9 resultados para Quantum Chromodynamics, Helicity Rates, One-Loop Corrections, Bremsstrahlung Contributions, Heavy Quarks, Standard Model

em University of Queensland eSpace - Australia


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We investigate the critical behavior of the spectral weight of a single quasiparticle, one of the key observables in experiment, for the particular case of the transverse Ising model. Series expansions are calculated for the linear chain and the square and simple cubic lattices. For the chain model, a conjectured exact result is discovered. For the square and simple cubic lattices, series analyses are used to estimate the critical exponents. The results agree with the general predictions of Sachdev [Quantum Phase Transitions (Cambridge University Press, Cambridge, England, 1999)].

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We present experimental results on the measurement of fidelity decay under contrasting system dynamics using a nuclear magnetic resonance quantum information processor. The measurements were performed by implementing a scalable circuit in the model of deterministic quantum computation with only one quantum bit. The results show measurable differences between regular and complex behavior and for complex dynamics are faithful to the expected theoretical decay rate. Moreover, we illustrate how the experimental method can be seen as an efficient way for either extracting coarse-grained information about the dynamics of a large system or measuring the decoherence rate from engineered environments.

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This article is a short introduction to and review of the cluster-state model of quantum computation, in which coherent quantum information processing is accomplished via a sequence of single-qubit measurements applied to a fixed quantum state known as a cluster state. We also discuss a few novel properties of the model, including a proof that the cluster state cannot occur as the exact ground state of any naturally occurring physical system, and a proof that measurements on any quantum state which is linearly prepared in one dimension can be efficiently simulated on a classical computer, and thus are not candidates for use as a substrate for quantum computation.

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We report new experiments that test quantum dynamical predictions of polarization squeezing for ultrashort photonic pulses in a birefringent fiber, including all relevant dissipative effects. This exponentially complex many-body problem is solved by means of a stochastic phase-space method. The squeezing is calculated and compared to experimental data, resulting in excellent quantitative agreement. From the simulations, we identify the physical limits to quantum noise reduction in optical fibers. The research represents a significant experimental test of first-principles time-domain quantum dynamics in a one-dimensional interacting Bose gas coupled to dissipative reservoirs.

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What resources are universal for quantum computation? In the standard model of a quantum computer, a computation consists of a sequence of unitary gates acting coherently on the qubits making up the computer. This requirement for coherent unitary dynamical operations is widely believed to be the critical element of quantum computation. Here we show that a very different model involving only projective measurements and quantum memory is also universal for quantum computation. In particular, no coherent unitary dynamics are involved in the computation. (C) 2003 Elsevier Science B.V. All rights reserved.

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By stochastic modeling of the process of Raman photoassociation of Bose-Einstein condensates, we show that, the farther the initial quantum state is from a coherent state, the farther the one-dimensional predictions are from those of the commonly used zero-dimensional approach. We compare the dynamics of condensates, initially in different quantum states, finding that, even when the quantum prediction for an initial coherent state is relatively close to the Gross-Pitaevskii prediction, an initial Fock state gives qualitatively different predictions. We also show that this difference is not present in a single-mode type of model, but that the quantum statistics assume a more important role as the dimensionality of the model is increased. This contrasting behavior in different dimensions, well known with critical phenomena in statistical mechanics, makes itself plainly visible here in a mesoscopic system and is a strong demonstration of the need to consider physically realistic models of interacting condensates.

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The demand for palliative care is increasing, yet there are few data on the best models of care nor well-validated interventions that translate current evidence into clinical practice. Supporting multidisciplinary patient-centered palliative care while successfully conducting a large clinical trial is a challenge. The Palliative Care Trial (PCT) is a pragmatic 2 x 2 x 2 factorial cluster randomized controlled trial that tests the ability of educational outreach visiting and case conferencing to improve patient-based outcomes such as performance status and pain intensity. Four hundred sixty-one consenting patients and their general practitioners (GPs) were randomized to the following: (1) GP educational outreach visiting versus usual care, (2) Structured patient and caregiver educational outreach visiting versus usual care and (3) A coordinated palliative care model of case conferencing versus the standard model of palliative care in Adelaide, South Australia (3:1 randomization). Main outcome measures included patient functional status over time, pain intensity, and resource utilization. Participants were followed longitudinally until death or November 30, 2004. The interventions are aimed at translating current evidence into clinical practice and there was particular attention in the trial's design to addressing common pitfalls for clinical studies in palliative care. Given the need for evidence about optimal interventions and service delivery models that improve the care of people with life-limiting illness, the results of this rigorous, high quality clinical trial will inform practice. Initial results are expected in mid 2005. (c) 2005 Elsevier Inc. All rights reserved.

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This paper considers a model-based approach to the clustering of tissue samples of a very large number of genes from microarray experiments. It is a nonstandard problem in parametric cluster analysis because the dimension of the feature space (the number of genes) is typically much greater than the number of tissues. Frequently in practice, there are also clinical data available on those cases on which the tissue samples have been obtained. Here we investigate how to use the clinical data in conjunction with the microarray gene expression data to cluster the tissue samples. We propose two mixture model-based approaches in which the number of components in the mixture model corresponds to the number of clusters to be imposed on the tissue samples. One approach specifies the components of the mixture model to be the conditional distributions of the microarray data given the clinical data with the mixing proportions also conditioned on the latter data. Another takes the components of the mixture model to represent the joint distributions of the clinical and microarray data. The approaches are demonstrated on some breast cancer data, as studied recently in van't Veer et al. (2002).

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In deregulated electricity market, modeling and forecasting the spot price present a number of challenges. By applying wavelet and support vector machine techniques, a new time series model for short term electricity price forecasting has been developed in this paper. The model employs both historical price and other important information, such as load capacity and weather (temperature), to forecast the price of one or more time steps ahead. The developed model has been evaluated with the actual data from Australian National Electricity Market. The simulation results demonstrated that the forecast model is capable of forecasting the electricity price with a reasonable forecasting accuracy.