贝叶斯推断来自稀疏测量的异型二维小角度散射的贝叶斯推断
Chi-Huan Tung1, Yangyang Wang2, Jan-Michael Carrillo2
1Neutron Scattering Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, USA.
The Journal of chemical physics
|October 15, 2025
概括
我们开发了一种新的贝叶斯方法,从有限的数据中重建二维小角度散射 (SAS) 模式. 这种技术可以准确地恢复结构细节,即使测量稀疏或噪音较大,也可以改进材料分析.
科学领域:
- 材料科学 材料科学 材料科学
- 中子散射物理学的物理学.
- 计算物理 计算物理
背景情况:
- 二维小角度散射 (2D SAS) 对于分析材料结构至关重要.
- 目前的方法在稀疏,杂或不完整的2D SAS数据上扎.
- 重建准确的模式对于定量结构分析至关重要.
研究的目的:
- 介绍一个新的贝叶斯推理框架,用于重建二维SAS模式.
- 从有限的,杂的或部分缺失的数据中实现准确的模式重建.
- 在具有挑战性的实验条件下提高2D SAS技术的应用性.
主要方法:
- 一个贝叶斯推理框架,结合了对称感知角度基础.
- 辐射高斯过程的先验,用于无训练的插值和无声化.
- 计算基准和各种材料的实验验证.
主要成果:
- 从严重减少的数据中可靠地恢复同otropic 和 anisotropic 特性.
- 与原始的2D SAS测量相比,提高了准确度和分辨率.
- 在检测到的中子数量减少多达50倍的情况下,实现了可比的准确性.
结论:
- 该框架允许在低流量,时间有限或一次性条件下进行定量结构分析.
- 将2D SAS的适用性扩展到紧的中子源.
- 有助于研究具有短暂结构变化的软物质系统.
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