Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

Efficient Image Reconstruction Architecture for Neutral Atom Quantum Computing

Jonas Winklmann, Yian Yu, Xiaorang Guo, Korbinian Staudacher, Martin Schulz

TL;DR

This work proposes a highly-parallel atom-detection accelerator for tweezer-based NAQCs that 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.

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 $μ$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.

Efficient Image Reconstruction Architecture for Neutral Atom Quantum Computing

TL;DR

This work proposes a highly-parallel atom-detection accelerator for tweezer-based NAQCs that 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.

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 256256-pixel image representing a 1010 atom array in just 115 s on a Xilinx UltraScale+ FPGA. Compared to the original CPU baseline and our optimized CPU version, we achieve about 34.9 and 6.3 speedup of the reconstruction time, respectively. Moreover, this work also contributes to the ongoing efforts toward fully integrated FPGA-based control systems for NAQCs.
Paper Structure (7 sections, 3 figures)

This paper contains 7 sections, 3 figures.

Table of Contents

  1. Introduction
  2. System Architecture
  3. Experiments and Evaluation
  4. Reconstructed Image
  5. Run Time of Reconstruction
  6. Resource Utilization
  7. Conclusion

Figures (3)

  • Figure 1: Overall Architecture of the Reconstruction Accelerator. In this figure, mat1 and mat2 represent the PSF kernel and the atom's image, respectively.
  • Figure 2: Result of the detection algorithm with a 30$\times$30 atom array as an example. (a) A raw image of the atom array captured by a camera (simulated). (b) The output of our reconstruction accelerator. Darker pixels denote higher reconstructed brightness. (c) Thresholded boolean result using a calibrated threshold. Black denotes a detected atom.
  • Figure 3: Run time comparison of the reconstruction process for various sizes of the atom array (10$\times$10 to 40$\times$40) among CPU-baseline, CPU-opt, and FPGA. Error bars represent the standard deviations of the run time.