Efficient manipulation of Bose–Einstein Condensates in a double-well potential
Efficient manipulation of Bose–Einstein Condensates in a double-well potential
复制标题
双势阱中玻色爱因斯坦凝聚的高效操控
DOI：
10.1016/j.cnsns.2023.107219
复制
发表时间：
2023
影响因子：
3.9
通讯作者：
Kevrekidis, Panayotis
中科院分区：
文献类型：
--
作者：
Adriazola, Jimmie;Goodman, Roy;Kevrekidis, Panayotis
我们提出了一个问题的转移玻色爱因斯坦凝聚（BEC）从一个双势阱的一侧到另一侧作为一个最优控制问题，以确定时间依赖的形式的潜力。我们推导出一个减少的动力系统，使用Galerkin截断到一组有限的特征函数，并发现includingthreemodes足以有效地控制全动态，所描述的BEC的Gross-Pitaevskii模型。的功能形式的控制减少到有限的尺寸，通过使用另一个Galerkin型的方法称为斩波随机基（CRAB）的方法，然后优化的遗传算法称为差分进化（DE）。最后，我们讨论了在何种程度上减少为基础的最优控制策略，可以通过包括更多的模式在Galerkin减少。
We pose the problem of transferring a Bose–Einstein Condensate (BEC) from one side of a double-well potential to the other as an optimal control problem for determining the time-dependent form of the potential. We derive a reduced dynamical system using a Galerkin truncation onto a finite set of eigenfunctions and find that includingthreemodes suffices to effectively control the full dynamics, described by the Gross–Pitaevskii model of BEC. The functional form of the control is reduced to finite dimensions by using another Galerkin-type method called the chopped random basis (CRAB) method, which is then optimized by a genetic algorithm called differential evolution (DE). Finally, we discuss the extent to which the reduction-based optimal control strategy can be refined by means of including more modes in the Galerkin reduction.