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Scanning probe experiments such as scanning tunneling microscopy (STM) and atomic force microscopy (AFM) on strongly correlated electronic systems often reveal complex pattern formation on multiple length scales. By studying the universal…

Strongly Correlated Electrons · Physics 2019-04-03 L. Burzawa , Shuo Liu , E. W. Carlson

Stable or metastable crystal structures of assembled atoms can be predicted by finding the global or local minima of the energy surface within a broad space of atomic configurations. Generally, this requires repeated first-principles energy…

The electron density of a molecule or material has recently received major attention as a target quantity of machine-learning models. A natural choice to construct a model that yields transferable and linear-scaling predictions is to…

Chemical Physics · Physics 2022-06-29 Andrea Grisafi , Alan M. Lewis , Mariana Rossi , Michele Ceriotti

We report the development of deep learning coherent electron diffractive imaging at sub-angstrom resolution using convolutional neural networks (CNNs) trained with only simulated data. We experimentally demonstrate this method by applying…

Materials Science · Physics 2022-04-19 Dillan J. Chang , Colum M. O'Leary , Cong Su , Salman Kahn , Alex Zettl , Jim Ciston , Peter Ercius , Jianwei Miao

This work presents the new template matching capabilities implemented in Pyxem, an open source Python library for analyzing four-dimensional scanning transmission electron microscopy (4D-STEM) data. Template matching is a brute force…

Recently, variational methods were successfully applied for computing the optical flow in gray and RGB-valued image sequences. A crucial assumption in these models is that pixel-values do not change under transformations. Nowadays, modern…

Optimization and Control · Mathematics 2021-09-06 Manuel Gräf , Sebastian Neumayer , Ralf Hielscher , Gabriele Steidl , Moritz Liesegang , Tilman Beck

Electron beam probe (EBP) is a new principle detector, which makes use of a low-intensity and low-energy electron beam to measure the transverse profile, bunch shape, beam neutralization and beam wake field of an intense beam with small…

Despite advancements in electron backscatter diffraction (EBSD) detector speeds, the acquisition rates of 4-Dimensional (4D) EBSD data, i.e., a collection of 2-dimensional (2D) diffraction maps for every position of a convergent electron…

Signal Processing · Electrical Eng. & Systems 2023-08-02 Zoë Broad , Daniel Nicholls , Jack Wells , Alex W. Robinson , Amirafshar Moshtaghpour , Robert Masters , Louise Hughes , Nigel D. Browning

Electron-phonon coupling (EPC) is fundamental for understanding the behavior of molecules and crystals, influencing phenomena such as charge transport, energy transfer, phase transitions, and polaron formation. Accurate computational…

Chemical Physics · Physics 2025-07-29 Konrad Merkel , Maximilian F. X. Dorfner , Manuel Engel , Georg Kresse , Frank Ortmann

Dielectrically confined Coulomb systems are widely employed in molecular dynamics (MD) simulations. Despite extensive efforts in developing efficient and accurate algorithms for these systems, rigorous and accurate error estimates, which…

Numerical Analysis · Mathematics 2025-03-25 Xuanzhao Gao , Qi Zhou , Zecheng Gan , Jiuyang Liang

4D-STEM-based orientation and phase mapping has enabled rapid microstructure quantification that can be directly combined with standard TEM- and STEM-based imaging modes. Typically, orientation mapping is coupled with beam precession (i.e.…

Materials Science · Physics 2026-04-01 Yichen Yang , Olivier Pierron , Josh Kacher , David Rowenhorst

Ultrasonic backscatter measurements are widely used for microstructural characterisation. However, in materials containing strong anisotropy and spatial heterogeneity, the interpretation of backscatter signals becomes challenging because…

Applied Physics · Physics 2026-05-22 Wei Yi Yeoh , Bo Lan , Michael J. S. Lowe

Based on the cross correlation analysis of the Kikuchi diffraction patterns high-resolution EBSD is a well established method to determine the internal stress in deformed crystalline materials. In many cases, however, the stress values…

Materials Science · Physics 2017-04-05 Szilvia Kalácska , István Groma , András Borbély , Péter Dusan Ispánovity

Serial crystallography experiments routinely produce thousands of diffraction patterns from crystals in random orientations. To turn this stream of images into a usable dataset, each pattern must be indexed before integration and merging…

Computational Physics · Physics 2025-12-01 Marc M Nasser , Frédéric Poitevin , Kevin M Dalton

Estimation of a sparse spectral precision matrix, the inverse of a spectral density matrix, is a canonical problem in frequency-domain analysis of high-dimensional time series (HDTS), with applications in neurosciences and environmental…

Methodology · Statistics 2025-11-11 Navonil Deb , Amy Kuceyeski , Sumanta Basu

Deep metric learning has been widely applied in many computer vision tasks, and recently, it is more attractive in \emph{zero-shot image retrieval and clustering}(ZSRC) where a good embedding is requested such that the unseen classes can be…

Computer Vision and Pattern Recognition · Computer Science 2019-01-23 Binghui Chen , Weihong Deng

The local arrangement of atoms is one of the most important predictors of mechanical and functional properties of materials. However, algorithms for identifying the geometrical arrangements of atoms in complex materials systems are lacking.…

Materials Science · Physics 2019-04-15 Arash Dehghan Banadaki , Jason J. Maldonis , Paul M. Voyles , Srikanth Patala

We present kikuchipy, an open-source toolbox for analysis of electron backscatter diffraction patterns, written in Python. The software is capable of both Hough and dictionary indexing and orientation and/or projection center refinement of…

Motivated by the need to identify erroneous disparity assignments, various approaches for uncertainty and confidence estimation of dense stereo matching have been presented in recent years. As in many other fields, especially deep learning…

Computer Vision and Pattern Recognition · Computer Science 2020-02-11 Max Mehltretter

Crystalline phase structure is essential for understanding the performance and properties of a material. Therefore, this study identified and quantified the crystalline phase structure of a sample based on the diffraction pattern observed…

Materials Science · Physics 2023-09-27 Ryo Murakami , Yoshitaka Matsushita , Kenji Nagata , Hayaru Shouno , Hideki Yoshikawa