Efficient Image Reconstruction Architecture for Neutral Atom Quantum Computing

TL;DR

This paper introduces a highly-parallel FPGA-based image analysis system that significantly accelerates atom detection in neutral atom quantum computers, reducing measurement time and enhancing scalability.

Contribution

It presents a novel FPGA implementation for parallel image analysis, achieving substantial speedups over CPU methods for atom detection in quantum computing.

Findings

Achieves 115 μs analysis time for 256x256 images

Provides 34.9x speedup over CPU baseline

Contributes to FPGA-based control system development

Abstract

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.