论文标题
部分可观测时空混沌系统的无模型预测
A modular software framework for the design and implementation of ptychography algorithms
论文作者
论文摘要
计算方法正在推动高冲击显微镜技术，例如Ptychography。但是，新算法的设计和实现通常是一个费力的过程，因为代码的许多部分都是用近距离软件编程结构编写的，以加快重建。在本文中，我们介绍了Scicompty，这是一种旨在模拟Ptychography数据集并测试最新和新的重建算法的新的Ptychography软件框架。尽管它很简单，但该软件还是通过Pytorch CUDA接口加速了GPU加速处理。这对于设计可以容易使用的新方法至关重要。例如，我们提出了一种基于ADAM的改进方法和新版本的RPIE算法，该方法适用于部分相干设置。结果在合成数据集和真实数据集上显示。该软件以开源方式发布。
Computational methods are driving high impact microscopy techniques such as ptychography. However, the design and implementation of new algorithms is often a laborious process, as many parts of the code are written in close-to-the-hardware programming constructs to speed up the reconstruction. In this paper, we present SciComPty, a new ptychography software framework aiming at simulating ptychography datasets and testing state-of-the-art and new reconstruction algorithms. Despite its simplicity, the software leverages GPU accelerated processing through the PyTorch CUDA interface. This is essential to design new methods that can readily be employed. As an example, we present an improved position refinement method based on Adam and a new version of the rPIE algorithm, adapted for partial coherence setups. Results are shown on both synthetic and real datasets. The software is released as open-source.
