In today's world of pervasive Information Technology (IT), there is a pressing need to develop novel computing paradigms to move beyond current architectures with the goal of achieving intelligent computing with superior efficiency. Modern, conventional, computers operate in a very different manner to that of the human brain. In stark contrast, the main building blocks of the human brain are neurons (the computing elements) and synapses (the adaptive memory elements) and neurons are massively interconnected with synapses. Since learning is intricately connected to synaptic behavior, this project seeks to build next-generation artificial synapses In particular, we will explore the potential of non-volatile artificial synapses, based on nanoscale magnets, for energy-efficient brain-inspired operations, also known as neuromorphic computing. In a market with products requiring an abundance of sensors at the edge (e.g. mobiles or wearables like smart watches), there is a recognised need for ultra-low power and always-on sensory data processing. Neuromorphic hardware is one of the most promising routes for Artificial Intelligence (AI) applications. We propose to demonstrate that nanoscale skyrmionics synapses (that use nanoscale whirling vortex-like magnetic states called skyrmions as information carriers) are ideal for energy-efficient smart edge-computing devices.

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Topic of Centre: This i4Nano CDT will accelerate the discovery cycle of functional nanotechnologies and materials, effectively bridging from ground-breaking fundamental science toward industrial device integration, and to drive technological innovation via an interdisciplinary approach. A key overarching theme is understanding and control of the nano-interfaces connecting complex architectures, which is essential for going beyond simple model systems and key to major advances in emerging scientific grand challenges across vital areas of Energy, Health, Manufacturing (particularly considering sustainability), ICT/Internet of things, and Quantum. We focus on the science of nano-interfaces across multiple time scales and material systems (organic-inorganic, bio-nonbio interfaces, gas-liquid-solid, crystalline-amorphous), to control nano-interfaces in a scalable manner across different size scales, and to integrate them into functional systems using engineering approaches, combining interfaces, integration, innovation, and interdisciplinarity (hence 'i4Nano'). The vast range of knowledge, tools and techniques necessary for this underpins the requirement for high-quality broad-based PhD training that effectively links scientific depth and application breadth. National Need: Most breakthrough nanoscience as well as successful translation to innovative technology relies on scientists bridging boundaries between disciplines, but this is hindered by the constrained subject focus of undergraduate courses across the UK. Our recent industry-academia nano-roadmapping event attended by numerous industrial partners strongly emphasised the need for broadly-trained interdisciplinary nanoscience acolytes who are highly valuable across their businesses, acting as transformers and integrators of new knowledge, crucial for the UK. They consistently emphasise there is a clear national need to produce this cadre of interdisciplinary nanoscientists to maintain the UK's international academic leadership, to feed entrepreneurial activity, and to capitalise industrially in the UK by driving innovations in health, energy, ICT and Quantum Technologies. Training Approach: The vision of this i4Nano CDT is to deliver bespoke training in key areas of nano to translate exploratory nanoscience into impactful technologies, and stimulate new interactions that support this vision. We have already demonstrated an ability to attract world-class postgraduates and build high-calibre cohorts of independent young Nano scientists through a distinctive PhD nursery in our current CDT, with cohorts co-housed and jointly mentored in the initial year of intense interdisciplinary training through formal courses, practicals and project work. This programme encourages young researchers to move outside their core disciplines, and is crucial for them to go beyond fragmented graduate training normally experienced. Interactions between cohorts from different years and different CDTs, as well as interactions with >200 other PhD researchers across Cambridge, widens their horizons, making them suited to breaking disciplinary barriers and building an integrated approach to research. The 1st year of this CDT course provides high-quality advanced-level training prior to final selection of preferred PhD research projects. Student progression will depend on passing examinable components assessed both by exams and coursework, providing a formal MRes qualification. Components of the first year training include lectures and practicals on key scientific topics, mini/midi projects, science communication and innovation/scale-up training, and also training for understanding societal and ethical dimensions of Nanoscience. Activities in the later years include conferences, pilot projects, further innovation and scale up training, leadership and team-building weekends, and ED&I and Responsible Innovation workshops

