DURHAM UNIVERSITY

UKRI Gateway to Research · FY 2025 · 2025-09

Advances in sensing technology have made it possible to collect large volumes of time-series data on many variables. In a diverse array of fields, a key question is whether such data can be used to learn directed relationships between variables. In other words, whether changes in one variable consistently precede those in another, an idea formalized in the concept of ‘Granger causality’. In this project, we use two motivating examples from neuroscience, where learning the drivers of change could lead to substantial improvements in our understanding of the underpinning physiology. The first concerns abnormal brain activity patterns which typically affect people with epilepsy. The second concerns the 24-hour biological clock, measured by a range of physiological variables. Graphical vector autoregressions (VARs) are a popular tool for learning such lag-lead relationships in multivariate time-series. A VAR of order p expresses the observation at time t as a regression on the preceding p terms. The pattern of zeros in the autoregressive coefficients has a graphical interpretation: absence of an edge from variable i to variable j is tantamount to i being Granger non-causal for j. In the Bayesian inferential framework, this kind of sparsity in model parameters can be accommodated by prior distributions which assign non-zero probability to every pattern of zeros. One limitation with current approaches to fitting graphical VARs is that useful Markov properties of Granger causality graphs rely on the process being stable (e.g. constant mean, variance, covariances), at least locally. For the process to be stable, the autoregressive coefficients must lie in a constrained space with a complex geometry, and so stability is generally assumed without being enforced. This can be problematic when there are not enough data to learn, with certainty, that a process is stable. A second limitation arises when data, though recorded at discrete intervals in time, would be more naturally described through the underlying continuous-time process. In this case, although the time discretisation is often chosen for convenience, the notion of Granger causality is dependent on it. Directly modelling the continuous-time system through the continuous-time analogue of a sparse VAR overcomes this problem but, again, enforcing stability imposes complex constraints on the parameters. Our aims are therefore: Develop prior distributions for VARs and continuous-time linear systems that simultaneously encourage sparsity in the parameters and enforce stability; Develop associated procedures for computational inference; Apply our ideas to the motivating applications from neuroscience.  There are two main challenges. The first is that the complex constraints imposed by the stability condition make it difficult to specify a prior distribution with appropriately restricted support. This problem is then compounded by requiring the prior to be sparse, essentially making its dimension one of the unknowns. There is then a second challenge: constructing a Markov chain Monte Carlo (MCMC) sampler over a constrained space of unknown dimension. In our two applications, interpretation of Granger causality networks has huge potential to improve understanding of the relationships between variables, with important implications for the treatment of disease. There are also numerous other fields which rely on network inference in their research and which therefore stand to gain from our methods. This includes genetics, finance and microbial ecology, with potential benefits further down the line from the broader agenda their research serves, be that society, the economy or the environment.

UKRI Gateway to Research · FY 2025 · 2025-09

Arrays of single ultracold neutral atoms, each trapped in so-called optical tweezers are emerging as a powerful platform for quantum computing. By clever application of laser beams we can fully control and detect the quantum state of each individual atom. Alkali atoms with a single outer electron are often used for these experiments, but atoms with two outer electrons like ytterbium (Yb) provide exciting new possibilities, owing to the existence of multiple long-lived states that can each be used to store quantum information, so called qubits. Each qubit is manipulated using light of a different wavelength, which makes moving information between these different types of qubits a powerful tool to selectively perform operations on a subset of qubits. Meanwhile other information is hidden away in another qubit type and protected from the lasers used in the operation. These systems are currently being rapidly adopted internationally but are not yet established in the UK. This is partly because the added capabilities come at the cost of laser wavelengths that are less convenient to generate and traditionally required complicated and bulky setups. In this project, I will address three bottlenecks to the adoption and scaling of quantum computing with Yb lasers: complexity of laser systems, the footprint of devices and quantum networking. I will develop a complete laser system for control of Yb qubits based on a single laser technology. I will also investigate novel sources for ultracold Yb that are smaller and use less power than conventional designs. In achieving these objectives I will lower the barrier to the adoption of Yb by decreasing the complexity of the required setups. A key feature making quantum computing so powerful is entanglement. Entanglement generation between two qubits usually requires their close proximity. However, quantum networking and the creation of large computing systems consisting of many processing nodes require the generation of entanglement between spatially separated qubits. This is possible by generating entanglement between stationary qubits and photons as flying qubits. By performing measurements on a pair of photons we can then generate entanglement between the atoms that emitted these photons. I will develop an optical network interface for Yb and demonstrate the generation of entanglement between two Yb qubits over conventional optical fibres used in telecommunication networks. To efficiently collect single photons emitted from the Yb atoms I will place them into micro cavities formed by the machined and coated endfaces of optical fibres. The presence of such cavities causes the atoms to preferentially emit photons in their direction, so that the photons can be coupled into optical fibres with much larger efficiency than is possible otherwise. The specific structure of Yb atoms allows us to operate at a wavelength compatible with common optical telecommunication fibres and thus allows transmission over long distances. The development of a quantum networking interface that directly integrates with the promising Yb quantum computing platform is an important step to ensure the continued scaling of this technology by allowing the construction of distributed computing systems - analogous to conventional supercomputers consisting of many smaller processing units. Demonstrating a more compact and less complicated setup for working with ultracold Yb benefits scaling of quantum computers and removes barriers to commercialisation and field-deployed applications. Beyond quantum computing and networking this will benefit applications in quantum sensing and optical clocks.

UKRI Gateway to Research · FY 2025 · 2025-09

Synthetic data - data generated using Artificial Intelligence (AI), designed to mimic real-world data characteristics or patterns without direct reference to real persons, objects, or events - has become increasingly prominent in discussions of science and technology innovation. A recent notable example is the UK government’s AI Action plan which specifically highlights the national importance of developing AI-generated synthetic datasets for scientific purposes. The increasing prominence of synthetic data in scientific research, where synthetic data is often framed as a solution to concerns around data privacy and model robustness, warrants deeper understanding of impacts. This timely interdisciplinary project will contribute critical theoretical and empirical knowledge about how synthetic datasets impact scientific research and innovation across the scientific ecosystem, exploring how synthetic data may potentially even redefine the role of the scientist. It will focus on the case study of biomedical research, a high-stakes area which interfaces closely with many scientific disciplines, to look at how AI methods and synthetic data are shaping scientific concepts and practice. The findings of this study will provide insights for the broader AI metascience community into how to foster rigorous, equitable scientific engagement with synthetic data. Long acknowledged issues in both AI and biomedicine, such as data bias and sparsity, make synthetic data a particularly promising proposition, with many of these issues anticipated to be resolvable through the generation and use of synthetic data. Meanwhile, as AI increasingly assumes exploratory and problem-solving functions, researchers become tasked with validating, refining, and contextualising machine-generated outputs. These developments raise critical questions about the authority and epistemic implications of AI-derived knowledge in comparison to traditional hypothesis-driven science, such as the impact of ground-truthing data gaps on veracity of synthetic data outputs. Evaluating science requires empirical and conceptual understanding of the nature of scientific roles and practice. However, synthetic data represents a paradigm shift which challenges deeply held norms of reasoning and evidence evaluation, distributing innovation between the human and machine. Responding to these challenges, this study will employ qualitative and empirical research methods to address key questions regarding how synthetic data reshapes epistemic practice and cultures within this case study domain. This research will address the following research questions; a) how does synthetic data mediate the role of the scientist, processes of problem formulation and the nature of scientific evaluation?, b) how do AI epistemic cultures redefine scientific concepts, such as scientific results and evaluation, relationships between inputs and outputs, and ideas of validity, reliability, and inference?, and c) what are the implications of this for building scientific cultures which employ synthetic data in a robust, open and conscientious way? Specifically, I will use interviews and interactive workshops in combination with document analysis of academic literature and other relevant writing, employing Reflexive Thematic Analysis to guide data analysis. Study findings will map how synthetic data are employed in practice, and how synthetic data mediates scientific practice. In doing so, this work will contribute crucial knowledge to the AI metascience community and inform governance and policy shaping engagement with AI methods in scientific.

