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arXiv 0911.3129cond-mat.quant-gascs.NAmath.NA
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一种用于直接最小化带旋转的Gross-Pitaevskii能量的新Sobolev梯度方法

A new Sobolev gradient method for direct minimization of the Gross-Pitaevskii energy with rotation

UPMC Univ Paris 06, UMR 7598, Laboratoire Jacques-Louis Lions(巴黎第六大学,UMR 7598,雅克-路易·利翁斯实验室);CNRS, UMR 7598, Laboratoire Jacques-Louis Lions(法国国家科学研究中心,UMR 7598,雅克-路易·利翁斯实验室)

Ionut Danaila, Parimah Kazemi

AI总结:

本文提出一种新的Sobolev梯度方法,通过定义新的内积和投影处理质量守恒约束,直接最小化带旋转的Gross-Pitaevskii能量,理论证明全局存在性和收敛性,数值实验显示在高旋转速率下优于经典梯度方法。

摘要:

在本文中,我们在两个层面上改进了用于直接最小化带旋转的Gross-Pitaevskii(GP)能量的传统最速下降法。首先,我们定义了一个新的内积来装备Sobolev空间$H^1$并推导出相应的梯度。其次,对于质量守恒约束的处理,我们使用了一种投影方法,避免了基于修正能量泛函或传统归一化方法的更复杂方法。在Hilbert空间框架下,我们对具有这两个新成分的下降方法进行了理论研究,并给出了在渐近极限下全局存在并收敛到GP能量极小元的证明。新方法在有限差分和有限元二维设置中实现,并用于计算旋转玻色-爱因斯坦凝聚体中具有涡旋的各种复杂构型。与经典的$L^2$或$H^1$梯度方法相比,新的Sobolev梯度方法显示出更好的数值性能,特别是在考虑高旋转速率时。

英文摘要:

In this paper we improve traditional steepest descent methods for the direct minimization of the Gross-Pitaevskii (GP) energy with rotation at two levels. We first define a new inner product to equip the Sobolev space $H^1$ and derive the corresponding gradient. Secondly, for the treatment of the mass conservation constraint, we use a projection method that avoids more complicated approaches based on modified energy functionals or traditional normalization methods. The descent method with these two new ingredients is studied theoretically in a Hilbert space setting and we give a proof of the global existence and convergence in the asymptotic limit to a minimizer of the GP energy. The new method is implemented in both finite difference and finite element two-dimensional settings and used to compute various complex configurations with vortices of rotating Bose-Einstein condensates. The new Sobolev gradient method shows better numerical performances compared to classical $L^2$ or $H^1$ gradient methods, especially when high rotation rates are considered.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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