The long-range Falicov-Kimball model and the amorphous Kitaev model: Quantum many-body systems I have known and loved

Large systems of interacting objects can give rise to a rich array of emergent behaviours. Make those objects quantum and the possibilities only expand. Interacting quantum many-body systems, as such systems are called, include essentially all physical systems. Luckily, we don't usually need to consider this full quantum many-body description. The world at the human scale is essentially classical (not quantum), while at the microscopic scale of condensed matter physics we can often get by without interactions. Strongly correlated materials, however, do require the full description. Some of the most exciting topics in modern condensed matter fall under this umbrella: the spin liquids, the fractional quantum Hall effect, high temperature superconductivity and much more. Unfortunately, strongly correlated materials are notoriously difficult to study, defying many of the established theoretical techniques within the field. Enter exactly solvable models, these are interacting quantum many-body systems with extensively many local symmetries. The symmetries give rise to conserved charges. These charges break the model up into many non-interacting quantum systems which are more amenable to standard theoretical techniques. This thesis will focus on two such exactly solvable models. The first, the Falicov-Kimball (FK) model is an exactly solvable limit of the famous Hubbard model which describes itinerant fermions interacting with a classical Ising background field. Originally introduced to explain metal-insulator transitions, it has a rich set of ground state and thermodynamic phases. Disorder or interactions can turn metals into insulators and the FK model features both transitions. We will define a generalised FK model in 1D with long-range interactions. This model shows a similarly rich phase diagram to its higher dimensional cousins. We use an exact Markov Chain Monte Carlo method to map the phase diagram and compute the energy resolved localisation properties of the fermions. This allows us to look at how the move to 1D affects the physics of the model. We show that the model can be understood by comparison to a simpler model of fermions coupled to binary disorder. The second, the Kitaev Honeycomb (KH) model, was the one of the first solvable 2D models with a Quantum Spin Liquid (QSL) ground state. QSLs are generally expected to arise from Mott insulators, when frustration prevents magnetic ordering all the way to zero temperature. The QSL state defies the traditional Landau-Ginzburg-Wilson paradigm of phases being defined by local order parameters. It is instead a topologically ordered phase. Recent work generalising non-interacting topological insulator phases to amorphous lattices raises the question of whether interacting phases like the QSLs can be similarly generalised. We extend the KH model to random lattices with fixed coordination number three generated by Voronoi partitions of the plane. We show that this model remains solvable and hosts a chiral amorphous QSL ground state. The presence of plaquettes with an odd number of sides leads to a spontaneous breaking of time reversal symmetry. We unearth a rich phase diagram displaying Abelian as well as a non-Abelian QSL phases with a remarkably simple ground state flux pattern. Furthermore, we show that the system undergoes a phase transition to a conducting thermal metal state and discuss possible experimental realisations.Open Acces

An Exact Chiral Amorphous Spin Liquid

Topological insulator phases of non-interacting particles have been generalized from periodic crystals to amorphous lattices, which raises the question whether topologically ordered quantum many-body phases may similarly exist in amorphous systems? Here we construct a soluble chiral amorphous quantum spin liquid by extending the Kitaev honeycomb model to random lattices with fixed coordination number three. The model retains its exact solubility but the presence of plaquettes with an odd number of sides leads to a spontaneous breaking of time reversal symmetry. We unearth a rich phase diagram displaying Abelian as well as a non-Abelian quantum spin liquid phases with a remarkably simple ground state flux pattern. Furthermore, we show that the system undergoes a finite-temperature phase transition to a conducting thermal metal state and discuss possible experimental realisations.Comment: 5 pages, 3 figure

Modelling effects of variability in feeding rate on growth – a vital step for DEB-TKTD modelling