UKRI Gateway to Research · FY 2025 · 2025-09

We live in a particularly exciting time for cosmology. The wealth of observational data has never been so abundant, with the potential to provide definitive constraints on the nature of dark matter (DM) and dark energy (DE), two fundamental problems in Physics today. Numerous ongoing and upcoming surveys have been designed to make high-precision maps of the large-scale structure of the Universe in an effort to address these problems directly. In order to make sense of these large -- and expensive -- data sets, it is necessary to consider them in the context of equally sophisticated theoretical models. My ongoing FLF project, which lies at the nexus of cosmology, particle physics and high-performance computing, addresses this need, following three broad scientific questions: What are the new frontiers for constraining DM and DE? How does the interplay between dark and luminous matter affect what we infer from future galaxy surveys? What can we learn about the Universe using the smallest “dwarf” galaxies? My research group uses state-of-the-art simulations of galaxy formation to tackle these questions. A significant milestone in my project so far has been the completion of MillenniumTNG (MTNG), which are some of the largest (and most realistic) simulations of galaxy formation ever performed. The results of these data are being used to inform theoretical models connecting dark and luminous matter -- the so-called “galaxy-halo connection” -- that are employed within large galaxy surveys for inferring cosmological parameters, which is one of the fundamental goals of modern cosmology. MTNG data are now being used by research groups across the community. We have also made advances in the study of “modified” gravity (MG), which provides an alternative explanation to DE. My group has produced the first realistic galaxy formation simulations in MG. By creating “mock” samples from the simulated data, we have shown how signatures of MG may be detected in the real Universe. I have also pioneered new methods that use Machine Learning that allow us to capture the complex physics of MG models in a fraction of the time needed to run the full simulations. My theoretical models have also been instructive in devising new tests of DM and galaxy formation in the early universe using the properties of dwarf galaxies, specifically those that orbit the Milky Way. This work suggests that the tightest constraints are possible when using a broad range of observables: from low surface brightness features around nearby galaxies, to the gravitational wave signals from dwarf galaxy mergers in the early Universe. Excitingly, these are exactly the sorts of observations that will targeted by upcoming surveys in the next decade. Over the next several years, I will extend upon the progress I have made in the FLF so far and drive forward advances along each of these three themes. Progress I have made in studying the galaxy-halo connection will be used to inform the next critical phase of analysis for the Dark Energy Spectroscopic Instrument survey (DESI) and Euclid, and to define the mission scope for DESI's successor in the 2030s. Using a new, cutting-edge model of galaxy formation called COLIBRE, I will also drive forward new advances in the study of dwarf galaxies in the early- and late-time Universe to enable robust constraints on the nature of DM and the physics of galaxy formation.

UKRI Gateway to Research · FY 2025 · 2025-09

From pharmaceuticals to snowflakes, seashells to chocolate, and batteries to bones, crystalline materials are everywhere.  The ability to control crystallisation is therefore hugely important.  This project will address this topic and develop a new strategy for controlling the properties of molecular crystals (crystals of organic molecules), where these form the basis of most pharmaceuticals and agrochemicals. The doping of crystals with impurities is well-established as a powerful method for enhancing the properties of inorganic, metallic and semiconductor materials.  This is termed the creation of a solid solution.  For example, the addition of < 1.5% carbon to iron produces steel, which is harder, more durable and more resistant to corrosion. By comparison, little is known about the doping of crystals of small organic molecules (molecular solid solutions, MoSS). This is due to the challenges associated with studying these materials, where (i) they are inherently disordered, making them challenging to study experimentally and computationally, (ii) there is a vast reaction space comprising different combinations of host and dopant molecules and reaction conditions (eg. solvent and temperature) and (iii) molecular crystals typically exhibit multiple solid forms, with some compounds able to crystallise in over fifty different structures. Existing data on MoSS suggest that this strategy has enormous potential to control the structures and properties of the product crystals.  The introduction of dopant molecules can potentially change the structure (polymorph) and stability of the crystals, produce different crystal morphologies and change the rate of formation and growth of crystals. Importantly, it can also change properties such as solubility and resistance to fracture, which are critical in many applications.  By understanding the design rules underlying the formation of MoSS and their structure-property relationships we can therefore learn how to use this strategy to tune the structures and properties of molecular crystals in a predictable way. Our vision is to realise the full potential of MoSS and create a framework of tools, data and understanding that translates MoSS from concept to real-world applications.  This will be achieved by: Developing screening, characterisation, modelling and crystallisation strategies to explore the synthesis and structure-property relationships of MoSS. Creating an openly accessible MoSS database of structure-property-crystallisation data. Establishing design rules to predict and anticipate which host:dopant systems can form MoSS. Investigating the effect of MoSS formation on crystal polymorph. Collaborating with industry to study real-world systems and translating the developed methods and knowledge to consumer products. Our team is uniquely placed to succeed in this ambitious project. We combine interdisciplinary expertise in MoSS and crystal engineering, high throughput crystallisation, atomic-scale characterisation, modelling of crystal structure and growth, and data handling and AI methods, with the expertise of leading industrial representatives.  With our team of experts, state-of-the-art facilities in Durham, Leeds, and Manchester, and the flexibility provided by a Programme Grant, we aim to revolutionise MoSS research and pave the way for real-world applications. Our work has the potential to transform the formulation of drugs, agrochemicals, and other molecular products of the future, and position the UK as a leader in this new field.

UKRI Gateway to Research · FY 2025 · 2025-09

The Langlands programme, initiated in the 1970s, is a broad web of ideas that connect the worlds of analysis, geometry, algebra, and number theory. It predicts that sequences of numbers coming from counting the solutions to integer equations also arise in a completely different way, from analytic functions with a very large amount of symmetry. This is both surprising and powerful; the confirmation of a very special case of this prediction led to the proof in 1995 of Fermat's Last Theorem, a problem that had stood for over 300 years. Congruences play a key role in much of the recent progress in the Langlands programme and its applications. These arise when two sequences of integers leave the same remainders when they are divided by a prime number. The study of these congruences divides into two cases: l-adic congruences, where the prime l that we are dividing by is distinct from the prime that is being varied in the data producing the sequences, and p-adic congruences, where these primes are the same. The p-adic case in particular has received a large amount of attention in recent years. The aim of this project is to exhibit a great deal of unity between these two apparently quite different cases. We will show that ideas from one case can be used to produce new conjectures and new proofs in the other case. For example, the Breuil-Mézard conjecture originally arose on the p-adic side but was previously shown by the PI to have an l-adic analogue; we will generalise the scope of this l-adic analogue (to arbitrary "reductive groups") which will then provide a foundation for generalising the p-adic analogue. We will also show that p-adic results of Emerton-Gee-Savitt on the integral cohomology of certain highly symmetric varieties has an l-adic analogue; and, in the other direction, find a p-adic version of recent l-adic results showing that endomorphism rings of projective modules appear in deformation spaces of Galois representations.

