22,756 research outputs found

    Techniques of linear prediction, with application to oceanic and atmospheric fields in the tropical Pacific

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    The problem of constructing optimal linear prediction models by multivariance regression methods is reviewed. It is well known that as the number of predictors in a model is increased, the skill of the prediction grows, but the statistical significance generally decreases. For predictions using a large number of candidate predictors, strategies are therefore needed to determine optimal prediction models which properly balance the competing requirements of skill and significance. The popular methods of coefficient screening or stepwise regression represent a posteriori predictor selection methods and therefore cannot be used to recover statistically significant models by truncation if the complete model, including all predictors, is statistically insignificant. Higher significance can be achieved only by a priori reduction of the predictor set. To determine the maximum number of predictors which may be meaningfully incorporated in a model, a model hierarchy can be used in which a series of best fit prediction models is constructed for a (prior defined) nested sequence of predictor sets, the sequence being terminated when the significance level either falls below a prescribed limit or reaches a maximum value. The method requires a reliable assessment of model significance. This is characterized by a quadratic statistic which is defined independently of the model skill or artificial skill. As an example, the method is applied to the prediction of sea surface temperature anomalies at Christmas Island (representative of sea surface temperatures in the central equatorial Pacific) and variations of the central and east Pacific Hadley circulation (characterized by the second empirical orthogonal function (EOF) of the meridional component of the trade wind anomaly field) using a general multiple‐time‐lag prediction matrix. The ordering of the predictors is based on an EOF sequence, defined formally as orthogonal variables in the composite space of all (normalized) predictors, irrespective of their different physical dimensions, time lag, and geographic position. The choice of a large set of 20 predictors at 12 time lags yields significant predictability only for forecast periods of 3 to 5 months. However, a prior reduction of the predictor set to 4 predictors at 10 time lags leads to 95% significant predictions with skill values of the order of 0.4 to 0.7 up to 6 or 8 months. For infinitely long time series the construction of optimal prediction models reduces essentially to the problem of linear system identification. However, the model hierarchies normally considered for the simulation of general linear systems differ in structure from the model hierarchies which appear to be most suitable for constructing pure prediction models. Thus the truncation imposed by statistical significance requirements can result in rather different models for the two cases. The relation between optimal prediction models and linear dynamical models is illustrated by the prediction of east‐west sea level changes in the equatorial Pacific from wind field anomalies. It is shown that the optimal empirical prediction is statistically consistent in this case with both the first‐order relaxation and damped oscillator models recently proposed by McWilliams and Gent (but with somewhat different model parameters than suggested by the authors). Thus the data do not allow a distinction between the two physical models; the simplest acceptable model is the first‐order damped response. Finally, the problem of estimating forecast skill is discussed. It is usually stated that the forecast skill is smaller than the true skill, which in turn is smaller than the hindcast skill, by an amount which in both cases is approximately equal to the artificial skill. However, this result applies to the mean skills averaged over the ensemble of all possible hindcast data sets, given the true model. Under the more appropriate side condition of a given hindcast data set and an unknown true model, the estimation of the forecast skill represents a problem of statistical inference and is dependent on the assumed prior probability distribution of true models. The Bayesian hypothesis of a uniform prior distribution yields an average forecast skill equal to the hindcast skill, but other (equally acceptable) assumptions yield lower forecast skills more compatible with the usual hindcast‐averaged expressio

    Perceived efficacy and attitudes towards genetic science and science governance

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    This is the postprint version of the Article. The official published version can be obtained from the link below - © 2010 SAGE Publications.Arguments for public involvement in science and technology are often based on ideas of developing a more capable public and the assumed effects this may have for science. However, such a relationship is yet to be sufficiently explored and recent work indicates that a more involved public may have counterintuitive effects. Using nationally representative survey data for the UK and Northern Ireland, the effects of the public's own beliefs about involvement are explored. Developing the concept of "belief in public efficacy," findings suggest those who believe that the public might be able to affect the course of decision making have less approving attitudes towards future applications of genetic science; however, an individual's political efficacy does not significantly influence these attitudes. Furthermore, political efficacy and belief in public efficacy have some distinct and opposing relationships with the principles of governance people prefer. Overall, findings provide support for suggestions that it is simplistic to consider increasing public involvement as a way of increasing the approval of risky new technologies

    Quantum retrodiction in open systems

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    Quantum retrodiction involves finding the probabilities for various preparation events given a measurement event. This theory has been studied for some time but mainly as an interesting concept associated with time asymmetry in quantum mechanics. Recent interest in quantum communications and cryptography, however, has provided retrodiction with a potential practical application. For this purpose quantum retrodiction in open systems should be more relevant than in closed systems isolated from the environment. In this paper we study retrodiction in open systems and develop a general master equation for the backward time evolution of the measured state, which can be used for calculating preparation probabilities. We solve the master equation, by way of example, for the driven two-level atom coupled to the electromagnetic field.Comment: 12 pages, no figure

