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Electron energy loss spectroscopy (EELS) and X-ray absorption spectroscopy (XAS) provide detailed information about bonding, distributions and locations of atoms, and their coordination numbers and oxidation states. However, analysis of…

Materials Science · Physics 2024-07-11 Samuel P. Gleason , Deyu Lu , Jim Ciston

Chemically exfoliated nanoscale few-layer thin Li$_x$CoO$_2$ samples are studied as function of annealing at various temperatures, using transmission electron microscopy (TEM) and Electron Energy Loss Spectroscopies (EELS), probing the O-K,…

We introduce the skew-spectrum statistic for weak lensing convergence $\kappa$ maps and test it against state-of-the-art high-resolution all-sky numerical simulations. We perform the analysis as a function of source redshift and smoothing…

Cosmology and Nongalactic Astrophysics · Physics 2020-10-14 D. Munshi , T. Namikawa , T. D. Kitching , J. D. McEwen , F. R. Bouchet

The Karhunen-Loeve (KL) transform can compactly represent the information contained in large, complex datasets, cleanly eliminating noise from the data and identifying elements of the dataset with extreme or inconsistent characteristics. We…

Astrophysics of Galaxies · Physics 2015-05-18 Todd A. Boroson , Tod R. Lauer

Kohn-Sham regularizer (KSR) is a differentiable machine learning approach to finding the exchange-correlation functional in Kohn-Sham density functional theory (DFT) that works for strongly correlated systems. Here we test KSR for weak…

Chemical Physics · Physics 2022-03-22 Bhupalee Kalita , Ryan Pederson , Jielun Chen , Li Li , Kieron Burke

We propose a full-wave pseudo-analytical numerical electromagnetic (EM) algorithm to model subsurface induction sensors, traversing planar-layered geological formations of arbitrary EM material anisotropy and loss, which are used, for…

Computational Physics · Physics 2016-04-20 Kamalesh Sainath , Fernando L. Teixeira

We use the Kramers-Kronig transform (KKT) with logarithmic kernel to obtain the reflection phase and, subsequently, the complex refractive index of a bulk mirror from reflectance. However, there remains some confusion regarding the…

Scanning transmission electron microscopy (STEM) has become the technique of choice for quantitative characterization of atomic structure of materials, where the minute displacements of atomic columns from high-symmetry positions can be…

Materials Science · Physics 2021-10-05 Kevin M. Roccapriore , Nicole Creange , Maxim Ziatdinov , Sergei V. Kalinin

The coupling of an electron monochromator (EM) to a mass spectrometer (MS) has created a new analytical technique, EM-MS, for the investigation of electrophilic compounds. This method provides a powerful tool for molecular identification of…

Here a new microscopic method is proposed to image and characterize very thin samples like few-layer materials, organic molecules, and nanostructures with nanometer or sub-nanometer resolution using electron beams of energies lower than 20…

Instrumentation and Detectors · Physics 2016-01-06 Ing-Shouh Hwang

By analyzing ``exact'' theoretical results from solving the time-dependent Schr\"odinger equation of atoms in few-cycle laser pulses, we established the general conclusion that differential elastic scattering and photo-recombination cross…

Atomic Physics · Physics 2008-04-04 Toru Morishita , Anh-Thu Le , Zhangjin Chen , C. D. Lin

We introduce simulations aimed at assessing how well weak gravitational lensing of 21cm radiation from the Epoch of Reionization ($z \sim 8$) can be measured by an SKA-like radio telescope. A simulation pipeline has been implemented to…

Cosmology and Nongalactic Astrophysics · Physics 2017-12-21 Alessandro Romeo , R. Benton Metcalf , Alkistis Pourtsidou

Efficient and accurate low-rank approximation (LRA) methods are of great significance for large-scale data analysis. Randomized tensor decompositions have emerged as powerful tools to meet this need, but most existing methods perform poorly…

Machine Learning · Computer Science 2022-11-29 Yichun Qiu , Weijun Sun , Guoxu Zhou , Qibin Zhao

We propose a Dynamical Low-Rank Ensemble Kalman Filter (DLR-ENKF) for efficient joint state-parameter estimation in high-dimensional dynamical systems. The method extends the DLR-ENKF formulation of arXiv:2509.11210 to the augmented…

Numerical Analysis · Mathematics 2026-02-09 Fabio Nobile , Sébastien Riffaud , Thomas Trigo Trindade

A new iterative image reconstruction algorithm for electrical capacitance tomography (ECT) is proposed that is based on iterative soft thresholding of a total variation penalty and adaptive reweighted compressive sensing. This algorithm…

Computer Vision and Pattern Recognition · Computer Science 2016-11-22 Kezhi Li , Daniel Holland

We update the field-level inference code KARMMA to enable tomographic forward-modelling of shear maps. Our code assumes a lognormal prior on the convergence field, and properly accounts for the cross-covariance in the lensing signal across…

Cosmology and Nongalactic Astrophysics · Physics 2024-03-11 Supranta S. Boruah , Pier Fiedorowicz , Eduardo Rozo

The random equivalent sampling (RES) is a well-known sampling technique that can be used to capture a high-speed repetitive waveform with low sampling rate. In this paper, the feasibility of spectrum-blind multiband signal reconstruction…

Instrumentation and Detectors · Physics 2017-01-10 Yijiu Zhao , Li Wang , Houjun Wang , Changjian Liu

Kolmogorov--Arnold networks (KANs) have demonstrated their potential as an alternative to multi-layer perceptions (MLPs) in various domains, especially for science-related tasks. However, transfer learning of KANs remains a relatively…

Machine Learning · Computer Science 2025-02-17 Yihang Gao , Michael K. Ng , Vincent Y. F. Tan

The motion of electrons under homogeneously applied electric fields in low-dimensional systems with non-zero off-diagonal effective mass (ODEM) is studied. The equation describing the time evolution of a probability coefficient of finding…

Applied Physics · Physics 2025-06-26 Nobuya Mori , Hajime Tanaka , Jo Okada

One of the main problems studied in statistics is the fitting of models. Ideally, we would like to explain a large dataset with as few parameters as possible. There have been numerous attempts at automatizing this process. Most notably, the…

Computation · Statistics 2018-09-24 Marc Härkönen , Tomonari Sei , Yoshihiro Hirose
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