Universal Quantum Computation with the Exchange Interaction

Experimental implementations of quantum computer architectures are now being investigated in many different physical settings. The full set of requirements that must be met to make quantum computing a reality in the laboratory [1] is daunting, involving capabilities well beyond the present state of the art. In this report we develop a significant simplification of these requirements that can be applied in many recent solid-state approaches, using quantum dots [2], and using donor-atom nuclear spins [3] or electron spins [4]. In these approaches, the basic two-qubit quantum gate is generated by a tunable Heisenberg interaction (the Hamiltonian is $H_{ij}=J(t){\vec S}_i\cdot{\vec S}_j$ between spins $i$ and $j$), while the one-qubit gates require the control of a local Zeeman field. Compared to the Heisenberg operation, the one-qubit operations are significantly slower and require substantially greater materials and device complexity, which may also contribute to increasing the decoherence rate. Here we introduce an explicit scheme in which the Heisenberg interaction alone suffices to exactly implement any quantum computer circuit, at a price of a factor of three in additional qubits and about a factor of ten in additional two-qubit operations. Even at this cost, the ability to eliminate the complexity of one-qubit operations should accelerate progress towards these solid-state implementations of quantum computation.Comment: revtex, 2 figures, this version appeared in Natur

Early characterization of the severity and transmissibility of pandemic influenza using clinical episode data from multiple populations

The potential rapid availability of large-scale clinical episode data during the next influenza pandemic suggests an opportunity for increasing the speed with which novel respiratory pathogens can be characterized. Key intervention decisions will be determined by both the transmissibility of the novel strain (measured by the basic reproductive number R0) and its individual-level severity. The 2009 pandemic illustrated that estimating individual-level severity, as described by the proportion pC of infections that result in clinical cases, can remain uncertain for a prolonged period of time. Here, we use 50 distinct US military populations during 2009 as a retrospective cohort to test the hypothesis that real-time encounter data combined with disease dynamic models can be used to bridge this uncertainty gap. Effectively, we estimated the total number of infections in multiple early-affected communities using the model and divided that number by the known number of clinical cases. Joint estimates of severity and transmissibility clustered within a relatively small region of parameter space, with 40 of the 50 populations bounded by: pC, 0.0133-0.150 and R0, 1.09-2.16. These fits were obtained despite widely varying incidence profiles: some with spring waves, some with fall waves and some with both. To illustrate the benefit of specific pairing of rapidly available data and infectious disease models, we simulated a future moderate pandemic strain with pC approximately ×10 that of 2009; the results demonstrating that even before the peak had passed in the first affected population, R0 and pC could be well estimated. This study provides a clear reference in this two-dimensional space against which future novel respiratory pathogens can be rapidly assessed and compared with previous pandemics

Joint PDF modelling of turbulent flow and dispersion in an urban street canyon

The joint probability density function (PDF) of turbulent velocity and concentration of a passive scalar in an urban street canyon is computed using a newly developed particle-in-cell Monte Carlo method. Compared to moment closures, the PDF methodology provides the full one-point one-time PDF of the underlying fields containing all higher moments and correlations. The small-scale mixing of the scalar released from a concentrated source at the street level is modelled by the interaction by exchange with the conditional mean (IECM) model, with a micro-mixing time scale designed for geometrically complex settings. The boundary layer along no-slip walls (building sides and tops) is fully resolved using an elliptic relaxation technique, which captures the high anisotropy and inhomogeneity of the Reynolds stress tensor in these regions. A less computationally intensive technique based on wall functions to represent boundary layers and its effect on the solution are also explored. The calculated statistics are compared to experimental data and large-eddy simulation. The present work can be considered as the first example of computation of the full joint PDF of velocity and a transported passive scalar in an urban setting. The methodology proves successful in providing high level statistical information on the turbulence and pollutant concentration fields in complex urban scenarios.Comment: Accepted in Boundary-Layer Meteorology, Feb. 19, 200

Metabolic state alters economic decision making under risk in humans

Background: Animals' attitudes to risk are profoundly influenced by metabolic state (hunger and baseline energy stores). Specifically, animals often express a preference for risky (more variable) food sources when below a metabolic reference point (hungry), and safe (less variable) food sources when sated. Circulating hormones report the status of energy reserves and acute nutrient intake to widespread targets in the central nervous system that regulate feeding behaviour, including brain regions strongly implicated in risk and reward based decision-making in humans. Despite this, physiological influences per se have not been considered previously to influence economic decisions in humans. We hypothesised that baseline metabolic reserves and alterations in metabolic state would systematically modulate decision-making and financial risk-taking in humans. Methodology/Principal Findings: We used a controlled feeding manipulation and assayed decision-making preferences across different metabolic states following a meal. To elicit risk-preference, we presented a sequence of 200 paired lotteries, subjects' task being to select their preferred option from each pair. We also measured prandial suppression of circulating acyl-ghrelin (a centrally-acting orexigenic hormone signalling acute nutrient intake), and circulating leptin levels (providing an assay of energy reserves). We show both immediate and delayed effects on risky decision-making following a meal, and that these changes correlate with an individual's baseline leptin and changes in acyl-ghrelin levels respectively. Conclusions/Significance: We show that human risk preferences are exquisitely sensitive to current metabolic state, in a direction consistent with ecological models of feeding behaviour but not predicted by normative economic theory. These substantive effects of state changes on economic decisions perhaps reflect shared evolutionarily conserved neurobiological mechanisms. We suggest that this sensitivity in human risk-preference to current metabolic state has significant implications for both real-world economic transactions and for aberrant decision-making in eating disorders and obesity

