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We propose a simple linear scaling expression in reciprocal space for evaluating the ion--electron potential of crystalline solids. The expression replaces the long-range ion--electron potential with an equivalent localized charge…

Materials Science · Physics 2016-12-21 Xuecheng Shao , Wenhui Mi , Qiang Xu , Yanchao Wang , Yanming Ma

Consider the problem of approximating a given probability distribution on the cube $[0,1]^n$ via the use of a square lattice discretization with mesh-size $1/N$ and the Metropolis algorithm. Here the dimension $n$ is fixed and we focus for…

Probability · Mathematics 2022-02-01 Laurent Saloff-Coste , Sophie Uluatam

The study of polycrystalline materials requires theoretical and computational techniques enabling multiscale investigations. The amplitude expansion of the phase field crystal model (APFC) allows for describing crystal lattice properties on…

Computational Physics · Physics 2019-04-25 Simon Praetorius , Marco Salvalaglio , Axel Voigt

The phase-field crystal (PFC) model describes crystal lattices at diffusive timescales. Its amplitude expansion (APFC) can be applied to the investigation of relatively large systems under some approximations. However, crystal symmetries…

Materials Science · Physics 2023-12-13 Marcello De Donno , Lucas Benoit--Maréchal , Marco Salvalaglio

Rapid solidification leads to unique microstructural features, where a less studied topic is the formation of various crystalline defects, including high dislocation densities, as well as gradients and splitting of the crystalline…

Modeling a crystal as a periodic point set, we present a fingerprint consisting of density functions that facilitates the efficient search for new materials and material properties. We prove invariance under isometries, continuity, and…

Computational Geometry · Computer Science 2021-06-28 Herbert Edelsbrunner , Teresa Heiss , Vitaliy Kurlin , Philip Smith , Mathijs Wintraecken

The known Complex Step Derivative (CSD) method allows easy and accurate differentiation up to machine precision of real analytic functions by evaluating them a small imaginary step next to the real number line. The current paper proposes…

Numerical Analysis · Mathematics 2021-06-18 Martin Roelfs , David Dudal , Daan Huybrechs

Crystalline materials exhibit long-range elastic fields due to the presence of defects, leading to significant domain size effects in atomistic simulations. A rigorous far-field expansion of these long-range fields identifies low-rank…

Numerical Analysis · Mathematics 2024-04-02 Julian Braun , Christoph Ortner , Yangshuai Wang , Lei Zhang

In this article, we design fast algorithms for the computation of approximant bases in shifted Popov normal form. We first recall the algorithm known as PM-Basis, which will be our second fundamental engine after polynomial matrix…

Symbolic Computation · Computer Science 2019-04-09 Claude-Pierre Jeannerod , Vincent Neiger , Gilles Villard

We calculate the leptonic decay constants of heavy-light pseudoscalar mesons with charm and bottom quarks in lattice quantum chromodynamics on four-flavor QCD gauge-field configurations with dynamical $u$, $d$, $s$, and $c$ quarks. We…

Computational prediction of stable crystal structures has a profound impact on the large-scale discovery of novel functional materials. However, predicting the crystal structure solely from a material's composition or formula is a promising…

Materials Science · Physics 2024-04-09 Yuqi Song , Rongzhi Dong , Lai Wei , Qin Li , Jianjun Hu

The PC algorithm is the state-of-the-art algorithm for causal structure discovery on observational data. It can be computationally expensive in the worst case due to the conditional independence tests are performed in an…

Machine Learning · Computer Science 2021-09-13 Kai Zhang , Chao Tian , Kun Zhang , Todd Johnson , Xiaoqian Jiang

Capitalizing on recent advances in lattice QCD, we present a calculation of the leptonic decay constants f_{B_s} and f_{D_s} that includes effects of one strange sea quark and two light sea quarks. The discretization errors of improved…

High Energy Physics - Phenomenology · Physics 2011-01-27 Matthew Wingate , Christine T. H. Davies , Alan Gray , G. Peter Lepage , Junko Shigemitsu

A method is presented to calculate from first principles the higher-order elastic constants of a solid material. The method relies on finite strain deformations, a density functional theory approach to calculate the Cauchy stress tensor,…

Materials Science · Physics 2025-10-08 Ruvini Attanayake , Umesh C. Roy , Abhiyan Pandit , Angelo Bongiorno

Standard procedures for local crystal-structure optimisation involve numerous energy and force calculations. It is common to calculate an energy-volume curve, fitting an equation of state around the equilibrium cell volume. This is a…

Materials Science · Physics 2016-01-26 Adam J. Jackson , Jonathan M. Skelton , Christopher H. Hendon , Keith T. Butler , Aron Walsh

Two-dimensional lead halide perovskites are promising materials for optoelectronics due to the tunability of their properties with the number of lead halide layers and the choice of an organic spacer. Physical understanding for the rational…

An algorithm for determining crystal structures from diffraction data is described which does not rely on the usual Fourier-space formulations of atomicity. The new algorithm implements atomicity constraints in real-space, as well as…

Condensed Matter · Physics 2007-05-23 Veit Elser

In this paper we present the results of a systematic numerical analysis of the channeling properties of electrons and positrons in oriented straight and periodically bent diamond(110) crystals. We analyse dependence of the intensity of the…

Accelerator Physics · Physics 2020-03-31 Alexander V. Pavlov , Andrei V. Korol , Vadim K. Ivanov , Andrey V. Solov'yov

Crystal structures are indispensable across various domains, from batteries to solar cells, and extensive research has been dedicated to predicting their properties based on their atomic configurations. However, prevailing Crystal Structure…

Neural and Evolutionary Computing · Computer Science 2024-06-24 Hannah Janmohamed , Marta Wolinska , Shikha Surana , Thomas Pierrot , Aron Walsh , Antoine Cully

Calculating the log-determinant of a matrix is useful for statistical computations used in machine learning, such as generative learning which uses the log-determinant of the covariance matrix to calculate the log-likelihood of model…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-11-21 Xiaomeng Dong , EN Barnett , Sudarshan K. Dhall