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Electron backscatter diffraction (EBSD) in the scanning electron microscope is routinely used for microstructural characterisation of polycrystalline materials. Maps of EBSD data are typically acquired at high stage tilt and slow scan…

Materials Science · Physics 2020-09-01 Vivian Tong , Thomas Benjamin Britton

A computational method is developed whereby the reflectivity of low-energy electrons from a surface can be obtained from a first-principles solution of the electronic structure of the system. The method is applied to multilayer graphene.…

Mesoscale and Nanoscale Physics · Physics 2014-01-21 R. M. Feenstra , M. Widom

Detecting weak target is an important and challenging problem in many applications such as radar, sonar etc. However, conventional detection methods are often ineffective in this case because of low signal-to-noise ratio (SNR). This paper…

Signal Processing · Electrical Eng. & Systems 2023-09-26 Jin Lu , Guojie Peng , Weichuan Zhang , Changming Sun

Photoelectron diffraction (PED) is a powerful spectroscopic technique that combines elemental resolution with a high sensitivity to the local atomic arrangement at crystal surfaces, thus providing unique fingerprints of selected atomic…

A simple procedure is developed to simultaneously eliminate multiple scattering contributions from two reflection electron energy loss spectra (REELS) measured at different energies or for different experimental geometrical configurations.…

Materials Science · Physics 2009-11-11 Wolfgang S. M. Werner

We present a solver for the 2D high-frequency Helmholtz equation in heterogeneous, constant density, acoustic media, with online parallel complexity that scales empirically as $\mathcal{O}(\frac{N}{P})$, where $N$ is the number of volume…

Numerical Analysis · Mathematics 2017-01-03 Leonardo Zepeda-Núñez , Laurent Demanet

Near total reflection regime has been widely used in X-ray science, specifically in grazing incidence small angle X-ray scattering and in hard X-ray photoelectron spectroscopy. In this work, we introduce some practical aspects of using near…

We propose a physics-informed consistency modeling framework for solving partial differential equations (PDEs) via fast, few-step generative inference. We identify a key stability challenge in physics-constrained consistency training, where…

Machine Learning · Computer Science 2026-02-11 Che-Chia Chang , Chen-Yang Dai , Te-Sheng Lin , Ming-Chih Lai , Chieh-Hsin Lai

A diffuse-interface model for microstructure with an arbitrary number of components and phases was developed from basic thermodynamic and kinetic principles and formalized within a variational framework. The model includes a composition…

Materials Science · Physics 2011-07-28 Daniel A. Cogswell , W. Craig Carter

A method for the calculation of the damping rate due to electron-hole pair excitation for atomic and molecular motion at metal surfaces is presented. The theoretical basis is provided by Time Dependent Density Functional Theory (TDDFT) in…

Computational Physics · Physics 2015-05-14 J. R. Trail , M. C. Graham , D. M. Bird

This article presents a higher-order spectral element method for the two-dimensional Stokes interface problem involving a piecewise constant viscosity coefficient. The proposed numerical formulation is based on least-squares formulation.…

Numerical Analysis · Mathematics 2025-08-14 Kishore Kumar Naraparaju , Shivangi Joshi , Subhashree Mohapatra

Highly overmoded and periodically loaded structures, such as the iris-line waveguide, offer an attractive solution for the efficient transportation of diffraction-prone THz pulses over long distances (hundreds of meters). This paper…

Accelerator Physics · Physics 2025-12-16 Adham Naji , Pawan Kumar Gupta , Gennady Stupakov

This paper investigates the inverse biharmonic scattering problems of identifying the shape and location of the obstacle with phased and phaseless measurement data. A direct imaging method based on reverse time migration is proposed for…

Analysis of PDEs · Mathematics 2026-05-12 Tielei Zhu , Zhihao Ge

We propose a method of measuring topological invariants of a photonic crystal through phase spectroscopy. We show how the Chern numbers can be deduced from the winding numbers of the reflection coefficient phase. An explicit proof of…

Mesoscale and Nanoscale Physics · Physics 2015-05-20 A. V. Poshakinskiy , A. N. Poddubny , M. Hafezi

Two-dimensional (2D) fluorescence-excitation (2D-FLEX) spectroscopy is a recently proposed nonlinear femtosecond technique for the detection of photoinduced dynamics. The method records a time-resolved fluorescence signal in its excitation-…

Chemical Physics · Physics 2024-06-24 Sebastian V. Pios , Maxim F. Gelin , Luis Vasquez , Jürgen Hauer , Lipeng Chen

Understanding the local fracture resistance of microstructural features. such as brittle inclusions, coatings, and interfaces at the microscale under complex loading conditions is critical for microstructure-informed design of materials. In…

Diffraction of light at lateral inhomogenities is a central process in the near-field studies of nanoscale phenomena, especially the propagation of surface waves. Theoretical description of this process is extremely challenging due to…

Mesoscale and Nanoscale Physics · Physics 2021-02-24 Egor Nikulin , Denis Bandurin , Dmitry Svintsov

We describe a method that uses total internal reflection at the water-air interface inside a large, transparent tank, to measure the interface's deflections. Using this configuration, we obtain an optical set-up where the liquid surface…

Fluid Dynamics · Physics 2021-10-26 Utkarsh Jain , Anaïs Gauthier , Devaraj van der Meer

Finding meaningful distances between high-dimensional data samples is an important scientific task. To this end, we propose a new tree-Wasserstein distance (TWD) for high-dimensional data with two key aspects. First, our TWD is specifically…

Machine Learning · Computer Science 2025-02-25 Ya-Wei Eileen Lin , Ronald R. Coifman , Gal Mishne , Ronen Talmon

Representation learning often plays a critical role in reinforcement learning by managing the curse of dimensionality. A representative class of algorithms exploits a spectral decomposition of the stochastic transition dynamics to construct…

Machine Learning · Computer Science 2023-03-08 Tongzheng Ren , Tianjun Zhang , Lisa Lee , Joseph E. Gonzalez , Dale Schuurmans , Bo Dai