Co-designing Indices for Tailored Seasonal Climate Forecasts in Malawi

In central and southern Malawi, climate variability significantly impacts agricultural production and food availability owing to a high dependence on rain-fed maize production. Seasonal climate forecast information has the potential to inform farmers' agricultural planning, thereby improving preparedness to extreme events. In this paper we describe and evaluate an approach to co-designing and testing agro-climatic indices for use in seasonal forecasts that are tailored to farmer-defined decision-making needs in three districts of central and southern Malawi. Specifically, we aim to (a) identify critical maize specific agro-climatic indices by engaging key stakeholders and farmers; (b) compare and triangulate these indices with the historical climate record in study districts; and (c) analyze empirical relationships between seasonal total rainfall and maize specific indices in order to assess the potential for forecasting them at appropriate seasonal timescales. The identified agro-climatic indices include critical temperature/rainfall thresholds that are directly associated with phenological stages of maize growth with direct implications for maize yield and quality. While there are statistically significant relationships between observed wet season rainfall totals and several agro-climatic indices (e.g., heavy rainfall days and dry spell), the forecast skill of the UK Met Office's coupled initialized global seasonal forecasting system (GloSea5) over Malawi is currently low to provide confident predictions of total wet season rainfall and the agro-climatic indices correlated with it. We reflect on some of the opportunities and challenges associated with integrating farmers' information needs into a seasonal forecast process, through the use of agro-climatic indices

The development of endomycorrhizal root systems VIII. Effects of soil phosphorus and fungal colonization on the concentration of soluble carbohydrates in roots

Concentrations of phosphorus in shoot and soluble carbohydrates (fructose, glucose, sucrose and fructans) in root were measured in non-mycorrhizal and vesicular-arbuscular (VA) mycorrhizal (Glomus mosseae) leek plants (Allium porrum) raised at six concentrations of soil phosphate. In conditions when an increased concentration of soil phosphate reduced VA mycorrhizal infection, the concentrations of soluble carbohydrates in the root were at a maximum. Therefore the hypothesis that greater concentrations of soluble carbohydrates in roots favour VA mycorrhizal infection is discounted. There was a specific effect of VA mycorrhizas, in that infected roots contained a larger concentration of sucrose than did uninfected roots, in plants with similar phosphorus concentrations in dry matter of shoots. We conclude, first, that increased phosphorus supply from either phosphate addition to soil or VA mycorrhizal infection increases concentration of soluble carbohydrates in leek roots and, secondly, that the VA mycorrhizal root behaves as a particularly strong physiological sink when there is an excess concentration of sucrose in the host

Pollination and biological control research: are we neglecting two billion smallholders

Food insecurity is a major world problem, with ca. 870 million people in the world being chronically undernourished. Most of these people live in tropical, developing regions and rely on smallholder farming for food security. Solving the problem of food insecurity is thought to depend, in part, on managing ecosystem services, such as the pollination of crops and the biological control of crop pests, to enhance or maintain food production. Our knowledge regarding regulating ecosystem services in smallholder-farmed (or dualistic) landscapes is limited and whilst pollination has been the focus of considerable research, the provision of natural enemy services, important for every crop worldwide, has been relatively neglected. In order to assess whether ecosystem-service research adequately represents smallholder-farmed landscapes, whilst also considering climatic region and national economic status, we examined the constituent studies of recent quantitative reviews relevant to biological control and pollination. No regulating ecosystem service meta-analysis, to our knowledge, has focussed on smallholder agriculture despite its importance to billions of peoples’ local food security. We found that whilst smallholdings contributed 16% of global farmland area and 83% of the global agricultural population (estimated using FAO’s World Census of Agriculture 2000) only 22 of 190 studies (12%), overall, came from smallholder-farmed landscapes. These smallholder studies mostly concerned coffee production (16 studies). Individual reviews of biological control were significantly and strongly biased towards data from large-scale farming in temperate regions. In contrast pollination reviews included more smallholder studies and were more balanced for climate regions. The high diversity of smallholder-farmed landscapes implies that more research will be needed to understand them compared to large-scale landscapes but we found far more research from the latter. We highlight that these skews in research effort have implications for sustainable intensification and the food security of billions in the developing world. In particular we urge for balance in future ecosystem-services research and synthesis by greater consideration of a diverse range of smallholder-farmed landscapes in Africa and continental Asia

Livelihood and vulnerability in the wake of Typhoon Yolanda: lessons of community and resilience

Livelihood strategies that are crafted in ‘extra-ordinary’ post-disaster conditions should also be able to function once some semblance of normalcy has resumed. This article aims to show that the vulnerability experienced in relation to Typhoon Yolanda was, and continues to be, directly linked to inadequate livelihood assets and opportunities. We examine the extent to which various livelihood strategies lessened vulnerability post-Typhoon Yolanda and argue that creating conditions under which disaster survivors have the freedom to pursue sustainable livelihood is essential in order to foster resilience and reduce vulnerability against future disasters. We offer suggestions to improve future relief efforts, including suggestions made by the survivors themselves. We caution against rehabilitation strategies that knowingly or unknowingly, resurrect pre-disaster vulnerability. Strategies that foster dependency, fail to appreciate local political or ecological conditions or undermine cooperation and cohesion in already vulnerable communities will be bound to fail. Some of the livelihood strategies that we observed post-Typhoon Yolanda failed on some or all of these points. It is important for future policy that these failings are addressed