Machine learning for Robust control of Quantum systems

该项目将建立在Irtaza Khalid的工作基础上，Irtaza Khalid是卡迪夫的最后一年博士生，关于机器学习的鲁棒控制，这将在重叠部分进一步讨论。该项目的主要目的是开发机器学习算法/模型，以将鲁棒控制应用于物理量子系统。这些模型将控制的具体系统将在项目开始时确定，但系统的一个例子可能是该项目的主要主管旨在建立的冷原子系统。如果选择了这一点，并且系统在该项目结束时可以运行，那么这些模型的输出将在这些量子系统上进行测试。如果不是这种情况，那么这些模型的结果可以应用于其他系统，而不是通过联系Alex Clark博士等实验学者并请求访问他的量子存储器系统或其他适用的量子系统来确定的系统。

This project will build on work done by Irtaza Khalid, a final year PhD student at Cardiff, on machine learning for robust control, which will be discussed further in the overlap section. The primary aim of this project is to develop machine learning algorithms/models to apply robust control to physical quantum systems. The specific system to which these models will be controlling will be identified in the beginning of the project, but an example of a system could be the cold atom systems that the primary supervisor of this project is aiming to build. Should this be chosen, and the systems be operational towards the end of this project, then the output of these models will be tested on these quantum systems. If this is not the case, then the result of these models can be applied to other systems additional to those identified by reaching out to experimental academics such as Dr Alex Clark and requesting access to his quantum memory systems or other applicable quantum systems where robust control is necessary.