A major limitation of dietary toxicity studies on rodents is that food consumption often differs between treatments. The control treatment serves as a reference of how animals would have grown if not for the toxicant in their diet, but this comparison unavoidably conflates the effects of toxicity and feeding rate on body weight over time. A key advantage of toxicity models based on dynamic energy budget theory (DEB) is that chemical stress and food consumption are separate model inputs, so their effects on growth rate can be separated. To reduce data requirements, DEB convention is to derive a simplified feeding input, f, from food availability; its value ranges from zero (starvation) to one (food available ad libitum). Observed food consumption in dietary toxicity studies shows that, even in the control treatment, rats limit their food consumption, contradicting DEB assumptions regarding feeding rate. Relatively little work has focused on addressing this mismatch, but accurately modelling the effects of food intake on growth rate is essential for the effects of toxicity to be isolated. This can provide greater insight into the results of chronic toxicity studies and allows accurate extrapolation of toxic effects from laboratory data. Here we trial a new method for calculating f, based on the observed relationships between food consumption and body size in laboratory rats. We compare model results with those of the conventional DEB method and a previous effort to calculate f using observed food consumption data. Our results showed that the new method improved model accuracy while modelled reserve dynamics closely followed observed body fat percentage over time. The new method assumes that digestive efficiency increases with body size. Verifying this relationship through data collection would strengthen the basis of DEB theory and support the case for its use in ecological risk assessment

A theory-based electronic learning intervention to support appropriate antibiotic prescribing by nurses and pharmacists: intervention development and feasibility study protocol

Introduction: Nurse and pharmacist independent prescribers manage patients with respiratory tract infections and are responsible for around 8% of all primary care antibiotic prescriptions. A range of factors influence the prescribing behaviour of these professionals, however, there are no interventions available specifically to support appropriate antibiotic prescribing behaviour by these groups. The aims of this paper are to describe (1) the development of an intervention to support appropriate antibiotic prescribing by nurse and pharmacist independent prescribers and (2) an acceptability and feasibility study designed to test its implementation with these prescribers. Method and analysis: Development of intervention: a three stage, eight step method was used to identify relevant determinants of behaviour change and intervention components based on the Behaviour Change Wheel. The intervention is an online resource comprising underpinning knowledge and an interactive animation with a variety of open and closed questions to assess understanding. Acceptability and feasibility of intervention: nurse and pharmacist prescribers (n=12-15) will use the intervention. Evaluation includes semi-structured interviews to capture information about how the user reacts to the design, delivery and content of the intervention and influences on understanding and engagement, and a pre-post survey to assess participants perceptions of the impact of the intervention on knowledge, confidence and usefulness in terms of application to practice. Taking an initial inductive approach, data from interview transcripts will be coded and then analysed to derive themes. These themes will then be deductively mapped to the Capability, Opportunity, Motivation-Behaviour (COM-B) model. Descriptive statistics will be used to analyse the survey data, and trends identified. Ethics and dissemination: Ethical approval for the study has been provided by the School of Healthcare Sciences Research Governance and Ethics Committee, Cardiff University. The findings will be disseminated via publication in peer reviewed journals and through conference presentations

Exploring the association of the discharge medicines review with patient hospital readmissions through national routine data linkage in Wales: a retrospective cohort study

Objective To evaluate the association of the discharge medicines review (DMR) community pharmacy service with hospital readmissions through linking National Health Service data sets. Design Retrospective cohort study. Setting All hospitals and 703 community pharmacies across Wales. Participants Inpatients meeting the referral criteria for a community pharmacy DMR. Interventions Information related to the patient’s medication and hospital stay is provided to the community pharmacists on discharge from hospital, who undertake a two-part service involving medicines reconciliation and a medicine use review. To investigate the association of this DMR service with hospital readmission, a data linking process was undertaken across six national databases. Primary outcome Rate of hospital readmission within 90 days for patients with and without a DMR part 1 started. Secondary outcome Strength of association of age decile, sex, deprivation decile, diagnostic grouping and DMR type (started or not started) with reduction in readmission within 90 days. Results 1923 patients were referred for a DMR over a 13-month period (February 2017–April 2018). Provision of DMR was found to be the most significant attributing factor to reducing likelihood of 90-day readmission using χ2 testing and classification methods. Cox regression survival analysis demonstrated that those receiving the intervention had a lower hospital readmission rate at 40 days (p<0.000, HR: 0.59739, CI 0.5043 to 0.7076). Conclusions DMR after a hospital discharge is associated with a reduction in risk of hospital readmission within 40 days. Linking data across disparate national data records is feasible but requires a complex processual architecture. There is a significant value for integrated informatics to improve continuity and coherency of care, and also to facilitate service optimisation, evaluation and evidenced-based practice

