Quantum computing provides a new paradigm in which to use systems operating under the laws of quantum mechanics to solve complex problems such as in quantum chemistry for enhanced drug design or modelling of correlated media for designing new materials for aerospace and engineering which are currently beyond the capability of modern digital computers. Quantum hardware can also provide a dramatic speed-up of computationally expensive problems ranging from classical optimisation relevant to logistics (e.g. travelling salesman type problems) to factorisation. The major barriers to exploiting the advantages of quantum computing for these real world problems however are the technological challenges associated with building a system able to provide a sufficient number of high quality, low noise quantum-bits (qu-bits). Recent progress has seen the development of a number of different technologies to address this challenge, including superconducting qubits and trapped ions, however reconfigurable arrays of individually trapped atoms have emerged as a highly competitive approach able to scale to large numbers of identical qubits without loss of performance. These current systems with a few hundred qubits offer opportunities to explore early benefits of quantum computing, but suffer from noise and errors which place a limit on the performance and their ability to address useful problems. To overcome this limitation, it is necessary to perform error correction to fix the errors that otherwise corrupt the computer output. In digital hardware this is achieved by performing measurements on the information stored in logical registers. For a quantum computer this is much harder to implement, as the information is encoded in fragile superposition states which when measured directly results in a loss of information. One route to address this problem is to perform quantum error correction using a number of qubits to encode a single logical qubit by exploiting topologically protected states with specially chosen symmetry properties. To check for errors without erasing the quantum states, additional qubits (known as ancillas) are used to perform local measurements of the symmetries, after which errors can be corrected using standard gate protocols. Whilst a range of encoding schemes have been proposed for performing quantum error correction, this has so far only been implemented on few qubit systems of superconductors and ions and has yet to be demonstrated on the more scalable neutral atom platform due to challenges with cross talk when a only a single atomic species is used. In QuERy we will develop a new dual-species platform for neutral atom quantum computing to directly address major barriers to scaling up quantum hardware from 100s to millions of qubits, namely extending atom array trapping lifetimes through integration in a cryogenic environment to suppress errors due to atom loss, and demonstrating quantum error correction through the ability to perform cross-talk free, state-selective local measurements by using one species for encoding information and a second species to perform local ancilla measurements. This research will provide new modalities for neutral atom quantum computing, including enabling verification and benchmarking through randomised measurements, and develop algorithms able to exploit topological encodings to implement transverse gate operations. These results are crucial for the realisation of large-scale, fault-tolerant quantum computers as required to exploit the transformative benefits of quantum computing across both academia and industry, including applications such as material design, logistics and quantum chemistry for drug discovery.

Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.

The student will adopt a portfolio approach to their research and will benefit from the opportunity of exposure to a number of different photonics research areas and industrial collaborators. The student will commence on a project looking to develop an optical microfluidic-silicon chip diagnostic platform for the point-of-care detection of antibiotic susceptibility. In the first instance, the technology is being developed to investigate antibiotic susceptibility of bacteria involved in urinary tract infection. This is a project already underway for development of a benchtop instrument. A follow-on project will be to develop of a hand-held instrument for the same application but using a different optical waveguide structure that has been developed in the IOP. In addition, there will be the opportunity for the student to be immersed in other FCAP industry facing projects under the health and life sciences theme, amongst others.

The existing fleet of nuclear power plants (NPPs) in the UK have been granted life extensions into the 2020s and 2030s. Lifetime extension is associated with an increased need for monitoring to ensure safe operation. To achieve this, while keeping the cost of investment in new instrumentation infrastructure down, innovative and robust sensor solutions and ways to analyse measurement data automatically are required. Following de-commissioning and partial de-construction of NPPs, it is critical that many monitoring systems remain operational for decades to alert the custodian of the plant of any structural deterioration that may cause further damage or risk to personnel. Photonics and fibre optics hold the promise of high-resolution measurement, multiplexing, robustness, security and longevity. Consequently, this EngD project will address the plethora of engineering issues to develop remote monitoring systems for key civil structures with an NPP. Among other things, the project will develop and demonstrate a combined system for monitoring crack deterioration and CO2 leakage in multiple locations of a pressure vessel housing an Advanced Gas Reactor. The project will assess a number of competing photonic techniques that can be employed for these tasks, including distributed and semi-distributed strain sensors, and various techniques for gas sensing, compatible with a multiplexed system. Interferometric techniques may need to be deployed to measure very small changes in strain or displacement. Methods of sensor integration with plant ensuring long-term stability will be developed while ensuring cost effectiveness. Machine learning and other techniques, e.g., tipping point analysis will be investigated to assist in the detection of structural deterioration. Following laboratory investigations, a demonstration system will be deployed within an operating NPP. The project is expected to push the boundaries of the current state of the art in fibre-optic measurement in the areas of photonic systems integration and automatic data analysis from a distributed photonic sensor network.

Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.