arXiv subjects

Yawei Hui

Publications and source records attributed to Yawei Hui.

4 recordsLinked to original sources

arXiv2018

Discovering Features in Sr$_{14}$Cu$_{24}$O$_{41}$ Neutron Single Crystal Diffraction Data by Cluster Analysis

To address the SMC'18 data challenge, "Discovering Features in Sr$_{14}$Cu$_{24}$O$_{41}$", we have used the clustering algorithm "DBSCAN" to separate the diffuse scattering features from the Bragg peaks, which takes into account both spatial and photometric information in the dataset during in the clustering process. We find that, in additional to highly localized Bragg peaks, there exists broad diffuse scattering patterns consisting of distinguishable geometries. Besides these two distinctive features, we also identify a third distinguishable feature submerged in the low signal-to-noise region in the reciprocal space, whose origin remains an open question.

cs.CV↗

arXiv2018

Computer Vision-aided Atom Tracking in STEM Imaging

To address the SMC'17 data challenge -- "Data mining atomically resolved images for material properties", we first used the classic "blob detection" algorithms developed in computer vision to identify all atom centers in each STEM image frame. With the help of nearest neighbor analysis, we then found and labeled every atom center common to all the STEM frames and tracked their movements through the given time interval for both Molybdenum or Selenium atoms.

cs.CV↗

arXiv2017

Volumetric Data Exploration with Machine Learning-Aided Visualization in Neutron Science

Recent advancements in neutron and X-ray sources, instrumentation and data collection modes have significantly increased the experimental data size (which could easily contain 10$^{8}$ -- 10$^{10}$ data points), so that conventional volumetric visualization approaches become inefficient for both still imaging and interactive OpenGL rendition in a 3D setting. We introduce a new approach based on the unsupervised machine learning algorithm, Density-Based Spatial Clustering of Applications with Noise (DBSCAN), to efficiently analyze and visualize large volumetric datasets. Here we present two examples of analyzing and visualizing datasets from the diffuse scattering experiment of a single crystal sample and the tomographic reconstruction of a neutron scanning of a turbine blade. We found that by using the intensity as the weighting factor in the clustering process, DBSCAN becomes very effective in de-noising and feature/boundary detection, and thus enables better visualization of the hierarchical internal structures of the neutron scattering data.

cs.CV↗

arXiv2009

The ion-induced charge-exchange X-ray emission of the Jovian Auroras: Magnetospheric or solar wind origin?

A new and more comprehensive model of charge-exchange induced X-ray emission, due to ions precipitating into the Jovian atmosphere near the poles, has been used to analyze spectral observations made by the Chandra X-ray Observatory. The model includes for the first time carbon ions, in addition to the oxygen and sulfur ions previously considered, in order to account for possible ion origins from both the solar wind and the Jovian magnetosphere. By comparing the model spectra with newly reprocessed Chandra observations, we conclude that carbon ion emission provides a negligible contribution, suggesting that solar wind ions are not responsible for the observed polar X-rays. In addition, results of the model fits to observations support the previously estimated seeding kinetic energies of the precipitating ions (~0.7-2 MeV/u), but infer a different relative sulfur to oxygen abundance ratio for these Chandra observations.

astro-ph.HE↗