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Modeling the Gross-Pitaevskii Equation Using the Quantum Lattice Gas Method

机译:使用量子格子气体方法对Gross-Pitaevskii方程建模

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摘要

We present an improved Quantum Lattice Gas (QLG) algorithm as a mesoscopic unitary perturbative representation of the mean field Gross Pitaevskii (GP) equation for Bose--Einstein Condensates (BECs). The method employs an interleaved sequence of unitary collide and stream operators. QLG is applicable to many different scalar potentials in the weak interaction regime and has been used to model the Korteweg--de Vries (KdV), Burgers and GP equations. It can be implemented on both quantum and classical computers and is extremely scalable. We present results for 1D soliton solutions with positive and negative internal interactions, as well as vector solitons with inelastic scattering. In higher dimensions we look at the behavior of vortex ring reconnection. A further improvement is considered with a proper operator splitting technique via a Fourier transformation. This is great for quantum computers since the quantum FFT is exponentially faster than its classical counterpart which involves non-local data on the entire lattice (Quantum FFT is the backbone of the Shor algorithm for quantum factorization). We also present an imaginary time method in which we transform the Schrodinger equation into a diffusion equation for recovering ground state initial conditions of a quantum system suitable for the QLG algorithm.
机译:我们提出了一种改进的量子格子气体(QLG)算法,作为玻色-爱因斯坦凝聚物(BEC)的平均场Gross Pitaevskii(GP)方程的介观unit微扰表示。该方法采用单一碰撞和流运算符的交错序列。 QLG适用于弱相互作用机制中的许多不同标量势,并已用于建模Korteweg-de Vries(KdV),Burgers和GP方程。它可以在量子计算机和经典计算机上实现,并且具有极高的可扩展性。我们提出了具有正负内部相互作用的一维孤子解的结果,以及具有非弹性散射的矢量孤子。在更高的维度中,我们研究了涡环重新连接的行为。考虑通过适当的算子拆分技术通过傅里叶变换进行进一步的改进。这对于量子计算机来说非常有用,因为量子FFT的速度比传统的指数FFT快得多,经典的经典FFT涉及整个晶格中的非本地数据(量子FFT是Shor算法进行量子分解的基础)。我们还提出了一种虚构的时间方法,其中我们将Schrodinger方程转换为扩散方程,以恢复适合QLG算法的量子系统的基态初始条件。

著录项

  • 作者

    Oganesov, Armen.;

  • 作者单位

    The College of William and Mary.;

  • 授予单位 The College of William and Mary.;
  • 学科 Physics.
  • 学位 Ph.D.
  • 年度 2018
  • 页码 120 p.
  • 总页数 120
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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