UKRI Gateway to Research · FY 2025 · 2025-08

One of the greatest challenges in modern physics is to understand the behaviour of interacting many-body quantum systems. Such systems are important in condensed-matter physics, nuclear and particle physics, cosmology, chemistry and biology. In many cases they are poorly understood because they are too complex to simulate on classical devices and the systems found in nature are difficult to control on a particle-by-particle basis. This has prompted the development of quantum simulators as an alternative route to understanding many-body quantum phenomena. Our vision is to use ensembles of ultracold polar molecules to explore the physics of many-body quantum systems and understand the emergent phenomena they exhibit. Our approach exploits the long-range anisotropic dipolar interactions and rich internal structure of diatomic molecules, combined with the exquisite control of ultracold platforms. Every element of the systems we study will be under our control – the quantum states of the molecules, the sign and strength of their interactions, their mobility in each spatial dimension, the number of internal states involved, the degree of disorder, and their coupling to the environment. This level of control and versatility is unique, allowing us to access parameter regimes that are not attainable in other systems. We have devised a programme that spans multiple quantum platforms and a wide range of interconnected many-body phenomena. We will use small ensembles of individually controlled molecules held in optical tweezers where the geometry of the array and the states of individual molecules are controlled dynamically.  We will also use larger ensembles in optical lattices where the interactions are stronger and there is controlled tunnelling between sites, leading to more complex many-body phenomena. We will address and detect individual molecules in lattices using quantum-gas microscopy to reveal further details of the behaviour of the system. We will exploit the long-lived rotational and hyperfine states of our molecules to encode interacting pseudo-spins and to engineer synthetic lattices. Finally, we will create molecular Bose-Einstein condensates with strong dipolar interactions and explore their rich properties. The synergies between these research strands and experimental platforms will be fundamental to accelerating progress and mitigating risk, allowing us to cement the UK's leading position in this field. We will collaborate at the interface between few-body physics, many-body physics, molecular quantum gases, quantum simulation and precision measurement to reveal how new phenomena emerge in ensembles of interacting quantum particles. By bringing together our expertise from across these fields, we will make transformative advances that we could never make alone. We will connect the few-body theory needed to understand the microscopic interactions of our molecules with the many-body theory needed to understand the emergent properties. We will engineer and quantify the entanglement that is central to all many-body quantum phenomena, study the behaviour of strongly interacting quantum fluids, explore spin dynamics, quantum magnetism and the exotic phases that emerge when spins tunnel between sites of a lattice, and use synthetic lattices to extend our exploration into new territories. We will harness the strongly correlated many-body phases of molecules to demonstrate quantum-enhanced sensors with future applications in quantum technologies and tests of fundamental physics. Our work will challenge state-of-the-art theoretical methods and cast light on the physics of many-body phenomena in other settings. As such, our arrays of polar molecules will be powerful and versatile platforms for simulating many-body quantum systems.

UKRI Gateway to Research · FY 2025 · 2025-07

Photons are excellent carriers of quantum information. They only weakly interact with their environment, meaning quantum information can be easily transmitted over great distances without being lost. However, the lack of interactions is a double-edged sword as it means the photons do not easily interact with each other. Without photon-photon interactions, it becomes difficult to entangle photons and perform certain quantum gate operations on them. It is possible to create photon-photon interactions by propagating photons through a medium. Inside the medium, hybrid light-matter particles known as polaritons can form, which interact through their matter component. However, finding a medium where the interaction strength is large enough to allow single photons to have a high-probability of interacting and becoming entangled with each other is challenging. One system which has achieved large enough interaction strengths is Rydberg atoms. Rydberg atoms are atoms where one electron is promoted to a highly excited state. The excited electron is far from the core of the atom, giving Rydberg atoms exaggerated properties, including enhanced interactions between atoms. By mapping these interactions onto light, it is possible to achieve a nonlinear response at the single photon level and strong enough effective photon-photon interactions to create entanglement between photons.  However, technologies based on Rydberg atoms are hard to combine with other photonic technologies, such as waveguides. Rydberg excitons are highly excited bound states of electrons and holes in a semiconductor and have recently emerged as a solid-state analogue of Rydberg atoms. They occupy a unique position, providing the possibility of combining the interactions and nonlinearities associated with Rydberg atoms, with the scalablity of semiconductor technologies. The current leading material for Rydberg excitons is cuprous oxide, where highly excited Rydberg states and interactions between Rydberg states have been observed. In 2022, Rydberg excitons in cuprous oxide were strongly coupled to light, creating Rydberg exciton-polaritons. Rydberg exciton-polaritons allow the Rydberg interactions to be observed as effective photon-photon interactions. However, the effective photon-photon interaction realised in cuprous oxide are still well below the level required for creating two-photon entangled states. This is because cuprous oxide is an absorptive material, which leads to loss in the material. This project will pioneer the study of Rydberg excitons in a new material, zinc diphosphide, and strongly couple them to light. Zinc diphosphide shows similar Rydberg lines to cuprous oxide but crucially has a 50 times lower absorption. Due to the lower absorption and strong interactions between Rydberg states, it will be possible to create arrays of single Rydberg exciton-polaritons in a microcavity for the first time, which will emit single photons and will allow photon-photon interactions to reach the single photon level. Additionally, the wavelengths of light involved in this material (775-780 nm and 1550 nm) mean that it is potentially compatible with other quantum technologies (e.g. atomic quantum memories) and telecommunication infrastructure (which commonly uses 1550 nm light). The creation of effective photon-photon interactions at the single photon level will have significant impact in photonic quantum information processing, as it will lead to the ability to entangle two single photons with high probability, allowing conditional quantum gate operations to be performed.                        

UKRI Gateway to Research · FY 2025 · 2025-07

The environmental sciences face a significant challenge in attracting students from minority ethnic and socioeconomically disadvantaged backgrounds, a problem acutely obvious at the postgraduate level. The Iapetus doctoral training partnership (DTP) has introduced recruitment and scholarship schemes to address this issue, but recruitment from these groups remains low. One key factor is that many students from under-represented backgrounds do not consider careers in environmental sciences. The limited awareness of environmental science career paths and the lack of relatable role models contribute to this problem. To tackle this, our project aims to change school pupils' perceptions of environmental science careers and eventually increase the pool of eligible doctoral applicants from these focal groups. The project will host a pilot event, focusing on 12 to 13-year-old students from schools in disadvantaged and ethnically diverse areas. This age group was chosen because it is a critical time in a young person’s education, when they begin to make decisions that could limit future career options. By engaging them early on, we aim to broaden their horizons and inspire them to consider environmental science careers as both viable and rewarding. The event will feature videos that showcase a diverse range of environmental scientists working in various sectors, such as public, private, charitable, and regulatory fields. These videos are designed to inspire students by showing them that environmental science offers many career possibilities, regardless of background. Alongside the videos, the event will include interactive activities and challenges that will help students connect theoretical knowledge with real-world applications, enabling them to envision themselves in environmental science careers. Students will also engage in discussions with environmental scientists who can answer their questions and provide further insights into their careers. This engagement with relatable role models will be crucial in breaking down barriers to entry for these under-represented groups. In addition, the project will involve a workshop where environmental scientists from under-represented backgrounds will collaborate with the DTP management team to co-create a theory of change. This framework will enable us to build a shared understanding of the long-term change we want to see and to identify concrete actions to realise that change. Our workshop will allow participants to explore barriers they faced and ways to remove them, ensuring that the DTP is more accessible and welcoming to all. We will share our findings with other NERC DTPs and other doctoral programmes. The expected outcomes of the project include three inspiring videos that highlight diverse environmental science careers and role models, a scalable engagement event model that can be expanded across the DTP network and beyond, and a theory of change that will guide efforts to increase diversity in environmental science education and careers. Ultimately, this project seeks to shift perceptions, inspire a more diverse generation of environmental scientists, and leave a lasting impact on how these careers are viewed by under-represented groups. It will also foster long-term change by providing a scalable framework to guide future initiatives that seek to create a more inclusive pipeline for the environmental science workforce.

