Foreground removal from WMAP 5yr temperature maps using an MLP neural network

One of the main obstacles for extracting the cosmic microwave background (CMB) signal from observations in the mm/sub-mm range is the foreground contamination by emission from Galactic component: mainly synchrotron, free-free, and thermal dust emission. The statistical nature of the intrinsic CMB signal makes it essential to minimize the systematic errors in the CMB temperature determinations. The feasibility of using simple neural networks to extract the CMB signal from detailed simulated data has already been demonstrated. Here, simple neural networks are applied to the WMAP 5yr temperature data without using any auxiliary data. A simple \emph{multilayer perceptron} neural network with two hidden layers provides temperature estimates over more than 75 per cent of the sky with random errors significantly below those previously extracted from these data. Also, the systematic errors, i.e.\ errors correlated with the Galactic foregrounds, are very small. With these results the neural network method is well prepared for dealing with the high - quality CMB data from the ESA Planck Surveyor satellite.Comment: 6 pages, 13 figure

On the Key-Uncertainty of Quantum Ciphers and the Computational Security of One-way Quantum Transmission

We consider the scenario where Alice wants to send a secret (classical) $n$-bit message to Bob using a classical key, and where only one-way transmission from Alice to Bob is possible. In this case, quantum communication cannot help to obtain perfect secrecy with key length smaller then $n$. We study the question of whether there might still be fundamental differences between the case where quantum as opposed to classical communication is used. In this direction, we show that there exist ciphers with perfect security producing quantum ciphertext where, even if an adversary knows the plaintext and applies an optimal measurement on the ciphertext, his Shannon uncertainty about the key used is almost maximal. This is in contrast to the classical case where the adversary always learns $n$ bits of information on the key in a known plaintext attack. We also show that there is a limit to how different the classical and quantum cases can be: the most probable key, given matching plain- and ciphertexts, has the same probability in both the quantum and the classical cases. We suggest an application of our results in the case where only a short secret key is available and the message is much longer.Comment: 19 pages, 2 figures. This is a revised version of an earlier version that appeared in the proc. of Eucrocrypt'04:LNCS3027, 200

Deep rest-frame far-UV spectroscopy of the giant Lyman-alpha emitter 'Himiko'

We present deep 10h VLT/XSHOOTER spectroscopy for an extraordinarily luminous and extended Lya emitter at z=6.595 referred to as Himiko and first discussed by Ouchi et al. (2009), with the purpose of constraining the mechanisms powering its strong emission. Complementary to the spectrum, we discuss NIR imaging data from the CANDELS survey. We find neither for HeII nor any metal line a significant excess, with 3 sigma upper limits of 6.8, 3.1, and 5.8x10^{-18} erg/s/cm^2 for CIV $\lambda$1549, HeII $\lambda$1640, CIII] $\lambda$1909, respectively, assuming apertures with 200 km/s widths and offset by -250 km/s w.r.t to the peak Lya redshift. These limits provide strong evidence that an AGN is not a major contribution to Himiko's Lya flux. Strong conclusions about the presence of PopIII star-formation or gravitational cooling radiation are not possible based on the obtained HeII upper limit. Our Lya spectrum confirms both spatial extent and flux (8.8+/-0.5x10^{-17} erg/s/cm^2) of previous measurements. In addition, we can unambiguously exclude any remaining chance of it being a lower redshift interloper by significantly detecting a continuum redwards of Lya, while being undetected bluewards

Generalised additive dependency inflated models including aggregated covariates

Let us assume that X, Y and U are observed and that the conditional mean of U given X and Y can be expressed via an additive dependency of X, λ(X)Y and X + Y for some unspecified function . This structured regression model can be transferred to a hazard model or a density model when applied on some appropriate grid, and has important forecasting applications via structured marker dependent hazards models or structured density models including age-period-cohort relationships. The structured regression model is also important when the severity of the dependent variable has a complicated dependency on waiting times X, Y and the total waiting time X+Y . In case the conditional mean of U approximates a density, the regression model can be used to analyse the age-period-cohort model, also when exposure data are not available. In case the conditional mean of U approximates a marker dependent hazard, the regression model introduces new relevant age-period-cohort time scale interdependencies in understanding longevity. A direct use of the regression relationship introduced in this paper is the estimation of the severity of outstanding liabilities in non-life insurance companies. The technical approach taken is to use B-splines to capture the underlying one-dimensional unspecified functions. It is shown via finite sample simulation studies and an application for forecasting future asbestos related deaths in the UK that the B-spline approach works well in practice. Special consideration has been given to ensure identifiability of all models considered

Non-markovian dynamics of double quantum dot charge qubit with static bias

The dynamics of charge qubit in double quantum dot coupled to phonons is investigated theoretically. The static bias is considered. By means of the perturbation approach based on unitary transformations, the dynamical tunneling current is obtained explicitly. The biased system displays broken symmetry and a significantly larger coherence-incoherence transition critical point $\alpha _{c}$. We also analyzed the decoherence induced by piezoelectric coupling phonons in detail. The results show that reducing the coupling between system and bath make coherence frequency increase and coherence time prolong. To maintain quantum coherence, applying static bias also is a good means.Comment: 13 pages, 5 figure

Fighting Decoherence by Feedback-controlled Dissipation

Repeated closed-loop control operations acting as piecewise-constant Liouville superoperators conditioned on the outcomes of regularly performed measurements may effectively be described by a fixed-point iteration for the density matrix. Even when all Liouville superoperators point to the completely mixed state, feedback of the measurement result may lead to a pure state, which can be interpreted as selective dampening of undesired states. Using a microscopic model, we exemplify this for a single qubit, which can be purified in an arbitrary single-qubit state by tuning the measurement direction and two qubits that may be purified towards a Bell state by applying a special continuous two-local measurement. The method does not require precise knowledge of decoherence channels and works for large reservoir temperatures provided measurement, processing, and control can be implemented in a continuous fashion.Comment: to appear in PR