Modern society depends massively on the generation, processing and transmission of vast amounts of data. It is predicted that by 2025, 175 zettabytes (175 trillion gigabytes) of data will be generated around the globe, with so-called 'edge computing' devices creating more than 90 zettabytes alone. Processing such huge amounts of data demands ever increasing computational power, memory and communication bandwidth - demands that cannot be sustainably met by conventional digital electronic technologies. The growing gap between the needs and the capabilities of today's information technology is exemplified if we consider the historical trend in total number of computations (in units of #days of calculating at a rate of 1 PetaFLOP/s) needed to train various artificial intelligence (AI) systems. The trend followed Moore's Law (doubling approximately every two years) until 2012, after which the doubling time reduced to a mere 3.4 months! This trend is compounded by the breakdown in Koomey's Law, which states that the number of computations per Joule of energy doubles around every 1.5 years. This law was also followed until quite recently, but we are now approaching a widely accepted computing efficiency-wall at around 10 GMAC/Joule (a MAC is a multiply-accumulate operation) for CMOS electronics and the von-Neumann architecture. As a result, the energy consumption used in training modern AI systems is truly staggering, with consequent adverse effects for sustainability. This has led to a move away from standard CPU designs in AI towards the use of co-processors - GPUs, ASICs, FPGAs - with superior parallelism. However, even here the limitations of electrical signalling lead to massive levels of energy consumption. It was recently estimated, for example, that the training of a large GPU-based natural language processing system used for accurate machine translation resulted in carbon dioxide emissions equivalent to lifetime use of 5 cars! Clearly, a new approach is needed. Thus, in the APT-NuCOM project we will develop a highly efficient novel non-von Neumann co-processor that exploits clear advantages offered by photonic computation, but at the same time links seamlessly with the electronic domain to enable integration with existing electronic computing infrastructure. The APT-NuCOM co-processor will exploit novel phase-change photonic in-memory computing concepts to deliver massively parallel computation at PetaMAC/s speeds and, ultimately, an energy budget approaching that of the human brain.

Quantum computing is expected to have far-reaching benefits as well as potential security concerns for a wide range of industries in coming years. At present, there is little understanding of, or expertise in, the skills required for effective quantum computational reasoning outside specialists in physics and mathematics. The goal of this work is to conduct a pilot project in collaboration with participants from across a range of ages and sectors to develop an understanding of how non-specialists develop their understanding of counter-intuitive quantum computational concepts and whether this can be assisted through the use of a visual game-like interface. Our project partner Quarks Interactive have developed a game which visually, rather than mathematically, represents the most common model of quantum computing; the gate model which is universal in the sense that it can model all quantum information processing. This project will allow us to develop and test the effectiveness of this game as a learning tool, as well as to assess its relative performance with different groups. The game consists of a visual Plinko (grid of pins) board like system where coloured balls travel down the board following different tracks. Players are tasked to solve increasingly complex puzzles using picture tiles to change the path the balls take down the board, or to introduce actions on the balls. Behind the scenes each picture tile accurately represents a quantum mechanical rule and the player's sequence of tiles is writing a functioning quantum algorithm. However, crucially, the player does not have to have any knowledge of the complex mathematics behind the scenes to be able to successfully complete the puzzles. The puzzles therefore enable the player to develop an intuition about quantum mechanics as well as generating genuine quantum computing algorithms, which can be implemented on quantum computers. Developing a more effective way for quantum non-specialists across diverse industries to develop intuition about quantum mechanics is crucial for businesses to understand the implications of quantum computing for their own context and to stay ahead of the game as quantum computing advances. Additionally, management and government will increasingly be expected to make decisions related to quantum computing and will have to become quantum literate to avoid falling victim to misconceptions and hype. Higher levels of quantum literacy will enable citizens from a wide variety of backgrounds to bring the potential benefits of exponentially faster and more complex data processing to their own businesses, industries and disciplines, enabling them to re-imagine the possibilities for data analysis and problem solving in their fields. At present, a relatively small number of quantum computing experts have this knowledge and understanding. The benefit of a broader range of citizens being able to access this understanding than is currently possible when quantum computing must be learned through maths and physics, is therefore a wider understanding of the potential applications of quantum computing in diverse areas of society, which currently do not benefit from this technological revolution. Quantum literacy equates to a different way of understanding reality and therefore, a potentially different way of conceiving of problems in a range of diverse fields. A quantum computing visualization learning tool could also have an important function in engaging the next generation of learners in the building blocks of quantum computing at an earlier age. We aim to discover whether learning through this puzzle visualization process also potentially increases engagement and motivation in groups who are traditionally under-represented in more advanced study of computer science, mathematics and physics.