UKRI Gateway to Research · FY 2025 · 2025-06

This secondary data analysis initiative project will reanalyse and reinvigorate data from The Affluent Worker in the Class Structure (Goldthorpe et al, 1967, 1968a, 1968b & 1969), a highly influential classic sociological study which set out to understand the changing nature of working class identity and political attitudes in 1960s Britain. The original research team carried out some 847 interviews, mainly with male workers in the car manufacturing industries of Luton and Cambridge, as well as a series of home interviews whereby the men were interviewed alongside their wives. Remarkably given the changing nature of Britain in the 1960s in terms of racism, gender relations, and social class inequality and their intersections, race and gender do not feature in the original write-up of the study and are largely absent from subsequent critiques involving small-scale reanalyses (e.g. Savage, 2005a; Lawrence, 2014) or replication studies (e.g. Devine, 1992). Funded by a Durham University Seedcorn Grant, we analysed 12% of the archived interview materials. In doing so, we discovered a number of striking omissions in the original data analysis pertaining to the ways in which matters of race, immigration, empire and racism shaped the interviewee's identities and political attitudes, as well as insights into the perspectives of women gleaned from the until-now neglected contributions of the "workers wives" to interviews conducted in the home. A major objective of this SDAI project, therefore, is to reanalyse the entire corpus of interview data from The Affluent Worker study in a way that is attentive to these omissions. Given its status as a sociological classic, it is also astonishing that the data originally collected and wider study documentation is currently only available to secondary analysts in archived paper form, with only a small fraction having been rudimentarily digitised and reanalysed by subsequent researchers (Haaker, forthcoming). A second major objective of this SDAI project, therefore, is to reinvigorate The Affluent Worker study by subcontracting with the University of Essex Special Collections team based at the UK Data Service to digitise the entire corpus of interview documents and related paradata including researchers' notes and supplementary study materials, thus making the original study data accessible to the wider research community and the local communities in which this research was undertaken. The project will leave two legacies: 1) a fresh analysis of the original study materials with a novel focus on matters of race and gender, their intersection with class identities and class relations in 1960s Britain, and the resonances of this for the present day; and 2) a digitised version of the study materials that will be readily available in perpetuity to the wider research community, as well as the local communities in which this research was undertaken, including local libraries, archival collections and local history societies in Cambridge and Bedfordshire.

UKRI Gateway to Research · FY 2025 · 2025-06

Our ultimate aim is to resolve the longstanding “open flux problem” whereby more magnetic flux is measured in situ at 1 AU than is predicted to leave the Sun by magnetic extrapolation models. The open solar flux is a crucial quantity for space weather because it extends out as the heliospheric magnetic field, affecting the interaction of the solar wind and coronal mass ejections with the Earth's magnetosphere, and modulating the flux of galactic cosmic rays. Conversely, connecting in situ measurements at 1 AU with the open flux on the Sun is important for long-term investigations of the solar dynamo through historical geomagnetic data. Recognising that the open flux shortfall likely results from multiple causes, we will quantify how much additional flux can be explained purely by the effect of solar wind outflow on the coronal magnetic field (Objective 1). In doing so, we will provide a calibrated "outflow equilibrium" model for the coronal magnetic field, and test the improvement of space weather forecasts versus presently-used models (Objective 2). The resulting code will be made available open source to the community. The project is achievable thanks to our recently-developed outflow equilibrium model that modifies the traditional potential field source surface model to account for an axisymmetric solar wind. Preliminary results suggest that this model enhances the open flux, but it remains to be calibrated against observations. Here we will compare with a recent "ground truth" dataset of open flux inferred from in situ data with switchbacks removed. We will also add further constraints from white-light tomographic observations of the latitude-longitude (pseudo)-streamer structure. Our model retains the numerical efficiency of the potential field model, facilitating a thorough parameter observation against observations over two solar cycles. As well as producing in itself an improved tool for space weather forecasting, isolating the effect of outflow will lay the groundwork for future calibration of the latest generation of time-dependent dynamical coronal models. The results will also be relevant to modelling of other stars.

UKRI Gateway to Research · FY 2025 · 2025-06

Reimagining Pathways into Environmental Science through Showcasing Technical Careers aims to empower young people from socially disadvantaged backgrounds into a technical career in environmental science. It identifies opportunities and barriers for technical environmental science careers within higher education technical workforces and beyond. Our team includes a diverse community of technical professionals and research enabling staff alongside a Project Advisory Group committed to piloting innovative solutions. It showcases how technical roles in environmental science can be an innovative pathway for students with a passion for creating environmental solutions to develop thriving careers. The project articulates the need for diversity in the environmental science workforce, and in collaboration with Further Education colleges seeks to improve social mobility in the North East to improve student outcomes, career prospects and pipelines. For Durham University technical staff, the project creates Technical Champions in environmental science. It raises the visibility, recognition and reward of technicians and highlights the sustainability of the research technical workforce of the future. Through the leadership of our technical staff and research enabling professionals, we seek to showcase the diversity of roles in the environmental science ecosystem and place students alongside “someone like me” with the motivation of enabling the next generation of NERC technicians. The project brings in partnership Durham University with regional Further Education colleges. It enables collaborations with the North East Institute of Technology and the North East Combined Authority and at a national-level the UK Institute for Technical Skills and Strategy, to explore and advance technical training, career pathways and education policy. The project is designed in two stages. Stage 1 will map internal structures and resources within Durham University to enable Technical Champions, outreach activities, and pilot T Level placements related to environmental science. This involves a self-assessment of Durham University’s technical expertise, resources, and current outreach activities in environmental science and capacity for delivering technical T Level placements. This will generate the establishment of a Technical Champions Forum, enhance bespoke outreach to FE colleges to showcase resources and equipment used in environmental research, and pilot T Level Placements showcasing environmental science careers. Our second work package involves an external assessment of FE college T Level curricula, to identify overlaps with NERC disciplines and education. This will detect opportunities for curriculum development in T Level programmes and create visibility for technical career pathways. Surrounding these streams is a process evaluation design and Theory of Change creation. This will analyse the outcomes of the first two work packages, assess the sustainability of the technical workforce, and develop an evaluation framework. Evaluation of the project will assess its impact on widening participation in environmental science, and the effectiveness of partnerships with FE colleges. This will inform the methodology for evaluating the potential outputs from the strategic aims for the 2026 project, focusing on the effectiveness of the technical workforce as champions in environmental science, the impact of outreach activities, and the impact and effectiveness of the T Level placement programme. The project will foster a culture of inclusion across our technical community and will enable a positive research culture where our technical staff are champions environmental science with the desire to enable young people from socially disadvantaged backgrounds to gain the skills and career pathways to equip them to respond to the global environmental challenges of the future.

UKRI Gateway to Research · FY 2025 · 2025-05

The intimate link between form, or shape, and function is ubiquitous in science. In biology, for instance, the shapes of biological components are pivotal in understanding patterns of normal behavior and growth; a notable example is protein shape, which contributes to our understanding of protein function and classification. This project, led by a diverse team of investigators from the USA and the UK, will develop ways of modeling how biological and other shapes change with time, using formal statistical frameworks that capture not only the changes themselves, but how these changes vary across objects and populations. This will enable the study of the link between form and function in all its variability. As example applications, the project will develop models for changes in cell morphology and topology during motility and division, and changes in human posture during various activities, facilitating the exploration of scientific questions such as how and why cell division fails, or how to improve human postures in factory tasks. These are proofs of concept, but the methods themselves will have much wider applicability. This project will thus not only progress the science of shape analysis and the specific applications studied; it will have broader downstream impacts on a range of scientific application domains, providing practitioners with general and useful tools.