    Comparison of consumer attitudes between Cyprus and Latvia: An evaluation of effect of setting on consumer preferences in the water industry

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    This is the post-print version of the article. The official published version can be obtained from th link below - Copyright @ SpringerModels approaching consumer expectations of their water supplier from a risk perspective suggest that consumers primarily and overwhelmingly want safe drinking water supply. In this study consumer preferences in the water sector are investigated in two contrasting case studies: Cyprus, where there have been significant quantity and continuity of supply issues, and Riga, where there have been water quality issues. While water quality is undoubtedly the main priority of water consumers in Riga, in Cyprus consumers indicate that they prioritise a more reliable service even though many are sufficiently dissatisfied with water quality that they do not drink the tap water. The analysis of consumer attitudes in the two case studies suggests that when water supply is unreliable, reliability takes precedence; once it is reliable quality issues come to the fore.This research was carried out as part of Work Area 6 of the TECHNEAU project, an integrated project funded under FP6 of the European Commission, grant number: 018320

    Measurement-driven dynamics for a coherently-excited atom

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    The phenomenon of telegraphing in a measurement-driven two-level atom was noted in Cresser et al. [Cresser, J.D.; Barnett, S.M.; Jeffers, J.; Pegg, D.T. Opt. Commun. 2006, 264, 352361]. Here we introduce two quantitative measures of telegraphing: one based on the accumulated measurement record and one on the evolution of the quantum state. We use these to analyse the dynamics of the atom over a wide range of parameters. We find, in particular, that the measures provide broadly similar statistics when the measurements are frequent, but differ widely when measurements are sparse. This is in line with intuition, and demonstrates the utility of both measures

    Retrodiction as a tool for micromaser field measurements

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    We use retrodictive quantum theory to describe cavity field measurements by successive atomic detections in the micromaser. We calculate the state of the micromaser cavity field prior to detection of sequences of atoms in either the excited or ground state, for atoms that are initially prepared in the excited state. This provides the POM elements, which describe such sequences of measurements.Comment: 20 pages, 4(8) figure

    Steady-state entanglement in a double-well Bose-Einstein condensate through coupling to a superconducting resonator

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    We consider a two-component Bose-Einstein condensate in a double-well potential, where the atoms are magnetically coupled to a single-mode of the microwave field inside a superconducting resonator. We find that the system has the different dark-state subspaces in the strong- and weak-tunneling regimes, respectively. In the limit of weak tunnel coupling, steady-state entanglement between the two spatially separated condensates can be generated by evolving to a mixture of dark states via the dissipation of the photon field. We show that the entanglement can be faithfully indicated by an entanglement witness. Long-lived entangled states are useful for quantum information processing with atom-chip devices.Comment: 9 pages, 7 figures, minor revisio

    Simulation of large turbulent structures with the parabolic Navier-Stokes equations

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    The theoretical basis for well posed marching of a Parabolic Navier-Stokes (PNS) computational technique for supersonic flow is discussed and examples given to verify the analysis. It is demonstrated that stable computations can be made even with very small steps in the marching direction. The method is applied to cones at large angle of attack in high Reynolds number, supersonic flow. Streamline trajectories generated from the numerical solutions demonstrate the development of vortex structures on the lee side of the cone

    A Normal-Mode Approach to Jovian Atmospheric Dynamics

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    We propose a nonlinear, quasi-geostrophic, baroclinic model of Jovian atmospheric dynamics, in which vertical variations of velocity are represented by a truncated sum over a complete set of orthogonal functions obtained by a separation of variables of the linearized quasi-geostrophic potential vorticity equation. A set of equations for the time variation of the mode amplitudes in the nonlinear case is then derived. We show that for a planet with a neutrally stable, fluid interior instead of a solid lower boundary, the baroclinic mode represents motions in the interior, and is not affected by the baroclinic modes. One consequence of this is that a normal-mode model with one baroclinic mode is dynamically equivalent to a one layer model with solid lower topography. We also show that for motions in Jupiter's cloudy lower troposphere, the stratosphere behaves nearly as a rigid lid, so that the normal-mode model is applicable to Jupiter. We test the accuracy of the normal-mode model for Jupiter using two simple problem forced, vertically propagating Rossby waves, using two and three baroclinic modes and baroclinic instability, using two baroclinic modes. We find that the normal-road model provide qualitatively correct results, even with only a very limited number of vertical degrees of freedom
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