论文标题
通过贝叶斯优化的电子ptychography的自动参数选择
Automatic Parameter Selection for Electron Ptychography via Bayesian Optimization
论文作者
论文摘要
电子ptychography提供了新的机会，可以通过深度亚根斯特罗姆空间分辨率解决原子结构，并研究具有高剂量效率的电子光束敏感材料。实际上，获得准确的PtyChography图像需要同时优化通常基于试用和错误选择的多个参数，从而导致低通量实验并防止更广泛的采用。在这里，我们开发一个自动参数选择框架，以使用高斯流程的贝叶斯优化来解决此问题。凭借最少的先验知识，工作流有效地产生了比经验丰富的专家处理的ptychographic重建。该方法还通过探索来自模拟数据的优化实验参数来促进更好的实验设计。
Electron ptychography provides new opportunities to resolve atomic structures with deep sub-angstrom spatial resolution and studying electron-beam sensitive materials with high dose efficiency. In practice, obtaining accurate ptychography images requires simultaneously optimizing multiple parameters that are often selected based on trial-and-error, resulting in low-throughput experiments and preventing wider adoption. Here, we develop an automatic parameter selection framework to circumvent this problem using Bayesian optimization with Gaussian processes. With minimal prior knowledge, the workflow efficiently produces ptychographic reconstructions that are superior than the ones processed by experienced experts. The method also facilitates better experimental designs by exploring optimized experimental parameters from simulated data.
