This project will develop an integrated theoretical and practical foundation for new methods and CAD tools to support the design of various types of systems with mixed synchronous-asynchronous operation. The crucial novelty will be in the use of the Elastic Logic principles when arranging interaction between blocks, partitioning the system into multi-block components ('localities').It will for the first time provide a pragmatic way of automating the design of mixed synchronous-asynchronous systems with varying granularity level, thereby leading to the development and application of systematic optimization techniques to obtain solutions targeted at the key design issues for deep submicron DSM and 3D implementation technologies, such as process variation power dissipation, area and speed. The project will deliver new theoretical models and algorithms for data-flow representation of systems for timing and power elasticity, automated partitioning of globally synchronous systems into subsystems with local synchronism, automated conversion of systems to elastic form and introduction of asynchronous protocols, design of synchronous-asynchronous interfaces and integration of the new methods into an appropriate industrial CAD environment. The new methods will be tested using an advanced case study from the industrial collaborators, using an advanced DSM technology.

Integrated photonics manufacturing is rapidly becoming a mature multi-billion pound global industry as photonics is underpinning an very wide range of applications aligned with UK's industrial strategy in AI and Web 5.0, the Future of Mobility, Healthcare, and Future Sensors. Test and measurement forms a critical part of most fabrication workflows both in industry and in research, for its potential of picking up deviations at the earliest stage possible and certainly before any expensive packaging and integration steps. On-wafer testing provides an early opportunity which can potentially save significant costs by preventing malfunctioning devices to continue in the processing workflow thus avoiding unnecessary waste of resources, tooling and energy. Importantly, wafer testing allows to feed back any deviations from the original design caused by failures in the fabrication process and smaller drifts exceeding the manufacturing tolerances. The semiconductor industry's leading IRDS Roadmap 2020 has identified the importance of photonics in next generation computing but has pointed out critical bottlenecks in available testing tools for addressing challenges in yield, variability, precision, and tunability of photonic chips. Fabrication imperfections are currently amongst the main limiting factors for achieving reliable high-volume photonics manufacturing. With the appearance of new photonic probe extensions to commercially available wafer probers commonly used in semiconductor electronics manufacturing, a range of sophisticated end-to-end characterisations is now available. This is ideal for a range of tests verifying performance and validating the entire circuit response against the expected output and identifying the critical outliers which are responsible for failure at the systems level. However the current generation of tools lack the capability of extracting information on what happens inside the photonic circuit. As integrated circuits become more and more complex, the lack of intermediate probe points in the circuit becomes an ever more pressing issue. Indeed this issue was addressed recently in other research projects, where groups have proposed erasable output couplers in the circuit as an option for more in-depth testing of intermediate probe points. However a more general approach is within reach as shown by us in a number of proof of principle studies leading to this project. It turns out that the semiconductors used in these photonic circuits are responsive to short-wavelength UV light, in fact responsive enough that illumination of a small microscopic point in the device gives rise to a traceable signal at the output of the circuit. By scanning this spot through the device, we can build up a detailed image of where the light is in both time and space. We can even resolve this map in wavelength, to build up a complete picture of device performance far beyond the capabilities of the commercial probe stations. While this so far has remained a basic research topic, we propose here to push this approach forward as a versatile tool for wafer-scale photonics testing. For this we need to make the techniques much faster, robust and reliable for use in a manufacturing workflow, and aligned with the actual requirements of the end users on different platforms. The majority of the project is therefore focused on developing this instrumentation, operating this with an open source Python data acquisition framework for interoperability and user customization, and generate a convincing set of tests and demonstrators for each platform that will be used to leverage the capabilities of this platform for different application areas. At the end of the project we expect that we have developed a self-contained instrument that will find use in a wide range of research and manufacturing environments around the world.