UKRI Gateway to Research · FY 2025 · 2025-04

In recent years, we have seen a surge in so-called Decentralized Autonomous Organizations (DAOs). These are online communities that have come together to pursue a specific goal. Some are research- and media-oriented, discussing Sustainable Development Goals (SDGs) like waste management or financial literacy, voting on solutions, identifying research priorities, and publishing articles to inform the public. Other DAOs take a more active role by planning and organising initiatives that, for instance, aim to make cities greener, more digital, and more democratic. Some well-known examples are GreenDAO, OceanDAO, and SoCity DAO—communities that promote urban development by incentivising pro-social behaviour. A defining characteristic of DAOs is their use of blockchain-based governance systems, meaning that these communities lack formal divisions between governance, executive, and supervisory bodies. Instead, members participate in decision-making by voting on proposals online. Anyone can join a DAO, and all governance processes (such as voting polls, vote counting, and voting rules) are managed through smart contracts (computer programs stored and executed on the blockchain) to ensure fairness and transparency. When a proposal gains majority support, it is executed and implemented; if it does not, it is rejected. As of 2025, there are over 80,000 DAOs, with a market valuation of $60 billion. In this project, we will examine various governance models of DAOs, exploring their risks, benefits, and overall effectiveness in maximising community welfare. Many blockchain-based governance models resemble direct democracies. For instance, in Switzerland, citizens vote directly on policies covering social and environmental issues, infrastructure, finance, and education. Similarly, blockchain-based governance allows people to vote directly on community projects, funding decisions, or governance processes. Unlike traditional voting, which relies on paper ballots and manual counting, blockchain-based governance is digital, automated, inclusive, and cost-effective. These advantages make it easier to conduct frequent elections and polls, which is driving the increasing adoption of blockchain technology in governance. Blockchain-based governance has attracted interest from cryptocurrency stakeholders and global regulators alike, who are seeking to understand when and why decentralised governance systems succeed or fail, how they are influenced, and how accountability is managed in cases of misuse or failure. Since its inception in 2009, blockchain technology has grown into one of the largest financial settlement systems, used for trading, lending, and borrowing cryptocurrencies. With the rise of DAOs, cryptocurrencies are now used not only for trading but also as a voting mechanism for DAO proposals. In our report, we will bring together knowledge from areas such as finance, economics, political science, law, and computer science to analyse the pros and cons of this novel governance mechanism. Blockchain governance also offers insights into voting behaviour, as votes are recorded on the blockchain and are publicly accessible. We will synthesise insights into voter behaviour, influencing factors, and causal relationships that have previously been difficult to explore. We are confident that our knowledge synthesis report will provide valuable insights into this new and fast-growing form of governance, which has been under-explored in the literature.

UKRI Gateway to Research · FY 2025 · 2025-03

Quantum Key Distribution (QKD) offers totally secure communications and can be realised across large distances using Free Space Optical Communications (FSOC)  links. QKD systems using satellites are under heavy development, (e.g. the EU’s “EAGLE-1”), however such systems require permanent ground and space infrastructure. We present the ReQON (Reconfigurable Quantum Optical Networking) programme with the objective to demonstrate deployable, mobile Quantum communications links with reduced requirements for infrastructure and cost, therefore enabling QKD to be used in a wider variety of applications. In this first step of the programme, we will focus on a laboratory demonstration of “asymmetrical” communication links, with one “active” terminal which contains transmission lasers, reception systems, tracking systems and adaptive optics (AO); and one “passive” terminal, which contains a receiver and a retro-modulator to return modulated light back to the active terminal without the need for heavy and power-hungry lasers or tracking systems. The passive terminal may then be mounted on a low cost platform, such as a Unmanned Aerial Vehicle, and quickly deployed above the area of interest. Research will focus on combining two key areas in which the partners have had previous success  – AO and retro-modulators. Durham University (DU) will focus on the development of the active terminal – a transportable Optical Ground Station (OGS) – with significant attention on creating the next generation of AO systems that can optimise the efficiency of the link even in the worst-case conditions. AO becomes critical in Quantum communications links as it is not acceptable to lose photons due to turbulence effects. New wavefront sensing solutions are required to operate through “deep” turbulence conditions found in horizontal links. Convolution Neural Networks operating on focal plane images detecting the electric field are a promising solution to this issue. They do not require dedicated wavefront sensing devices and can improve the performance of the OGS by detecting the electric field, hence better accounting for “branch points” and “branch cuts”. DU has significant experience in developing AO systems for astronomy, including the CANARY laser guide star demonstrator and leading development of the control system for the HARMONI Extremely Large Telescope instrument. Dr Andrew Reeves has recently joined the instrumentation group having previously led development of the German Aerospace Centre’s (DLR) AO system for their state-of-the-art OGS, the test facility for EAGLE-1. The University of British Columbia (UBC) will develop the passive terminal, including the next generation of retro-modulators that are compatible with QKD. Prof Jonathan Holzman and his lab has previously specialised in the development of retro-modulators for optical communications. New techniques to improve the modulation depth will be explored - the retro-modulator must be capable of deep modulation to ensure an acceptable signal to noise ratio when sending low power quantum signals. Entanglement of photons with differing polarisation state is the most suggested solution for QKD across FSOC links, this will likely be achieved by enhancing their ability to quickly and efficiently control the polarisation as well as amplitude of the light. The two ReQON terminals will be brought together for full system testing through turbulence at DU. DU and UBC are a unique team capable of delivering accessible, secure communications to a variety of applications including disaster relief, defence, finance and providing secure communications to remote areas and less developed nations.

UKRI Gateway to Research · FY 2025 · 2025-03

Digital computing platforms, from sensors to supercomputers, are vital for many branches of research and innovation. Increasingly, they are either accelerated by special-purpose hardware - notably in the realm of AI - or act themselves as accelerators to traditional digital research infrastructure (DRI). Such accelerated compute has the potential to drive transformational change in the frontiers of knowledge through enhanced productivity, yet if, and only if, sufficient expertise is available to translate research ambition into technical solutions. Digital Research Technology Professionals (RTPs), in dedicated RTP posts or covering RTP aspects as part of their academic or industry roles, either cross-cutting or embedded within domain disciplines, irrespective of specialism (e.g. platforms or software), are positioned at the intersection of research and digital technologies and are critical to this endeavour. In the future, they will lead on research software development, system design, deployment and workflow/user environment management to map academic ambitions onto development and deployment. They will champion the translation into computing solutions. This is becoming increasingly challenging as systems become multifaceted, tailored, and heterogeneous, and as the rate of change is itself accelerating. RTPs must be able to draw upon deep technical  knowledge, horizon scan for new developments, navigate research and service delivery models, and develop strong professional skills to advocate and implement changes across diverse research domains and their home institutions. Despite their critical role, the number of RTPs per institution remains low within the UK, with support for professional development heavily reliant upon grassroots activities among RTPs and initiatives by vendors. This is not sustainable in the long-term. SHAREing will therefore establish a shared UK-wide and cross-disciplinary Hub that supports and enables RTPs to accelerate research and innovation through the transition of large-scale compute-, data-intensive and AI workflows into the era of accelerated compute. SHAREing will foster an ecosystem in which RTPs and other stakeholders can design, prototype and assess the best accelerated software-hardware combination for their research, i.e. pioneer solutions. establish structured learning, including upskilling pathways, such that RTPs can acquire all skills to realise accelerated computing projects and to subsequently train others. showcase how RTPs' interventions enable significant research innovation if they transform into dev-ops that lead accelerate computing projects. SHAREing focuses predominantly on the required skills, learning ecosystems facilitating training, and the sharing of expertise, material and core initiatives, but also will contribute towards an ecosystem to apply the acquired skills to enable the use of accelerated compute within the UK's research and innovation landscape. Inclusivity, accessibility and a science-centred ethos will be core to SHAREing, encouraging open-mindedness and critical thinking, respecting that there is often no single `right way' when operating at the forefront of technology and research. It will deliver a talented workforce with core competencies for  accelerated research computing environments. A close collaboration with national, European and international initiatives will strengthen its impact and branding and establish the UK as showcase of the benefits of using a holistic approach to creating a national DRI, where RTPs partner with academics to dev-op the most challenging simulation-, throughput- or AI-workloads.

