arXiv subjects

Jonas Winklmann

Publications and source records attributed to Jonas Winklmann.

8 recordsLinked to original sources

arXiv2026

AtomFlow: An End-to-End FPGA-Based Control Architecture for Neutral Atom Quantum Computers

Neutral Atom Quantum Computing (NAQC) is an emerging modality for scalable quantum computation, valued for its long coherence times and the naturally identical atomic qubits. However, one of the main drawbacks is its slow execution rate, dominated by lengthy classical processing tasks, such as fluorescence imaging, cooling, and atom rearrangement. We address this bottleneck with AtomFlow, a field-programmable gate array (FPGA)-based control architecture that consolidates fluorescence-image analysis and a newly developed atom-rearrangement algorithm onto a single Zynq UltraScale+ device. By co-locating the two stages on the same board and emitting rearrangement moves in a streaming fashion as soon as they are computed, AtomFlow eliminates the round-trip latency of conventional host-mediated pipelines. Evaluated on a 16x16 atom array, AtomFlow achieves an end-to-end latency of 25.3 ms with a first-move latency of 4 ms and an average move generation of 1 ms. Furthermore, our scalability analysis demonstrates that the architecture can readily support larger atom arrays within a single-board resource budget.

quant-ph↗

arXiv2026

Practical Insights into Fair Comparison and Evaluation Frame for Neutral-Atom Compilers

Neutral-atom quantum computing is among the most promising platforms for scalable quantum computation, and compilation toolchains are crucial for leveraging capabilities such as qubit shuttling and parallel gate execution. An important challenge, however, is that existing neutral-atom compilers are often evaluated using metrics computed over different parts of the toolchain and under non-equivalent assumptions. Consequently, fair quantification and comparison of compiler performance remain difficult. Reported metrics may depend on inconsistent transpilation optimization levels, different movement-duration models, different sets of considered fidelity sources, and even minor implementation bugs or undocumented representation choices. To address this problem, we present a unified and reproducible evaluation framework for neutral-atom compilers. Our framework introduces RSQASM (Routed and Scheduled QASM), a QASM-inspired post-compilation representation that captures mapped, routed, and scheduled circuits, including explicit parallel gate execution and shuttling operations. As part of the framework, we provide adapter scripts that translate existing compiler outputs and intermediate artifacts into RSQASM. As a case study, we compare three well-known neutral-atom compilation toolchains: HybridMapper, DasAtom, and Enola, motivated by the large performance differences reported in prior work. Using our framework and representation, we perform a new evaluation and show that several previously claimed performance gaps become substantially smaller and, in some cases, are not reproduced once evaluation inconsistencies are removed.

cs.ET↗

arXiv2026

Highly-Parallel Atom-Detection Accelerator for Tweezer-Based Neutral Atom Quantum Computers

Neutral atom quantum computers (NAQCs) are among the most promising computational platforms for quantum computing. Controlling and measuring individual atoms and their states, which often requires multiple imaging and image-analysis procedures, is typically the most time-consuming task during computation and contributes significantly to overall cycle times. To resolve this challenge, we propose a highly-parallel atom-detection accelerator for tweezer-based NAQCs. Our design builds on an existing state-reconstruction method and combines an algorithm-level optimization with a Field Programmable Gate Array (FPGA) implementation to maximize parallelism and reduce the run time of the image-analysis process. We identify and overcome several challenges for an FPGA implementation, such as introducing a prefetching mechanism to improve scalability and customizing bus transfers to support large bandwidths. Tested on a Xilinx UltraScale+ FPGA, our design can analyze a 256x256-pixel fluorescence image in just 115mus, achieving 34.9x and 6.3x speedups over the original and optimized CPU baseline, respectively. Moreover, our accelerator can maintain consistent resource utilization across various atom array sizes, contributing to the ongoing efforts toward scalable and fully integrated FPGA-based control systems for NAQCs.

quant-ph↗

arXiv2026

Efficient Image Reconstruction Architecture for Neutral Atom Quantum Computing

In recent years, neutral atom quantum computers (NAQCs) have attracted a lot of attention, primarily due to their long coherence times and good scalability. One of their main drawbacks is their comparatively time-consuming control overhead, with one of the main contributing procedures being the detection of individual atoms and measurement of their states, each occurring at least once per compute cycle and requiring fluorescence imaging and subsequent image analysis. To reduce the required time budget, we propose a highly-parallel atom-detection accelerator for tweezer-based NAQCs. Building on an existing solution, our design combines algorithm-level optimization with a field-programmable gate array (FPGA) implementation to maximize parallelism and reduce the run time of the image analysis process. Our design can analyze a 256$\times$256-pixel image representing a 10$\times$10 atom array in just 115 $\mu$s on a Xilinx UltraScale+ FPGA. Compared to the original CPU baseline and our optimized CPU version, we achieve about 34.9$\times$ and 6.3$\times$ speedup of the reconstruction time, respectively. Moreover, this work also contributes to the ongoing efforts toward fully integrated FPGA-based control systems for NAQCs.

