Comparing, optimizing, and benchmarking quantum-control algorithms in a unifying programming framework
Comparing, optimizing, and benchmarking quantum-control algorithms in a unifying programming framework
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DOI：
10.1103/physreva.84.022305
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发表时间：
2011-08-03
影响因子：
2.9
通讯作者：
Schulte-Herbrueggen, T.
中科院分区：
文献类型：
--
作者：
Machnes, S.;Sander, U.;Schulte-Herbrueggen, T.
为了为量子模拟、计算和技术中的新应用铺平道路，越来越大的量子系统必须以高精度进行控制。这是一个典型的任务，服从数字最优控制，以扭转脉冲的时间进程，即，分段恒定的控制振幅，迭代成优化的形状。在这里，我们提出了一个比较研究的最优控制算法的范围广泛的有限维应用。我们专注于最常用的算法：GRAPE方法，同时更新所有控件，和Krotov类型的方法，这样做的顺序。他们的使用准则，并指出开放的研究问题。此外，我们介绍了一个统一的算法框架，动态优化平台，旨在为量子技术社区提供一个方便的基于MATLAB的工具集的最优控制。此外，它还为最优控制技术的研究人员提供了一个框架，用于对新提出的算法进行基准测试和比较，并将其与最先进的算法进行比较。它允许采用各种类型的梯度、更新和步长方法以及子空间选择的混合匹配方法。包括示例在内的开放源代码可在http://qlib.info上获得。
For paving the way to novel applications in quantum simulation, computation, and technology, increasingly large quantum systems have to be steered with high precision. It is a typical task amenable to numerical optimal control to turn the time course of pulses, i.e., piecewise constant control amplitudes, iteratively into an optimized shape. Here, we present a comparative study of optimal-control algorithms for a wide range of finite-dimensional applications. We focus on the most commonly used algorithms: GRAPE methods which update all controls concurrently, and Krotov-type methods which do so sequentially. Guidelines for their use are given and open research questions are pointed out. Moreover, we introduce a unifying algorithmic framework, DYNAMO (dynamic optimization platform), designed to provide the quantum-technology community with a convenient MATLAB-based tool set for optimal control. In addition, it gives researchers in optimal-control techniques a framework for benchmarking and comparing newly proposed algorithms with the state of the art. It allows a mix-and-match approach with various types of gradients, update and step-size methods as well as subspace choices. Open-source code including examples is made available at http://qlib.info.