Research Institute of Visual Computing

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Controlling, Modelling, Simulating and Identifying Quantum Systems

Cardiff Industrial Security

Controlling, Modelling, Simulating and Identifying Quantum Systems

In this project we explore models and techniques for designing and controlling quantum devices and establish links between physical (quantum) device modelling, experimental system identification, model verification and quantum control. Having reliable mathematical and computational models and methods is crucial for quantum engineers to design realistic quantum devices. This includes tools that allow not only efficient simulation of complicated quantum devices such as semi-conductor nanostructures, superconducting devices or atom chips, but also device optimization and dynamic control.

Specifically we consider the following questions:

(1) What techniques and models are needed to design, simulate and control the operation of quantum devices? Dynamic control simulations require control system models, conventionally based on partial differential equations derived from fundamental principles, such as the control dependent Schroedinger or quantum Liouville equation. Efficient simulation algorithms for physically accurate computational models are crucial for this task. Statistical models simply describing the behaviour of an actual device may sometimes be sufficient, or at least be used to augment the differential equation approach to consider specific material properties and the complete behaviour of real devices.

(2) What protocols for experimental system identification, parameter estimation and model verification are available? How efficient and reliable are these? What are their experimental requirements and how realistic are these? Do they provide the models we need? E.g. common techniques such as spectroscopy and quantum process tomography provide information about the system but do not directly provide the type of dynamic control systems models we require. How can techniques be combined, modified or extended to enable construction of the models we need?

(3) What are efficient ways to solve the inverse of the modelling and simulation problem, i.e., design and control optimization from optimal device geometries to dynamic voltage profiles applied to control electrodes or optimally shaped control pulses to be applied? What should be the main objectives of such optimizations? What are the practical constraints? How well can current algorithms cope with large-scale problems?

Models with efficient design and control methods are crucial to enable engineering complex quantum devices, whose ultimate importance lies in the applications. Quantum communication and encryption is maybe the most advanced area on the application side, with important effects already on secure communication. However, similar high-impact technologies are on the horizon in electronics, metrology, imaging, biology and medicine.

Project Leaders

Frank Langbein

Telephone: +44 (0) 29 20870110

Project Team

Research Themes

Research Institutions


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