quant-ph↗

arXiv2025

HiPARS: Highly-Parallel Atom Rearrangement Sequencer

Neutral atom quantum computing's great scaling potential has resulted in it emerging as a popular modality in recent years. For state preparation, atoms are loaded stochastically and have to be detected and rearranged at runtime to create a predetermined initial configuration for circuit execution. Such rearrangement schemes either suffer from low parallelizability for acousto-optic deflector (AOD)-based approaches or are comparatively slow in case of spatial light modulators (SLMs). In our work, we introduce an algorithm that can improve the parallelizability of the former. Since the transfer of atoms from static SLM traps to AOD-generated movable traps is detrimental both in terms of atom loss rates and execution time, our approach is based on highly-parallel composite moves where many atoms are picked up simultaneously and maneuvered into target positions that may be comparatively distant. We see that our algorithm outperforms its alternatives for near-term devices with up to around 1000 qubits and has the potential to scale up to several thousand with further optimizations.

cs.ET↗

arXiv2024

Design of an FPGA-Based Neutral Atom Rearrangement Accelerator for Quantum Computing

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 FPGA 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$\times$30 compact target array, derived from a 50$\times$50 initial loaded array, in approximately 1.0 $\mu s$. Compared to a comparable CPU implementation and to state-of-the-art FPGA work, we achieved about 54$\times$ and 300$\times$ 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.

quant-ph↗

arXiv2024

Comparison of Atom Detection Algorithms for Neutral Atom Quantum Computing

In neutral atom quantum computers, readout and preparation of the atomic qubits are usually based on fluorescence imaging and subsequent analysis of the acquired image. For each atom site, the brightness or some comparable metric is estimated and used to predict the presence or absence of an atom. Across different setups, we can see a vast number of different approaches used to analyze these images. Often, the choice of detection algorithm is either not mentioned at all or it is not justified. We investigate several different algorithms and compare their performance in terms of both precision and execution run time. To do so, we rely on a set of synthetic images across different simulated exposure times with known occupancy states. Since the use of simulation provides us with the ground truth of atom site occupancy, we can easily state precise error rates and variances of the reconstructed property. To also rule out the possibility of better algorithms existing, we calculated the Cram\'er-Rao bound in order to establish an upper limit that even a perfect estimator cannot outperform. As the metric of choice, we used the number of photonelectrons that can be contributed to a specific atom site. Since the bound depends on the occupancy of neighboring sites, we provide the best and worst cases, as well as a half filled one. Our comparison shows that of our tested algorithms, a global non-linear least-squares solver that uses the optical system's PSF to return a each sites' number of photoelectrons performed the best, on average crossing the worst-case bound for longer exposure times. Its main drawback is its huge computational complexity and, thus, required calculation time. We manage to somewhat reduce this problem, suggesting that its use may be viable. However, our study also shows that for cases where utmost speed is required, simple algorithms may be preferable.

quant-ph↗

arXiv2023

Realistic Neutral Atom Image Simulation

Neutral atom quantum computers require accurate single atom detection for the preparation and readout of their qubits. This is usually done using fluorescence imaging. The occupancy of an atom site in these images is often somewhat ambiguous due to the stochastic nature of the imaging process. Further, the lack of ground truth makes it difficult to rate the accuracy of reconstruction algorithms. We introduce a bottom-up simulator that is capable of generating sample images of neutral atom experiments from a description of the actual state in the simulated system. Possible use cases include the creation of exemplary images for demonstration purposes, fast training iterations for deconvolution algorithms, and generation of labeled data for machine-learning-based atom detection approaches. The implementation is available through our GitHub as a C library or wrapped Python package. We show the modeled effects and implementation of the simulations at different stages of the imaging process. Not all real-world phenomena can be reproduced perfectly. The main discrepancies are that the simulator allows for only one characterization of optical aberrations across the whole image, supports only discrete atom locations, and does not model all effects of CMOS cameras perfectly. Nevertheless, our experiments show that the generated images closely match real-world pictures to the point that they are practically indistinguishable and can be used as labeled data for training the next generation of detection algorithms.

quant-ph↗