Discovery of shale gas in organic rich Jurassic successions, Adventdalen, Central Spitsbergen, Norway

Thermogenic dry gas flowed from Jurassic sections in the DH5R research well drilled onshore in Adventdalen, central Spitsbergen, Arctic Norway. The DH5R gas originates from the organic-rich units of the mudstone-dominated Middle Jurassic to Lower Cretaceous Agardhfjellet Formation, which is the onshore equivalent to the Fuglen Formation and the prolific oil and gas generating Hekkingen Formation in the southern Barents Shelf. Low-permeable, low-porosity sandstones from the Upper Triassic De Geerdalen Formation of the neighbouring DH4 well were oil-stained and gas was also collected from this interval. Gas from the two stratigraphic intervals have different compositions; the gas from the Agardhfjellet Formation is drier and isotopically heavier than the gas from the Upper Triassic succession. Both gases originated from source rocks of maturity near the end of the oil window (1.1 < Ro < 1.4% Ro). Maceral analyses of the Agardhfjellet Formation indicate that the more silty parts contain a high percentage of vitrinite-rich type III kerogen, whereas the clay-dominated parts are rich in liptinitic type II kerogen. The Agardhfjellet Formation has therefore the potential to generate both oil and gas. Several simulations based on pressure data and flow rates from the DH5R well were run to evaluate if the gas accumulation in the Agardhfjellet Formation is producible, i.e., can it be commercial shale gas. The models demonstrate how changes in the drainage area size and form, well types (vertical versus horizontal), number and length of induced fractures and thickness of the Agardhfjellet Formation affect gas production rates and producible volumes. Despite uncertainties in the input data, simulations indicate that the shale gas accumulation characterised in Adventdalen is producible. This gas can have major environmental benefits as an alternative for local power generation compared to coal.publishedVersio

Moving Large Data Sets Over High-Performance Long Distance Networks

In this project we look at the performance characteristics of three tools used to move large data sets over dedicated long distance networking infrastructure. Although performance studies of wide area networks have been a frequent topic of interest, performance analyses have tended to focus on network latency characteristics and peak throughput using network traffic generators. In this study we instead perform an end-to-end long distance networking analysis that includes reading large data sets from a source file system and committing large data sets to a destination file system. An evaluation of end-to-end data movement is also an evaluation of the system configurations employed and the tools used to move the data. For this paper, we have built several storage platforms and connected them with a high performance long distance network configuration. We use these systems to analyze the capabilities of three data movement tools: BBcp, GridFTP, and XDD. Our studies demonstrate that existing data movement tools do not provide efficient performance levels or exercise the storage devices in their highest performance modes. We describe the device information required to achieve high levels of I/O performance and discuss how this data is applicable in use cases beyond data movement performance

A metagenomic snapshot of taxonomic and functional diversity in an Alpine glacier cryoconite ecosystem:Alpine cryoconite metagenome

Cryoconite is a microbe–mineral aggregate which darkens the ice surface of glaciers. Microbial process and marker gene PCR-dependent measurements reveal active and diverse cryoconite microbial communities on polar glaciers. Here, we provide the first report of a cryoconite metagenome and culture-independent study of alpine cryoconite microbial diversity. We assembled 1.2 Gbp of metagenomic DNA sequenced using an Illumina HiScanSQ from cryoconite holes across the ablation zone of Rotmoosferner in the Austrian Alps. The metagenome revealed a bacterially-dominated community, with Proteobacteria (62% of bacterial-assigned contigs) and Bacteroidetes (14%) considerably more abundant than Cyanobacteria (2.5%). Streptophyte DNA dominated the eukaryotic metagenome. Functional genes linked to N, Fe, S and P cycling illustrated an acquisitive trend and a nitrogen cycle based upon efficient ammonia recycling. A comparison of 32 metagenome datasets revealed a similarity in functional profiles between the cryoconite and metagenomes characterized from other cold microbe–mineral aggregates. Overall, the metagenomic snapshot reveals the cryoconite ecosystem of this alpine glacier as dependent on scavenging carbon and nutrients from allochthonous sources, in particular mosses transported by wind from ice-marginal habitats, consistent with net heterotrophy indicated by productivity measurements. A transition from singular snapshots of cryoconite metagenomes to comparative analyses is advocated