Computer simulation to optimise the development and deployment of quantum sensors

计算机建模和优化对于开发和部署新的高科技设备、原型和产品至关重要。这对于加速量子传感器的生产和早期采用尤为重要，原因有两个。首先，制造传感器将需要许多供应链组件的集成，集成和功率降低，包括原子源和陷阱，激光器和光学设备以及超高真空系统。其次，为了建立传感器市场，需要确定和量化传感器的优势以及最佳使用方式。该项目将涉及计算机模拟软件的开发，包括使用复杂的逆方法定制的软件和使用COMSOL软件包的多物理场建模，以克服现实世界量子技术开发中的三个挑战：- 发展微型、一体化、适用于可扩展制造的低功耗组件-使用逆方法了解如何最好地部署量子重力传感器进行地下测绘-量化在脑磁图（MEG）中使用热原子传感器的好处学生可以选择考虑所有这三个主题，并在它们之间转移技术，或者随着项目的进行专门研究其中一个。与行业的合作将是博士研究的一个组成部分，该研究将建立在与英国地质调查局，e2 v，国家物理实验室和RSK的现有项目基础上，并建立新的行业合作伙伴关系。虽然总部设在诺丁汉大学，学生将花时间与专家在苏塞克斯大学的量子传感器和组件的模拟工作，也将鼓励与其他合作伙伴机构合作。

Computer modelling and optimisation is crucial for the development and deployment of new high-technology devices, prototypes and products. It is particularly important for accelerating the production and early adoption of quantum sensors for two reasons. Firstly, making the sensors will require the miniaturisation, integration, and power reduction of many supply-chain components, including atom sources and traps, lasers and optical devices, and ultra-high vacuum systems. Secondly, in order to build markets for the sensors, the advantages that they offer, and the best way to use them, need to be determined and quantified.This project will involve the development of computer simulation software, both bespoke using sophisticated inverse methods and Multiphysics modelling using COMSOL packages, to overcome three challenges in the development of real-world quantum technologies:- The development of miniature, integrated, low-power components suitable for scalable manufacture- Using inverse methods to understand how best to deploy quantum sensors of gravity for underground mapping- Quantifying the benefits of using thermal atom sensors in Magnetoencephalography (MEG) systems and designing components for such systemsThe student may choose to consider all three of these topics, and transfer techniques between them, or specialise in one of them as the project proceeds. Collaboration with industry will be an integral part of the PhD research, which will build on existing projects with British Geological Survey, e2v, National Physical Laboratory and RSK as well as open new industry partnerships. Although based at the University of Nottingham, the student will spend periods working with experts on the simulation of quantum sensors and components at the University of Sussex and will also be encouraged to collaborate with other partner institutions.