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为提高传统光滑粒子动力学(SPH)方法求解高维非线性薛定谔(nonlinear Schrödinger/Gross-Pitaevskii equation, NLS/GP)方程的数值精度和计算效率, 本文首先基于高阶时间分裂思想将非线性薛定谔方程分解成线性导数项和非线性项, 其次拓展一阶对称SPH方法对复数域上线性导数部分进行显式求解, 最后引入MPI并行技术, 结合边界施加虚粒子方法给出一种能够准确、高效地求解高维NLS/GP方程的高阶分裂修正并行SPH方法. 数值模拟中, 首先对带有周期性和Dirichlet边界条件的NLS方程进行求解, 并与解析解做对比, 准确地得到了周期边界下孤立波的奇异性, 且对提出方法的数值精度、收敛速度和计算效率进行了分析; 随后, 运用给出的高阶分裂粒子方法对复杂二维和三维NLS/GP问题进行了数值预测, 并与其他数值结果进行比较, 准确地展现了非线性孤立波传播中的奇异现象和玻色-爱因斯坦凝聚态中带外旋转项的量子涡旋变化过程.
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关键词:
- 非线性薛定谔方程/
- 光滑粒子动力学/
- 时间分裂/
- 玻色-爱因斯坦凝聚态
To improve the numerical accuracy and computational efficiency of solving high-dimensional nonlinear Schrödinger/Gross-Pitaevskii (NLS/GP) equation by using traditional SPH method, a high-order split-step coupled with a corrected parallel SPH (HSS-CPSPH) method is developed by applying virtual particles to the boundary. The improvements are described as follows. Firstly, the nonlinear Schrödinger equation is divided into linear derivative term and nonlinear term based on the high-order split-step method. Then, the linear derivative term is solved by extending the first-order symmetric SPH method in explicit time integration. Meanwhile, the MPI parallel technique is introduced to enhance the computational efficiency. In this work, the accuracy, convergence and the computational efficiency of the proposed method are tested by solving the NLS equations with the periodic and Dirichlet boundary conditions, and compared with the analytical solutions. Also, the singularity of solitary waves under the periodic boundary condition is accurately obtained using the proposed particle method. Subsequently, the proposed HSS-CPSPH method is used to predict the results of complex two-dimensional and three-dimensioanl GP problems which are compared with other numerical results. The phenomenon of singular sharp angle in the propagation of nonlinear solitary wave and the process of quantum vortex under Bose-Einstein condensates with external rotation are presented accurately.-
Keywords:
- nonlinear Schrödinger equation/
- smoothed particle hydrodynamics/
- time split-step/
- Bose-Einstein condensates
[1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] [21] [22] [23] [24] [25] [26] -
时间t SS-ICPSPH HSS-CPSPH 0.5 1.697 × 10–3 1.696 × 10–3 1 3.616 × 10–3 2.494 × 10–3 2 7.347 × 10–3 4.857 × 10–3 
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$h = {\text{π}}/32$ $h = {\text{π}}/64$ $h = {\text{π}}/128$ ${e_{\rm{m}}}$ $o{r_{\rm{\alpha }}}$ ${e_{\rm{m}}}$ $o{r_{\rm{\alpha }}}$ ${e_{\rm{m}}}$ $o{r_{\rm{\alpha }}}$ SS-ICPSPH 1.381 × 10–2 — 3.616 × 10–3 1.933 9.0412 × 10–4 2.00 HSS-CPSPH 1.381 × 10–2 — 2.494 × 10–3 2.47 4.498 × 10–4 2.47 下载:
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均匀分布粒子 非均匀分布情形1 非均匀分布情形2 $t = 0.1$ $t = 1$ $t = 0.1$ $t = 1$ $t = 0.1$ $t = 1$ SS-ICPSPH 2.776 × 10–4 3.616 × 10–3 2.944 × 10–4 3.818 × 10–3 3.116 × 10–4 4.082 × 10–3 HSS-CPSPH 2.774 × 10–4 2.494 × 10–3 2.886 × 10–4 2.527 × 10–3 2.967 × 10–4 2.578 × 10–3 下载:
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时间t SS-ICPSPH HSS-CPSPH 0.5 9.131 × 10–4 4.512 × 10–4 1 1.828 × 10–3 8.135 × 10–4 2 3.658 × 10–3 1.623 × 10–3 下载:
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$h = {\text{π}}/32$ $h = {\text{π}}/64$ $h = {\text{π}}/128$ ${e_{\rm{m}}}$ $o{r_{\rm{\alpha }}}$ ${e_{\rm{m}}}$ $o{r_{\rm{\alpha }}}$ ${e_{\rm{m}}}$ $o{r_{\rm{\alpha }}}$ SS-ICPSPH 7.553 × 10–3 — 1.828 × 10–3 2.046 4.316 × 10–4 2.082 HSS-CPSPH 4.534 × 10–3 — 8.135 × 10–4 2.476 1.379 × 10–4 2.560 下载:
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CPU数量 步数 相对加速比S num= 1 num= 10 num= 1000 2 97805.9 107508 1174728 — 12 16716.9 18516.7 215526.7 — 24 8388.87 9404.37 120284.37 1.792 36 5603.29 6344.98 87524.98 2.462 72 2948.83 3189.24 48564.28 4.438 下载:
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粒子数 CPU数量 2 12 24 36 72 ${121^3}$ 449.55 82.926 45.962 35.000 19.585 ${161^3}$ 1076.922 198.810 111.90 81.922 47.363 ${181^3}$ 1558.445 292.711 164.838 120.886 65.437 ${201^3}$ 2190.921 425.688 235.775 179.856 96.836 下载:
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[1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] [21] [22] [23] [24] [25] [26]
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