UKRI Gateway to Research · FY 2025 · 2025-03

Context: In January 2022, the Newcastle Material Culture Analytical Suite (NeMCAS) was established through CapCo, with support from Newcastle's World Class Laboratories fund, upgrading and expanding equipment for imaging and analysis of archaeological and heritage collections. We offer an unrivalled range of expertise in heritage materials including glass, metals, ceramics, environmental and organic artefacts, and are one of the few places in the world that can offer integrated thin section analysis and µCT imaging, optimised for humanities research. NeMCAS has seen considerable internal and external demand in the first 18 months of operation, and the potential applications and benefits are diverse. We have already supported work by academics and stakeholders for example: Additional research for projects funded by AHRC, Leverhulme, EPSRC Enabled new research funded by BBSRC, British Academy, AHRC, EU commission Contributed to research and an exhibition for the Great North Museum Conservation work for English Heritage and Norwich Castle Museum Commercial analysis of concrete additives for a British building materials company Other applications include non-destructive internal imaging of a wide range of cultural objects and archaeological materials, taphonomic experiments to inform preservation and conservation including impacts of climate and environmental change, and multiproxy analysis of archaeological sediments and heritage materials to understand the local environment in which objects have been deposited. Challenge 1: there is a huge demand for sample preparation for large-format thin section analysis (required for a wide range of analytical techniques). Following the closure of facilities at Stirling, there is nowhere else in the UK that can provide this for external users. Researchers now outsource to Europe and USA, where facilities uniformly have backlogs of >6 months. This includes the academic and UK commercial archaeology sectors and IROs such as Historic Environment Scotland. Challenge 2: The combination of 2D and 3D imaging is becoming the standard in areas such as soil science to provide the most comprehensive information on composition and structure. In archaeological and heritage science research however, µCT has not been easily accessible. The majority of µCT facilities in the UK are designed for STEM or Medicine, and are not easily accessible for SHAPE research, especially for the research base in the north. The demand for access to our µCT facilities highlights a growing interest in the potential of this approach to investigate questions related to object composition, ancient technology, for informing conservation, and for recording materials such as teeth/bone and their micro-environmental context prior to destructive sampling for isotopes and aDNA. Crucially, there are no UK facilities where researchers can combine both of these methodologies. Aims and Objectives: Our aims are to: Provide a new dedicated, fully accessible laboratory facility to co-locate equipment for sample preparation and analysis with capacity for large numbers of users Purchase an additional bespoke µCT and high specification PCs, to increase capacity, resolution, and enable rapid automated analysis of high-demand objects Provide a space where materials and their surrounding soil/sediment matrix can be simultaneously sampled for further analyses, in combination with µCT and ultra-high-resolution microscopy Establish the administrative and management infrastructure to enable external users to access the facility for collaborative and commercial work.

UKRI Gateway to Research · FY 2025 · 2025-03

This is a project jointly funded by the National Science Foundation?s Directorate for Geosciences (NSF/GEO) and the National Environment Research Council (NERC) of the United Kingdom (UK) via the NSF/GEO-NERC Lead Agency Agreement. This Agreement allows a single joint US/UK proposal to be submitted and peer-reviewed by the Agency whose investigator has the largest proportion of the budget. Upon successful joint determination of an award recommendation, each Agency funds the proportion of the budget that supports scientists at institutions in their respective countries. Understanding the long-term history and coastal impacts of earthquakes and tsunamis along the Alaska-Aleutian subduction zone (AASZ) is critical for preparing communities for future natural disasters. Despite the AASZ experiencing a series of significant earthquakes in the 20th century, this is only a brief observational window, and the documented events may not represent the full potential of the subduction zone in the future. This research aims to fill the knowledge gap between observed events and prehistoric events by using innovative methods to build thousands of year-long records of past earthquakes and tsunamis. By examining coastal sediments and microfossils, and simulating tsunamis, the researchers will reconstruct the patterns, timing, and size of earthquakes and tsunamis over the last 2,000 years. This work not only advances scientific knowledge but also provides critical data for improving seismic hazard maps used to protect coastal communities in Alaska, the west coast of the United States, and Hawaii. Furthermore, the researchers are committed to sharing their findings with the scientific community, educating students, and increasing public awareness through outreach programs in collaboration with local educators and the NSF-funded Alaska Native Geoscience Learning Experience (ANGLE). The goal is to enhance resilience to future geohazards by fostering a deeper understanding of earthquake and tsunami science. This project will employ innovative microfossil-based paleogeodetic methods and tsunami simulations to reconstruct the patterns, timing, and magnitude of strain accumulation and release during past AASZ earthquakes on the western edge of the 1964 CE rupture. Trench-parallel and trench-perpendicular site transects will establish the lateral and down-dip extent of past ruptures, addressing a significant limitation of most existing studies at global subduction zones. At new and existing sites, the researchers will (1) quantify vertical deformation over the past ~2,000 years using a new diatom-based Bayesian transfer function technique never applied along the AASZ; and (2) map the spatial distribution of tsunami deposition and conduct a systematic exploration of which kinds of slip distributions and subsequent tsunamis best match the spatial pattern of coastal deformation and tsunami deposit extent. This work will be the first to combine geologic evidence of vertical deformation and tsunami deposit extent with a suite of forward models of possible tsunamigenic earthquake locations to evaluate the down-dip and lateral variability of past ruptures along the AASZ, providing important inputs for the advancement of USGS National Seismic Hazard Maps.

UKRI Gateway to Research · FY 2025 · 2025-03

Context: Weight discrimination (hereafter WD) is endemic in healthcare. Of the 43.2m ‘obese’/‘overweight’ UK adults, 74% report discrimination by practitioners. WD takes the form of overtly stigmatising language, an over-emphasis on weight at the expense of other health issues, the unavailability of adequately sized equipment, and more. WD leads to disordered eating, trauma, depression, healthcare avoidance and their knock-on costs. It compounds and deepens existing health inequalities. The Challenge: Several professional and policy bodies have drawn attention to the need for better training provision for healthcare practitioners to recognise and address unintentional discriminatory behaviours. Yet such training is severely lacking - our market validation  demonstrated that only 2.3% of hospitals in England offer their staff specific WD training and 0% of GP surgeries that we surveyed offered their staff any form of WD training. Aim: In response, we propose founding a specialist, profit-generating training organisation - Equweighty - offering bespoke, flexible CPD-accredited training in WD marketed to UK healthcare practitioners. We aim to offer a 'menu' of training formats that can be tailored to specific customer group needs. Our venture will help address the problem of WD in healthcare and its consequent treatment inequity by providing support for more inclusive, person-centred, equitable care benefiting practitioners and patients with better health outcomes. Objectives: We have undertaken market validation which has identified a need for our venture, and we have verified a willingness for customers to pay for our training through a pilot workshop with occupational therapists. Our objectives for ARC Accelerate participation are to (i) develop a business model, (ii) develop a marketing and visibility strategy, and (iii) acquire the skills to pitch for investment. Working with ARC experts on these objectives will help us move towards our next milestones of incorporation and scale-up. Applications and Benefits: After incorporation, our primary application, customer base and beneficiaries are related to the healthcare field. Our initial target customers are the 1.5m NHS employees with annual CPD training budgets of £330-£5K, and practitioner group education leads who commission CPD courses in response to strategic priorities. WD is climbing the policy and practice agenda and increasingly being identified as a priority training area in healthcare. Practitioners who participate in our WD training will benefit from strategies to develop more inclusive practice, their patients will experience more supportive healthcare interactions which empower them as joint decision-makers, and the NHS will benefit from increased patient satisfaction, engagement and cost reduction. We also have stretch goals to expand into secondary markets including marketing our training to the 600K non-clinical NHS staff who require annual EDI training; practitioners in private healthcare organisations; and other sectors where WD occurs – e.g. the travel, hospitality, leisure and retail industries. Measure of Success: Research with student practitioners shows training increases awareness of, and reduces, WD. Active and tailored training involving reflection, empathy, role-specific considerations and patient experiences shows reduced WD and improved weight neutrality in 50-82% of learners. Our own research on Health At Every Size demonstrates weight-neutral practitioners engender better patient engagement, and our pilot workshop demonstrated behaviour change. Others have shown that non-discriminatory, weight-neutral healthcare practice can improve clinical measures like reducing blood pressure and improving mental well-being. Success for Equweighty is an incorporated WD training organisation providing reliable revenue and making a measurable impact on healthcare practice.

