Jonas Winklmann

Emil Khusainov, Yanbin Chen, Jonas Winklmann et al.

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.

Jonas Winklmann, Yian Yu, Xiaorang Guo et al.

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.