Quantum computation as geometry

Quantum computers hold great promise for solving interesting computational problems, but it remains a challenge to find efficient quantum circuits that can perform these complicated tasks. Here we show that finding optimal quantum circuits is essentially equivalent to finding the shortest path between two points in a certain curved geometry. By recasting the problem of finding quantum circuits as a geometric problem, we open up the possibility of using the mathematical techniques of Riemannian geometry to suggest new quantum algorithms or to prove limitations on the power of quantum computers.

Quantum computation by communication

We present here a new approach to scalable quantum computing - a 'qubus computer' - which realizes qubit measurement and quantum gates through interacting qubits with a quantum communication bus mode. The qubits could be 'static' matter qubits or 'flying' optical qubits, but the scheme we focus on here is particularly suited to matter qubits. There is no requirement for direct interaction between the qubits. Universal two-qubit quantum gates may be effected by schemes which involve measurement of the bus mode, or by schemes where the bus disentangles automatically and no measurement is needed. In effect, the approach integrates together qubit degrees of freedom for computation with quantum continuous variables for communication and interaction.

Universal quantum computation with continuous-variable cluster states

We describe a generalization of the cluster-state model of quantum computation to continuous-variable systems, along with a proposal for an optical implementation using squeezed-light sources, linear optics, and homodyne detection. For universal quantum computation, a nonlinear element is required. This can be satisfied by adding to the toolbox any single-mode non-Gaussian measurement, while the initial cluster state itself remains Gaussian. Homodyne detection alone suffices to perform an arbitrary multimode Gaussian transformation via the cluster state. We also propose an experiment to demonstrate cluster-based error reduction when implementing Gaussian operations.

Quantum computation using weak nonlinearities: Robustness against decoherence

We investigate decoherence effects in the recently suggested quantum-computation scheme using weak nonlinearities, strong probe coherent fields, detection, and feedforward methods. It is shown that in the weak-nonlinearity-based quantum gates, decoherence in nonlinear media can be made arbitrarily small simply by using arbitrarily strong probe fields, if photon-number-resolving detection is used. On the contrary, we find that homodyne detection with feedforward is not appropriate for this scheme because in this case decoherence rapidly increases as the probe field gets larger.

Incremental cost-effectiveness of exercise echocardiography vs. SPECT imaging for the evaluation of stable chest pain

Aims Technological advances in cardiac imaging have led to dramatic increases in test utilization and consumption of a growing proportion of cardiovascular healthcare costs. The opportunity costs of strategies favouring exercise echocardiography or SPECT imaging have been incompletely evaluated. Methods and results We examined prognosis and cost-effectiveness of exercise echocardiography (n=4884) vs. SPECT (n=4637) imaging in stable, intermediate risk, chest pain patients. Ischaemia extent was defined as the number of vascular territories with echocardiographic wall motion or SPECT perfusion abnormalities. Cox proportional hazard models were employed to assess time to cardiac death or myocardial infarction (MI). Total cardiovascular costs were summed (discounted and inflation-corrected) throughout follow-up. A cost-effectiveness ratio = 2% annual event risk), SPECT ischaemia was associated with earlier and greater utilization of coronary revascularization (P < 0.0001) resulting in an incremental cost-effectiveness ratio of $32 381/LYS. Conclusion Health care policies aimed at allocating limited resources can be effectively guided by applying clinical and economic outcomes evidence. A strategy aimed at cost-effective testing would support using echocardiography in low-risk patients with suspected coronary disease, whereas those higher risk patients benefit from referral to SPECT imaging.

Incremental learning for interactive e-mail filtering

In this article, we propose a framework, namely, Prediction-Learning-Distillation (PLD) for interactive document classification and distilling misclassified documents. Whenever a user points out misclassified documents, the PLD learns from the mistakes and identifies the same mistakes from all other classified documents. The PLD then enforces this learning for future classifications. If the classifier fails to accept relevant documents or reject irrelevant documents on certain categories, then PLD will assign those documents as new positive/negative training instances. The classifier can then strengthen its weakness by learning from these new training instances. Our experiments’ results have demonstrated that the proposed algorithm can learn from user-identified misclassified documents, and then distil the rest successfully.

Can myocardial contrast echo provide incremental benefit to exercise echo? Implications of the intensity and duration of hyperaemia

Background. Stress myocardial contrast echo (MCE) is technically challenging with exercise (Ex) because of cardiacmovementandshort duration ofhyperemia.Vasodilators solve these limitations, but are less potent for inducing abnormal wall motion (WM). We sought whether a combined dipyridamole (DI; 0.56 mg/kg i.v. 4 min) and Ex stress protocol would enable MCE to provide incremental benefit toWManalysis for detection of CAD. Methods. Standard echo images were followed by real time MCE at rest and following stress in 85 pts, 70 undergoing quantitative coronary angiography and 15 low risk pts.WMAfrom standard and LVopacification images, and then myocardial perfusion were assessed sequentially in a blinded fashion. A subgroup of 13 pts also underwent Ex alone, to assess the contribution of DI to quantitative myocardial flow reserve (MFR). Results. Significant (>50%) stenoses were present in 43 pts, involving 69 territories. Addition of MCE improved SE sensitivity for detection of CAD (91% versus 74%, P = 0.02) and better appreciation of disease extent (87% versus 65%territories, P=0.003), with a non-significant reduction in specificity. In 55 territories subtended by a significant stenosis, but with no resting WM abnormality, ability to identify ischemia was also significantly increased by MCE (82% versus 60%, P = 0.002). MFR was less with Ex alone than with DIEx stress (2.4 ± 1.6 versus 4.0 ± 1.9, P = 0.05), suggesting prolongation of hyperaemia with DI may be essential to the results. Conclusions. Dipyridamole-exercise MCE adds significant incremental benefit to standard SE, with improved diagnostic sensitivity and more accurate estimation of extent of CAD.

Incremental model transformation for the evolution of model-driven systems

Model transformations are an integral part of model-driven development. Incremental updates are a key execution scenario for transformations in model-based systems, and are especially important for the evolution of such systems. This paper presents a strategy for the incremental maintenance of declarative, rule-based transformation executions. The strategy involves recording dependencies of the transformation execution on information from source models and from the transformation definition. Changes to the source models or the transformation itself can then be directly mapped to their effects on transformation execution, allowing changes to target models to be computed efficiently. This particular approach has many benefits. It supports changes to both source models and transformation definitions, it can be applied to incomplete transformation executions, and a priori knowledge of volatility can be used to further increase the efficiency of change propagation.