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We use complementary optical spectroscopy methods to directly measure the lowest crystal-field energies of the rare-earth quantum magnet LiY$_{1-x}$Ho$_{x}$F$_{4}$, including their hyperfine splittings, with more than 10 times higher…

With a particular focus on Scipy's minimize function the eclipse mapping method is thoroughly researched and implemented utilizing Python and essential libraries. Many optimization techniques are used, including Sequential Least Squares…

Instrumentation and Methods for Astrophysics · Physics 2024-06-04 Anoop Kumar , Madan Mohan Tito Ayyalasomayajula , Dheerendra Panwar , Yeshwanth Vasa

Crystalline defects critically influence material properties, necessitating accurate simulation methods. Existing approaches, from atomic-scale configurations to continuum elasticity, face inherent limitations in modeling…

Materials Science · Physics 2025-10-09 Xinyi Wei , Yangshuai Wang , Kai Jiang , Lei Zhang

We describe a computer application designed to analyze hyperspectral data collected by the Compact Infrared Spectrometer for Mars (CRISM). The application links the spectral, imaging and mapping perspectives on the eventual CRISM dataset by…

Instrumentation and Methods for Astrophysics · Physics 2014-01-29 Adrian J. Brown , Michael Storrie-Lombardi

Over the past decade, cryogenic electron microscopy (cryo-EM) has emerged as a primary method for determining near-native, near-atomic resolution 3D structures of biological macromolecules. In order to meet increasing demand for cryo-EM,…

Image and Video Processing · Electrical Eng. & Systems 2022-01-19 Paul T. Kim , Alex J. Noble , Anchi Cheng , Tristan Bepler

Dataset distillation has emerged as a powerful approach for reducing data requirements in deep learning. Among various methods, distribution matching-based approaches stand out for their balance of computational efficiency and strong…

Computer Vision and Pattern Recognition · Computer Science 2025-03-03 Shaobo Wang , Yicun Yang , Zhiyuan Liu , Chenghao Sun , Xuming Hu , Conghui He , Linfeng Zhang

Despite their success, kernel methods suffer from a massive computational cost in practice. In this paper, in lieu of commonly used kernel expansion with respect to $N$ inputs, we develop a novel optimal design maximizing the entropy among…

Machine Learning · Computer Science 2020-02-12 Liang Ding , Rui Tuo , Shahin Shahrampour

Advances on cryo-electron imaging technologies have led to a rapidly increasing number of density maps. Alignment and comparison of density maps play a crucial role in interpreting structural information, such as conformational…

Computer Vision and Pattern Recognition · Computer Science 2023-09-19 Bintao He , Fa Zhang , Chenjie Feng , Jianyi Yang , Xin Gao , Renmin Han

The development of coarse-grained (CG) molecular models typically requires a time-consuming iterative tuning of parameters in order to have the approximated CG models behaving correctly and consistently with, e.g., available…

The effective crystal field Hamiltonian provides the key description of the electronic properties of single-ion magnets, but obtaining its parameters from ab initio computation is challenging. We introduce a simple approach to derive the…

Global optimization of crystal compositions is a significant yet computationally intensive method to identify stable structures within chemical space. The specific physical properties linked to a three-dimensional atomic arrangement make…

A simple method for constructing effective Hamiltonians for the 4fN and 4fN-15d energy levels of lanthanide ions in crystals from quantum-chemical calculations is presented. The method is demonstrated by deriving crystal-field and…

Materials Science · Physics 2012-01-25 L. Hu , M. F. Reid , C. K. Duan , S. Xia , M. Yin

Cryo-electron microscopy (cryo-EM) extracts single-particle density projections of individual biomolecules. Although cryo-EM is widely used for 3D reconstruction, due to its single-particle nature, it has the potential to provide…

Closed-loop field development (CLFD) optimization is a comprehensive framework for optimal development of subsurface resources. CLFD involves three major steps: 1) optimization of full development plan based on current set of models, 2)…

Optimization and Control · Mathematics 2019-04-03 Mehrdad G Shirangi

Crystal structure prediction (CSP) stands as a powerful tool in materials science, driving the discovery and design of innovative materials. However, existing CSP methods heavily rely on formation enthalpies derived from density functional…

Materials Science · Physics 2025-07-16 Chenglong Qin , Jinde Liu , Shiyin Ma , Jiguang Du , Gang Jiang , Liang Zhao

In this paper, we attempt to explore the landscape of two-dimensional conformal field theories (2d CFTs) by efficiently searching for numerical solutions to the modular bootstrap equation using machine-learning-style optimization. The torus…

High Energy Physics - Theory · Physics 2026-05-05 Nathan Benjamin , A. Liam Fitzpatrick , Wei Li , Jesse Thaler

The analysis of ultrafast electron diffraction (UED) data from low-symmetry single crystals of small molecules is often challenged by the difficulty of assigning unique Laue indices to the observed Bragg reflections. For a variety of…

Materials Science · Physics 2025-06-30 Alexander Marx , Sascha W. Epp

The PySCF package has emerged as a powerful and flexible open-source platform for quantum chemistry simulations. However, the efficiency of electronic structure calculations can vary significantly depending on the choice of computational…

Chemical Physics · Physics 2025-06-10 Zhichen Pu , Qiming Sun

X-ray diffraction (XRD) is an essential technique to determine a material's crystal structure in high-throughput experimentation, and has recently been incorporated in artificially intelligent agents in autonomous scientific discovery…

In silico design and optimization of new materials primarily relies on high-accuracy atomic simulators that perform density functional theory (DFT) calculations. While recent works showcase the strong potential of machine learning to…

Machine Learning · Computer Science 2025-09-30 Prashant Govindarajan , Mathieu Reymond , Antoine Clavaud , Mariano Phielipp , Santiago Miret , Sarath Chandar