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Numerical modeling of wave propagation in heterogeneous media is important in many applications. Due to the complex nature, direct numerical simulations on the fine grid are prohibitively expensive. It is therefore important to develop…

Numerical Analysis · Mathematics 2016-11-26 Eric T. Chung , Yalchin Efendiev , Wing Tat Leung

We apply a recently developed quasiparticle self-consistent $GW$ method (QSGW) to Gd, Er, EuN, GdN, ErAs, YbN and GdAs. We show that QSGW combines advantages separately found in conventional $GW$ and LDA+$U$ theory, in a simple and fully…

Materials Science · Physics 2007-11-10 Athanasios N. Chantis , Mark van Schilfgaarde , Takao Kotani

Rue and Held (2005) proposed a method for efficiently computing the Gaussian likelihood for stationary Markov random field models, when the data locations fall on a complete regular grid, and the model has no additive error term. The…

Computation · Statistics 2019-12-16 Joseph Guinness , Ilse C. F. Ipsen

A Continuous Galerkin method-based approach is presented to compute the seismic normal modes of rotating planets. Special care is taken to separate out the essential spectrum in the presence of a fluid outer core using a polynomial…

Computational Physics · Physics 2021-09-28 Jia Shi , Ruipeng Li , Yuanzhe Xi , Yousef Saad , Maarten V. de Hoop

We present a spectral scheme for atomic structure calculations in pseudopotential Kohn-Sham density functional theory. In particular, after applying an exponential transformation of the radial coordinates, we employ global polynomial…

Computational Physics · Physics 2024-06-07 Sayan Bhowmik , John E. Pask , Andrew J. Medford , Phanish Suryanarayana

Kernel methods for solving partial differential equations on surfaces have the advantage that those methods work intrinsically on the surface and yield high approximation rates if the solution to the partial differential equation is smooth…

Numerical Analysis · Mathematics 2024-10-04 Thomas Hangelbroek , Christian Rieger

Spectral approximation and variational inducing learning for the Gaussian process are two popular methods to reduce computational complexity. However, in previous research, those methods always tend to adopt the orthonormal basis functions,…

Machine Learning · Statistics 2021-07-15 Wenqi Fang , Guanlin Wu , Jingjing Li , Zheng Wang , Jiang Cao , Yang Ping

A new approach to large-scale nuclear structure calculations, based on the Density Matrix Renormalization Group (DMRG), is described. The method is tested in the context of a problem involving many identical nucleons constrained to move in…

Nuclear Theory · Physics 2011-05-12 J. Dukelsky , S. Pittel

We present a novel formulation of the vibrational density matrix renormalization group (vDMRG) algorithm tailored to strongly anharmonic molecules described by general high-dimensional model representations of potential energy surfaces. For…

Chemical Physics · Physics 2023-12-29 Nina Glaser , Alberto Baiardi , Markus Reiher

We present a subspace projection technique to conduct large-scale Kohn-Sham density functional theory calculations using spectral finite-element discretization. The proposed method treats both metallic and insulating materials in a single…

Computational Physics · Physics 2015-10-26 Phani Motamarri , Vikram Gavini

We study the intermediate statistics of the spectrum of quasi-energies and of the eigenfunctions in the kicked rotator, in the case when the corresponding system is fully chaotic while quantally localized. As for the eigenphases, we find…

Chaotic Dynamics · Physics 2013-09-03 Thanos Manos , Marko Robnik

This paper presents an efficient spectral method for solving the fractional Fredholm integro-differential equations. The non-smoothness of the solutions to such problems leads to the performance of spectral methods based on the classical…

Numerical Analysis · Mathematics 2022-09-23 Y. Talaei , S. Noeiaghdam , H. Hosseinzadeh

Variational approaches for the calculation of vibrational wave functions and energies are a natural route to obtain highly accurate results with controllable errors. However, the unfavorable scaling and the resulting high computational cost…

Chemical Physics · Physics 2017-08-14 Alberto Baiardi , Christopher J. Stein , Vincenzo Barone , Markus Reiher

This work is concerned with the construction of Gaussian Beam (GB) solutions for the numerical approximation of wave equations, semi-discretized in space by finite difference schemes. GB are high-frequency solutions whose propagation can be…

Analysis of PDEs · Mathematics 2023-06-12 Umberto Biccari , Enrique Zuazua

We develop a spectral method for solving univariate singular integral equations over unions of intervals by utilizing Chebyshev and ultraspherical polynomials to reformulate the equations as almost-banded infinite-dimensional systems. This…

Numerical Analysis · Mathematics 2016-12-12 Richard Mikael Slevinsky , Sheehan Olver

Most numerical schemes proposed for solving BGK models for rarefied gas dynamics are based on the discrete velocity approximation. Since such approach uses fixed velocity grids, one must secure a sufficiently large domain with fine velocity…

Numerical Analysis · Mathematics 2022-04-20 Sebastiano Boscarino , Seung Yeon Cho , Giovanni Russo

We present the second-order multidimensional Staggered Grid Hydrodynamics Residual Distribution (SGH RD) scheme for Lagrangian hydrodynamics. The SGH RD scheme is based on the staggered finite element discretizations as in [Dobrev et al.,…

Numerical Analysis · Mathematics 2018-11-02 R. Abgrall , K. Lipnikov , N. Morgan , S. Tokareva

This paper is devoted to the study of generalized subdifferentials of spectral functions over Euclidean Jordan algebras. Spectral functions appear often in optimization problems playing the role of "regularizer", "barrier", "penalty…

Optimization and Control · Mathematics 2021-09-27 Bruno F. Lourenço , Akiko Takeda

We describe a method for imposing the correct electron-nucleus (e-n) cusp in molecular orbitals expanded as a linear combination of (cuspless) Gaussian basis functions. Enforcing the e-n cusp in trial wave functions is an important asset in…

Chemical Physics · Physics 2020-06-05 Pierre-François Loos , Anthony Scemama , Michel Caffarel

We study linear spectral statistics of high dimensional sample covariance matrices in a regime where the empirical spectral distribution remains governed by the classical sample covariance law but the fluctuation theory is nonclassical. Our…

Statistics Theory · Mathematics 2026-05-13 Yanqing Yin , Wang Zhou
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