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A recursive extension of the hybrid tetrahedron method for Brillouin-zone integration is proposed, allowing iterative tetrahedron refinement and significantly reducing the error from the linear tetrahedron method. The Brillouin-zone…

Materials Science · Physics 2024-11-27 Kun Dong , Yihao Lin , Xiaoqiang Liu , Jiechao Feng , Ji Feng

Calculations of properties of materials require performing numerical integrals over the Brillouin zone (BZ). Integration points in density functional theory codes are uniformly spread over the BZ (despite integration error being…

Materials Science · Physics 2022-01-25 Jeremy J. Jorgensen , John E. Christensen , Tyler J. Jarvis , Gus L. W. Hart

We present an algorithm for the adaptive tetrahedral integration over the Brillouin zone of crystalline materials, and apply it to compute the optical conductivity, dc conductivity, and thermopower. For these quantities, whose contributions…

Computational Physics · Physics 2016-04-11 E. Assmann , P. Wissgott , J. Kuneš , A. Toschi , P. Blaha , K. Held

We present a new implementation of the k-space interpolation scheme for electronic structure presented by E. L. Shirley, Phys. Rev. B 54, 16464 (1996). The method permits the construction of a compact k-dependent Hamiltonian using a…

Materials Science · Physics 2009-09-10 David Prendergast , Steven G. Louie

The complexity in large-scale optimization can lie in both handling the objective function and handling the constraint set. In this respect, stochastic Frank-Wolfe algorithms occupy a unique position as they alleviate both computational…

Optimization and Control · Mathematics 2021-02-16 Cyrille W. Combettes , Christoph Spiegel , Sebastian Pokutta

We develop a numerical Brillouin-zone integration scheme for real-time propagation of electronic systems with time-dependent density functional theory. This scheme is based on the decomposition of a large simulation into a set of small…

Materials Science · Physics 2021-12-03 Shunsuke A. Sato

Computationally efficient numerical methods for high-order approximations of convolution integrals involving weakly singular kernels find many practical applications including those in the development of fast quadrature methods for…

Numerical Analysis · Mathematics 2018-10-10 Akash Anand , Awanish Kumar Tiwari

This paper investigates the use of stratified sampling as a variance reduction technique for approximating integrals over large dimensional spaces. The accuracy of this method critically depends on the choice of the space partition, the…

Probability · Mathematics 2009-09-15 Pierre Etoré , Gersende Fort , Benjamin Jourdain , Eric Moulines

As the size of quantum devices continues to grow, the development of scalable methods to characterise and diagnose noise is becoming an increasingly important problem. Recent methods have shown how to efficiently estimate Hamiltonians in…

Quantum Physics · Physics 2019-12-18 Tim J. Evans , Robin Harper , Steven T. Flammia

Automatic algorithms attempt to provide approximate solutions that differ from exact solutions by no more than a user-specified error tolerance. This paper describes an automatic, adaptive algorithm for approximating the solution to a…

Numerical Analysis · Mathematics 2018-09-28 Yuhan Ding , Fred J. Hickernell , Lluís Antoni Jiménez Rugama

This paper presents an adaptive discretization strategy for level set topology optimization of structures based on hierarchical B-splines. This work focuses on the influence of the discretization approach and the adaptation strategy on the…

Numerical Analysis · Mathematics 2019-09-25 L. Noel , M. Schmidt , C. Messe , J. A. Evans , K. Maute

Bayesian optimization (BO) has shown impressive results in a variety of applications within low-to-moderate dimensional Euclidean spaces. However, extending BO to high-dimensional settings remains a significant challenge. We address this…

Machine Learning · Statistics 2024-03-11 Shouri Hu , Jiawei Li , Zhibo Cai

Test-time adaptation (TTA) aims to improve model robustness under distribution shifts by adapting to unlabeled test data, but most existing methods rely on backpropagation (BP), which is computationally costly and incompatible with…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Ronghao Zhang , Shuaicheng Niu , Qi Deng , Yanjie Dong , Jian Chen , Runhao Zeng

An efficient gradient-based method to solve the volume constrained topology optimization problems is presented. Each iterate of this algorithm is obtained by the projection of a Barzilai-Borwein step onto the feasible set consisting of box…

Optimization and Control · Mathematics 2010-06-04 Ruhollah Tavakoli , Hongchao Zhang

First principles calculations based on many-electron perturbation theory methods, such as the \textit{ab initio} GW and GW plus Bethe-Salpeter equation (GW-BSE) approach, are reliable ways to predict quasiparticle and optical properties of…

Materials Science · Physics 2017-01-11 Felipe H. da Jornada , Diana Y. Qiu , Steven G. Louie

We introduce a new numerical method for solving time-harmonic acoustic scattering problems. The main focus is on plane waves scattered by smoothly varying material inhomogeneities. The proposed method works for any frequency $\omega$, but…

Numerical Analysis · Mathematics 2022-01-14 Anton Arnold , Sjoerd Geevers , Ilaria Perugia , Dmitry Ponomarev

Brillouin spectroscopy is a powerful optical technique for viscoelastic characterization of samples without contact. However, like all optical systems, Brillouin spectroscopy performances are degraded by optical aberrations, and have…

Optics · Physics 2018-02-09 Eitan Edrei , Giuliano Scarcelli

We present two developments for the numerical integration of a function over the Brillouin zone. First, we introduce a nonuniform grid, which we refer to as the Farey grid, that generalizes regular grids. Second, we introduce…

Other Condensed Matter · Physics 2026-01-21 Siyu Chen , Pascal T. Salzbrenner , Bartomeu Monserrat

In controlled blasting operations, accurately detecting densely distributed tiny boreholes from far-view imagery is critical for operational safety and efficiency. However, existing detection methods often struggle due to small object…

Computer Vision and Pattern Recognition · Computer Science 2025-05-09 Xuesong Liu , Tianyu Hao , Emmett J. Ientilucci

Bayesian Optimization (BO) is a method for globally optimizing black-box functions. While BO has been successfully applied to many scenarios, developing effective BO algorithms that scale to functions with high-dimensional domains is still…

Machine Learning · Computer Science 2024-02-13 Yihang Shen , Carl Kingsford
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