UKRI Gateway to Research · FY 2025 · 2025-03

The study of distributed algorithms aims to capture the essence of systems in which multiple networked devices collaborate to complete tasks and solve problems. Since large-scale computing is now dominated by such systems (most notably the Internet, but also, for example, GPU clusters and radio networks), the field is fundamental to understanding which computational tasks are achievable at scale. Many of the most efficient algorithms for problems are randomised, and so results in probability theory are heavily utilised in their analysis. One particular problem when analysing randomised distributed algorithms in relatively sparse networks is that algorithms can succeed locally with reasonably good probability, but not with high probability over the entire network, meaning that we expect the algorithms to fail in some network regions. This is particularly the case in networks whose maximum or average degree is much smaller than their overall size, which is often the case for large real-world networks, e.g. those modelled as scale-free networks. In these situations the Lovász Local Lemma (LLL), a classic result in probability theory, can be used to show that global success is possible. Furthermore, distributed algorithms for the constructive LLL can find such successful outputs, essentially "fixing" algorithms for other problems by amplifying their success probability. The LLL therefore plays a key role in distributed complexity. However, the complexity of the distributed LLL itself remains far from settled, with a substantial gap between upper and lower bounds. The aim of this project is to close this gap, and provide improved distributed algorithms for the LLL. The long-term impact goal is to improve the speed, efficiency, and economy of solving large-scale problems on networks such as the Internet. Main Question: Do faster distributed algorithms exist for the Lovász Local Lemma? To address this question, the PI would leverage insights gained during recent work on the distributed LLL (published at ACM SODA 2023), as well as  extending existing approaches (such as analysing in more depth the structure of the "witness trees" employed in Moser and Tardos's celebrated analysis, work which won the 2020 Gödel Prize). An improved distributed LLL result would have substantial implications to other problems and models, and would lead to many avenues for improving results in applications and special cases, such as graph coloring problems, routing, and scheduling. Upon answering this question, the project would then aim to explore potential applications within and beyond distributed computing. Extension Questions: 1) For which applications of the LLL can we find improved algorithms? 2) Can our methods provide new insight into other models and paradigms, such as Massively Parallel Computation? Ultimately, this project will provide new understanding of distributed and parallel complexity, underpinning what is possible to efficiently compute over large-scale networks. It has the potential to improve the speed and economy of a wide array of distributed tasks such as routing and resource allocation over the Internet.

UKRI Gateway to Research · FY 2025 · 2025-03

Throwing a stone into water excites a wave that decays in distance and time. However, some wave-like phenomena, known as topological objects (TOs), don't behave like this. They are localised in space and trapped in existence for long periods of time. Many such TOs are found in magnetic materials (e.g. domain walls and, latterly, the more exotic skyrmions), but significantly more have been stabilised recently, including hopfions, blochions and merons. Topology provides the organising principle to understand the extraordinary properties of TOs, but also the classification of topological states (TS) of matter, including topological electronic structure and topological order. Magnetic phenomena in materials are some of the oldest discoveries of science and continue to be some of the technologically most useful. Despite this, an understanding of topological magnetism (TM) is relatively recent and is undergoing a rapid change, with key discoveries of new physics, materials and applications. TM systems have a wealth of potentially useful properties and excitations. However, the exploitation of topological magnetic effects in technology is in its infancy and is the long-term motivation of our project, with its combination of materials development and fundamental scientific investigation. The discovery of exotic TOs in magnetic materials and their potential for use as high-density, low-energy components in magnetic storage and in computation applications has made topological magnetism one of the hottest topics in worldwide physics research. The related investigation of TSs has also undergone rapid expansion, and the exploitation of topological states and excitations now holds promise for applications. What the field of TM lacks is the ability to control the topological properties of well-characterized magnetic materials. We will address this fundamental problem to achieve a step-change in the exploitation of topological magnetic states and excitations through the manipulation and elucidation of novel material systems. Our project is organised around two Work Package Clusters, whose key aims are: -Cluster 1 (C1): synthesise/characterize bulk topological-magnetic systems; -Cluster 2 (C2): using a host of techniques including x-ray, neutron and muon spectroscopy, determine the topological properties of novel magnetic TSs and TOs, especially where TOs and TSs coincide/interact, and develop methods to control them. The specific objectives are: C1: -Identify candidate materials exhibiting unconventional spin textures and topological and magnetic states; produce high-quality single crystals. -Optimise their structural, magnetic and electrical properties through chemical and physical manipulation, to promote contol over the topological elements. -This cluster will initially target a number of materials classes for investigation, before concentrating on the most promising. Our target materials classes include: -Frustrated kagome systems hosting magnetic topological phases such as Fe3Sn2 and RMn6Sn6. -Weyl semimetals/Dirac materials of the type RAlX (R=Ce, Pr; X=Si, Ge) -Intermetallics with the ThCr2Si2 structure proposed as hosts of topological structures, such as GdRu2Si2, REMn2Ge2 (RE=rare earth). -Spin liquid candidate materials Na3Co2SbO6 and Na2Co3TeO6. C2: -Determine which novel TOs, previously only stabilized in artificial structures, can be found intrinsically in bulk single-crystal systems; -Elucidate the role of three-dimensional magnetic structure in the stability and properties of those TOs usually treated as purely two-dimensional; -Characterize and control the dynamic processes that dominate the responses of TOs and TS; -Determine and control the ground states, TOs, and TSs occurring in exotic TM systems.

UKRI Gateway to Research · FY 2025 · 2025-03

Molecules cooled to within a millionth of a degree of absolute zero offer a wealth of fascinating possibilities for the exploration of fundamental science, as well as new opportunities to test our understanding of quantum theory and the behaviour of matter at the smallest of scales. Accordingly, many groups around the world are now investigating ultracold molecules and the field is advancing rapidly. Unlike ground-state atoms, molecules can possess an electric dipole moment, leading to tunable long-range interactions and strong coupling to microwave fields. Molecules also offer a rich structure of long-lived internal states associated with rotational and vibrational degrees of freedom. These properties have stimulated applications ranging from sensitive tests of physics beyond the Standard Model and ultracold chemistry to investigations of many-body physics and quantum magnetism. The richness of molecules presents many experimental challenges, however, particularly as we seek to achieve full quantum control over both their internal and motional degrees of freedom. Many of these challenges stem from the lack of a true cycling transition in molecules, which makes their cooling and detection more difficult. We have pioneered an approach that circumvents this problem by associating pre-cooled atoms to form molecules, which are detected by dissociation back into the constituent atoms. We have recently extended this approach to the assembly of individual RbCs molecules from single Rb and Cs atoms using optical tweezers. This technology offers a powerful way to manipulate individual particles and to organise them into perfectly ordered arrays. It has been widely employed for atoms, but only a handful of experiments have applied the technology to ground-state molecules and several challenges still exist. These include: (1) the non-destructive detection of individual molecules, necessary for their rearrangement into perfectly ordered arrays and (2) engineering quantum entanglement between neighbouring molecules for applications ranging from quantum-enhanced sensing to quantum information processing. In this project, we will address these key challenges using an innovative hybrid platform that combines ultracold molecules and Rydberg atoms in optical tweezers. In a Rydberg atom, one electron is excited to a state where it is very far from the nucleus, leading to greatly exaggerated properties. We propose to leverage these properties to engineer strong controlled interactions between a single Rydberg atom and a single polar molecule. We will then harness these interactions to overcome the challenges above. Specifically, our objectives are to: (a) Create 2D tweezer arrays of polar molecules and atoms which will be excited to Rydberg states. (b) Study the strong resonant dipolar interactions between a Rydberg atom and a polar molecule and explore the creation of Giant Polyatomic Rydberg Molecules. (c) Exploit the enhanced interactions between Rydberg atoms and polar molecules to detect the presence of a molecule and use this capability to rearrange molecules into perfectly ordered arrays. (d) To use the strong interactions of a Rydberg atom to engineer entanglement between polar molecules. Through these objectives we will advance our fundamental understanding of ultracold molecules and their interactions with Rydberg atoms. Our techniques will be applicable to other systems and exploitable for quantum-enhanced sensing protocols. Our outcomes will contribute to the development of molecular quantum simulators, impacting a wide range of beneficiaries in the scientific community. More broadly, our research will provide underpinning quantum science and technical advances relevant to the quantum technology community.