The elementary unit of quantum information is the quantum bit or qubit. Like the classical bit, the qubit is a two-level system but with the intriguing ability to exist in a superposition of states. This means it can be in the on and off state at the same time which has profound implications if we consider quantum systems of more than one qubit. Instead of each qubit carrying any well-defined information of its own, the information is encoded in their joint properties. In quantum mechanics, the qubits are described as being entangled. The challenge is to find ways to harness quantum phenomena such as superposition and entanglement to construct a quantum computer that is able to perform computational tasks that are unattainable in a classical context. A very natural qubit is the electron spin. The energy difference between spin states of an electron can be precisely controlled by magnetic fields and, using the electron's charge, it is also possible to isolate and manipulate individual spins electrically. One route to achieve entanglement between spin qubits is to use the interaction of their electron wavefunction overlap by placing them in close proximity. While such an approach is feasible for a small number of qubits, a large-scale quantum processor which relies on direct nearest neighbour coupling becomes rapidly impractical. Here we therefore propose an alternative strategy which makes use of an intriguing quantum mechanical effect by which two spatially separated quantum bits become entangled if a measurement cannot tell them apart. As has been shown theoretically, measurement-based entanglement can be used to couple large numbers of physically separated qubits, building up so-called graph states. Computation is then achieved by a sequence of measurements on individual qubits that consumes the entanglement - known as one-way quantum computation - which is entirely different from the standard circuit-based approach. In practise this also requires the presence of a quantum memory where quantum information is stored to allow graph-state growth without the risk of losing existing entanglement. Here we propose to use a solid-state implementation which is ideally suited to this task: single As-dopants in isotopically pure Si-28. To fabricate the devices, we will use the most precise silicon dopant incorporation technique available: scanning tunnelling microscopy (STM) hydrogen resist lithography. The atomically precise incorporation of individual As-dopants is essential in satisfying a key requirement of the measurement-based entanglement protocol: qubit indistinguishability. Having fabricated the devices, we will be able to manipulate the electron spins of the As-dopants and create entanglement between remote qubits using projective measurements. For this we will be using radio-frequency reflectometry techniques which allows us to perform these tasks on a timescale significantly faster than electron spin lifetimes. Once entanglement generation has been achieved, hyperfine coupling will be used to transfer the quantum information from the electron to the As nuclear spin states. This approach takes advantage of record nuclear spin coherence, in the 10-100 second range, of dopants in Si and allows us to grow the entangled graph state. Moreover, since the As nucleus has a non-zero electric quadrupole moment and a four dimensional Hilbert space we will be able to control the nuclear spins electrically and store and control the equivalent of two qubits in each dopant. For a proof-of-principle demonstrator we will entangle four spatially separated devices, each consisting of two As-dopant atom qubits with all-to-all qubit connectivity, equivalent to a 16-qubit processor. The experimental efforts will be supported by theoretical studies to further develop the most efficient strategies for growing a resilient remote network taking into account realistic experimental parameters such as spin dephasing and signal loss.

Materials characterisation is critical to the understanding of key processes in a range of functional and structural materials that have applications across several industrial sectors. These sectors include strategic priorities such as discovery of functional materials, energy storage and conversion and materials manufacturing, and healthcare. Materials characterisation is increasing in complexity, driven by a need to understand how materials properties evolve in operando, over their full lifetimes and over all levels of their hierarchy to predict their ultimate performance. The new generation of materials characterisation techniques will require: 1. Greater spatial and chemical resolution; 2. Correlated information that bridges nano- and centimeter -length scales, to relate the nanoscale chemistry and structure of interest to their intrinsically multi-scale surroundings, and 3. Temporal information about the kinetics of materials behaviour in extreme environments. The CDT will train students in a range of complementary techniques, ensuring that they have the breadth and depth of knowledge to make informed choices when considering key characterisation challenges. Our CDT will use an integrated training approach, to ensure that the technical content is well aligned with the research objectives of each student. This training in specific research needs will be informed by our industry partners and will reflect the suite of research projects that the students will undertake. Our portfolio of research projects will provide an innovative and ambitious research and training experience that will enhance the UK's long-term capabilities across high value industrial sectors. Additionally, our students will receive training in a range of topics that will support their research progress including in science communication, research ethics, career development planning and data science. These additional courses will be distributed throughout the 4-year PhD programme and will ensure that a cohesive training plan is in place for each student, supported by cohort mentors. Each student graduating from the CDT-ACM will leave will a through understanding of the key challenges presented by materials characterisation problems, and have the tools to provide creative solutions to these. They will have first hand experience of collaborating with industry partners and will be well placed to address the strategic needs of the UK Industrial Strategy. Our training will be developed in collaboration with leading partner organisations, and include international collaboration with the AMBER centre, a Science Foundation Ireland centre, as well as national facilities such as Diamond Light Source. Innovative on-line and remote instrument access will be developed that will enable both UK and Irish cohorts to interact seamlessly. Industry partners will be closely involved in designing and delivering training activities including at summer schools, and will include entrepreneurship activities. Overall the 70 students that will be trained over the lifetime of the CDT will receive excellent tuition and research training at two world leading institutions with unique characterisation abilities.