• 论文 • 上一篇    

Julia编程语言在材料模拟中的应用

廖明杰, 王浩磊, 张镭   

  1. 上海交通大学数学科学学院, 自然科学研究院, 教育部科学工程计算重点实验室, 上海 200240
  • 收稿日期:2020-12-02 发布日期:2021-03-18
  • 基金资助:
    国家自然科学基金(11871339,11861131004,11571314)资助.

廖明杰, 王浩磊, 张镭. Julia编程语言在材料模拟中的应用[J]. 数值计算与计算机应用, 2021, 42(1): 71-79.

Liao Mingjie, Wang Haolei, Zhang Lei. THE APPLICATION OF JULIA LANGUAGE TO MATERIAL SIMULATION[J]. Journal on Numerica Methods and Computer Applications, 2021, 42(1): 71-79.

THE APPLICATION OF JULIA LANGUAGE TO MATERIAL SIMULATION

Liao Mingjie, Wang Haolei, Zhang Lei   

  1. School of Mathematical Sciences, Institute of Natural Sciences, and MOE-LSC, Shanghai Jiao Tong University, Shanghai 200240, China
  • Received:2020-12-02 Published:2021-03-18
Julia是一种快速、易用、开源、动态的编程语言,在近年来得到了迅猛发展,尤其适用于科学计算.本文简单介绍Julia语言的重要特性如类型稳定性和多重分派等,并以原子模拟软件包JuLIP为例,介绍Julia语言在材料模拟中的应用.我们通过两个典型应用,二维/三维无序材料的建模和二维晶体固体中的波动传播,来展示利用JuLIP进行材料建模和功能扩展的过程.
Julia, a fast, easy to use, open source, dynamic programming language, has been dramatically developed in recent years, and is especially suitable for scientific computing. In this paper, we briefly introduce the important features such as type stability and multi-dispatch of Julia language, and take JuLIP, a pure Julia package for materials simulation as an outstanding example to demonstrate the application of Julia language in materials modeling. We show two material applications which can be easily accomplished by extensions of the JuLIP packages, namely, the quasi-static evolution of 2d/3d disorder materials and wave propagation of 2d crystalline solid.

MR(2010)主题分类: 

()
[1] Bezanson J, Edelman A, Karpinski S, et al. Julia:A fresh approach to numerical computing[J]. SIAM review, 2017, 59(1):65-98.
[2] Bezanson J, Karpinsky S, Shah V B, et al. Julia:A fast dynamic language for technical computing[J]. Preprint, arXiv:1209.51452012.
[3] Bezanson J, Karpinski S, Shah V B, Edelman A. Why We Created Julia[EB]. https://julialang.org/blog/2012/02/why-we-created-julia-zhCN
[4] Chen H J, Liao M J, Wang H, Wang Y S, Zhang L. Adaptive QM/MM coupling for crystalline defects[J]. Comput. Methods Appl. Mech. Engrg., 2019, 354:351-368.
[5] Fichtner A, Zunino A, Gebraad L. Hamiltonian Monta Carlo solution of tomographic inverse problems[J]. Geophys. J. Int., 2019, 216(2); 1344-1363.
[6] Frost JM. Calculation polaron mobility in halide perovskites[J]. Phys. Rev. B., 2017, 96.
[7] Foreman-Mackey D, Agol E, Ambikasaran S, et al. Fast and scalable Gaussian process modeling with applications to astronomical time series[J]. Astron. J., 2017, 154.
[8] Wang H, Liao M, Lin P, Zhang L. A posteriori error estimation and adaptive algorithm for the atomistic/continuum coupling in two dimensions[J]. SIAM J. Sci. Comput., 2018, 40(4):A2087A2119
[9] Johnson K L, Johnson K L. Contact mechanics[M]. Cambridge university press, 1987.
[10] Linton NM, Kobayashi T, Yang Y C, et al. Incubation period and other epidemiological characteristics of 2019 novel coronavirus infections with right truncation:A statistical analysis of publicly available case data[J]. J. Clin. Med., 2020, 538.
[11] Mones L, Ortner C, Csányi G. Preconditioners for the geometry optimisation and saddle point search of molecular systems[J]. Scientific reports, 2018, 8(1):13991.
[12] Park H, Karpov E, Liu W K, Klein P. The bridging scale for two-dimensional atomistic/continuum coupling. Philos. Mag., 2005, 85(1):79-113.
[13] Pich O, Muinos F, Lolkema M P, et al. The mutational footprints of cancer therapies[J]. Nat. Genet., 2019, 51(12):1732-1740.
[14] Perkel J M. Julia:come for the syntax, stay for the speed[J]. Nature, 2019, 572:141-142.
[15] Thiebaut E, Young J. Principles of image reconstruction in optical interferometry:tutorial[J]. J. Opt. Soc. Am. A., 2017, 34(6):904-923.
[16] Vicentini F, Biella A, Regnault N, etal. Variational neural-network ansatz for steady states in open quantum systems[J]. Phys. Rev. Lett., 2019, 122.
[17] 王浩磊,张镭. 三维颗粒物质的能量最小化模拟方法[J], 数值计算与计算机应用, 2021, 42(1):80-90.
No related articles found!
阅读次数
全文


摘要