UKRI Gateway to Research · FY 2025 · 2025-03

Our project aims to develop "generation after next" quantum sensor arrays that surpass the standard quantum limit (SQL), a fundamental barrier in classical sensing. These “type-2” quantum sensors will deliver unprecedented sensitivity and precision, driving forward the quantum missions of both the UK and Canada. By leveraging quantum entanglement and other advanced quantum resources, these sensors will unlock new, practical applications across key industries and government sectors. For example, the enhanced sensitivity of these sensors could revolutionise medical diagnostics by enabling the early detection of diseases through the identification of anomalous cells in blood samples. In the defence sector, they will improve the detection of submarines beneath ice sheets and enhance magnetic navigation in GPS-denied environments. In mining, they will assist in identifying minerals within rocks and conducting geodesy surveys. To achieve these ambitious goals, we will develop atomic and molecular quantum sensors that exploit the quantum properties of matter cooled to near absolute zero. The intrinsic properties of these sensors, derived from fundamental constants, ensure uniformity and eliminate manufacturing flaws. This results in reliable and accurate measurements that are traceable to the International System of Units, minimising the need for external calibration. While current atomic sensors have demonstrated remarkable capabilities in measuring gravity, time, and magnetic fields, they are often constrained by the SQL. This limitation is particularly critical in scenarios that demand extreme precision or rapid, sensitive measurements. Our approach involves the bottom-up assembly of systems composed of thousands of individual atoms and molecules trapped in laser-generated potentials. This technique allows for precise manipulation and imaging of individual particles. The ability to control these particles at such a fine level, combined with strong interactions among them, enables the creation of large entangled states—crucial for surpassing the SQL. The resulting quantum sensors will be capable of imaging electric and magnetic fields with sub-micron resolution and quantum-enhanced sensitivity. We have defined three key objectives to realise our vision: Enhance capabilities for single-particle control in micron-scale arrays of quantum sensors. Develop methods to image electromagnetic fields using sensor arrays composed of individual atoms, Rydberg atoms, and molecules. Explore and implement protocols to create type-2 quantum sensors that achieve improved sensitivity and metrological advantages over current sensors. Achieving these objectives will significantly advance the state-of-the-art in quantum control and sensing, leading to transformative outcomes for both fundamental science and practical applications. In fundamental physics, our work will push the boundaries of quantum metrology in the terahertz regime and enhance searches for phenomena beyond the Standard Model using molecules. In applied science, our advanced sensors will enable the sensitive detection of electromagnetic fields with sub-micron resolution, thereby improving medical diagnostics and supporting defence applications. In the broader context, this project will contribute to creating a skilled transatlantic quantum workforce, strengthening the alliance between the UK and Canada, and positioning both nations at the forefront of the quantum technology revolution.

UKRI Gateway to Research · FY 2025 · 2025-02

Over the next century, climate change will have significant impacts on dryland ecosystems with some regions already experiencing elevated temperature and hydrological change. Drylands exist on every continent, cover ~46.2% (±0.8%) of the global land area and are home to 3 billion people[1]. Drylands are critical locations for climate change mitigation (via carbon sequestration) due to the high concentrations of soil inorganic carbon (SIC, 1237 Pg C) which exceeds soil organic carbon (SOC) in most drylands (Fig. 1) [2,3]. Despite drylands containing 80% of global SIC[3] (more than the individual permafrost, vegetation, and atmospheric reservoirs) this pool remains relatively understudied. The dryland SIC reservoir is considered relatively stable, however, growing evidence indicates SIC instability due to climate and land use change[4–6] contributing to the degradation of 5.43 million Km2 of drylands over the past 35 years[7]. Significant SIC degradation and desertification of drylands has occurred in the Mediterranean and European regions with some soils at the critical limit for providing ecosystem services. Therefore, quantifying the controls on dryland SIC/SOC is an immediate priority for the long-term stability of drylands. The impact of vegetation on dryland carbon cycling is relatively well studied with vegetation type and spatial distribution key controls. However, microbiology are the key drivers of the carbon cycle but the role of bacteria, archaea, and fungi in SIC/SOC synthesis and preservation remains elusive particularly in drylands that contain high biodiversity and are ecological hotspots. Microbes transfer carbon between the SOC and SIC pools through complex interactions between microbial communities, plant roots and mycorrhiza, and organo-mineral complexes and are controlled by biophysical parameters which may have non-linear and discontinuous influence across climate zones. Due to the spatial heterogeneity of drylands, the biophysical controls on SIC/SOC microbial carbon cycling could vary significantly in semiarid drylands due to the complexity of habitat types and differences in temperature and hydrological baselines. Therefore, the aim of this research is to establish the biophysical controls on microbial carbon cycling of the SOC and SIC pools in semiarid drylands. This proposal focusses on 3 semiarid dryland biodiversity hotspots: Makgadikgadi Basin (Botswana), and the islands of Lesvos and Samothraki (Greece). Using an interdisciplinary approach that bridges biology and chemistry, within a geographical context, this project will address the research questions: What are the key pathways of microbial carbon synthesis in semiarid dryland complexes? How is SOC and SIC degraded and preserved in semiarid dryland complexes? What impact do biophysical controls have on microbial carbon cycling in semiarid drylands? This project examines the full complement of biomolecules, including DNA/RNA (metagenomics/metatranscriptomics) to characterise the microbial community and metabolic potential, the speciation of carbon (geochemistry) to assess the SIC/SOC pools, and lipid distributions (lipidomics) to identify the transformation of carbon during synthesis and preservation. Using both environmental observation and laboratory experiments, the response of the microbial carbon cycle to individual and confounding climatic controls (temperature and hydrological change) will be tested. Combining “omics” based methodologies with geochemistry offers a novel approach and will be the first systematic analysis of microbial carbon cycling combined with omics in the Makgadikgadi Basin (Botswana), Lesvos, and Samothraki (Greece). This project will establish the diversity of bacterial, archaea and fungi and resolve the biophysical controls on the SIC/SOC carbon pools and establish the stability of SIC under changing environmental conditions.

UKRI Gateway to Research · FY 2025 · 2025-02

This proposal builds on the UK element of a highly successful JPICH Cultural Heritage (Conservation, Protection and Use call) project called 'Inspiring Rural Heritage' (IRIS). That research, which ended in January 2024, explored the contribution of local farmers in sustaining their rural upland environment in the UK, Italy, Spain, France, Montenegro. The UK JPICH case study centred on the hill-farmers of the Cheviot Hills in Northumberland and gathered evidence through 19 hours of in-person structured oral interviews with shepherds, farmers, land managers and communities. This was complemented by fresh research into historical processes and land use practices through the analysis of archaeological sites, documents, maps and unpublished surveys (earthworks, excavations, watching briefs, standing buildings on farms). Workshops with local stakeholders delivered a new understanding of their expertise and traditions and contributed to a genuinely collaborative approach which has generated fresh possibilities. Now we wish to take our project further and embed our new understanding in local communities, particularly local schools, community groups for older adults, and the many visitors to the area, which is widely known for its cultural heritage and landscapes and falls within the Northumberland National Park. For this we require support for new elements of outreach which would build on the strengths of our results. These new activities are 1) a series of podcast episodes for local residents and visitors to the area incorporating oral history clips drawn from our existing archive of interviews and linked to new local artwork commissioned by Glendale Gateway Trust (the local community development trust) and Wooler Parish Council, 2) a resource pack of user-friendly interactive information adaptable for in-person delivery to local schools and community groups for older people, particularly those with dementia or experiencing social isolation, and 3) a permanent display in the local community information centre for residents and visitors. The podcast series, resource pack and display will be launched together at an event in the local area which we will organise in collaboration with our local partners. The different outreach elements will be connected to each other, each forming part of an integrated whole (e.g. QR codes on the display will link to the podcast series) and we will promote these resources through local authorities, local tour guides, charities and landowners, all of whom are project partners.