhang-Rui Zhao, Le-Tian Zheng, Tai-Ran Hu, Hongming Wu, Zhan Wu, Wei-Jie Ma, Yan Gao, Yi-Kang Zhu, Zhaofeng Su, Wanli Ouyang, Yuchen Zhang, Jun Rui, Ming-Cheng Chen, Chao‐Yang Lu, Jian-Wei Pan

Published May 29, 2025• 36 citations
arXivHTMLPDF

Abstract

Assembling increasingly larger-scale defect-free optical-tweezer-trapped atom arrays is essential for quantum computation and quantum simulations based on atoms. Here, we propose an AI-enabled, rapid, constant-time-overhead rearrangement protocol, and we experimentally assemble defect-free 2D and 3D atom arrays with up to 2024 atoms with a constant-time cost of 60 ms. The AI model calculates the holograms for real-time atom rearrangement. With precise controls over both position and phase, a high-speed spatial light modulator moves all the atoms simultaneously. This protocol can be readily used to generate defect-free arrays of tens of thousands of atoms with current technologies and become a useful toolbox for quantum error correction.

DOI
10.1103/2ym8-vs82

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Assembling increasingly larger-scale defect-free optical-tweezer-trapped atom arrays is essential for quantum computation and quantum simulations based on atoms. Here, we propose an AI-enabled, rapid, constant-time-overhead rearrangement protocol, and we experimentally assemble defect-free 2D and 3D atom arrays with up to 2024 atoms with a constant-time cost of 60 ms. The AI model calculates the holograms for real-time atom rearrangement. With precise controls over both position and phase, a high-speed spatial light modulator moves all the atoms simultaneously. This protocol can be readily used to generate defect-free arrays of tens of thousands of atoms with current technologies and become a useful toolbox for quantum error correction.
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.
We present fast parallel rearrangement of single atoms in optical tweezers into arbitrary geometries by updating holograms displayed by an ultra fast spatial light modulator. Using linear interpolation of the tweezer position and the optical phase between the start and end arrays, we can calculate and display holograms every few ms, limited by technology. To show the versatility of our method, we sort the same atomic sample into multiple geometries with success probabilities of 0.996(2) 0.996 ( 2 ) per rearrangement cycle. This makes the method a useful tool for rearranging large atom arrays for quantum computation and quantum simulation.
It is widely believed that tens of thousands of physical qubits are needed to build a practically useful quantum computer. Atom arrays formed by optical tweezers are among the most promising platforms for achieving this goal, owing to the excellent scalability and mobility of atomic qubits. However, assembling a defect-free atom array with ~ 10^4 qubits remains algorithmically challenging, alongside other hardware limitations. This is due to the computationally hard path-planning problems and the time-consuming generation of suffciently smooth trajectories for optical tweezer potentials by spatial light modulators (SLM). Here, we present a unified framework comprising two innovative components to fully address these algorithmic challenges: (1) a path-planning module that employs a supervised learning approach using a graph neural network combined with a modified auction decoder, and (2) a potential-generation module called the phase and profile-aware Weighted Gerchberg-Saxton algorithm. The inference time for the first module is nearly a size-independent constant overhead of ~ 5 ms, and the second module generates a potential frame with about 0.5 ms, a timescale shorter than the current commercial SLM refresh time. Altogether, our algorithm enables the assembly of an atom array with 10^4 qubits on a timescale much shorter than the typical vacuum lifetime of the trapped atoms.
The rapid and reliable assembly of defect-free atom arrays poses a fundamental challenge for neutral atom quantum computing. While parallel rearrangement methods using spatial light modulators show promise, they suffer from significant overhead in two sub-tasks: atom-site matching and hologram generation. We propose a framework to address these bottlenecks and enhance the efficiency and fidelity of the assembly process. It features a new optimization objective for atom-site matching that minimizes the longest movement path, and a Fourier U-Net model that integrates Fourier operators with image-to-image translation to enable real-time hologram generation. The model is trained in a fully self-supervised paradigm, leveraging the physical properties of holography to remove the need for costly ground-truth labels. Experimental results show our framework not only significantly outperforms the state-of-the-art supervised CNN-based model but also achieves an inference speed orders of magnitude faster than traditional iterative algorithms, enabling real-time, dynamic atom rearrangement.
The ability to assemble and reconfigure individual atoms is central to performing quantum science using optical tweezer arrays. Here, we demonstrate parallel omnidirectional atom transport and rearrangement using dynamic holograms generated by a single kilohertz-rate spatial light modulator. By carefully characterizing survival and heating, we show that atoms remain confined even when successive holograms are commanded before the liquid crystal has settled, enabling significantly faster transport. To generate holograms in real time, we develop and implement a warm-start, weighted Gerchberg-Saxton algorithm that achieves performance comparable to neural-network methods without requiring any training. Combining these techniques, we assemble ytterbium atoms into a 2078-site kagome lattice with 99.0% mean filling. In addition, we demonstrate parallel transport between array layers, combining axial and transverse motion to reconfigure atoms in three dimensions. Our approach is readily adaptable to existing tweezer platforms and provides a method for large-scale SLM-based atom assembly as well as programmable three-dimensional control.
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.