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

Near-infrared photoabsorption by C(60) dianions in a storage ring

We present a detailed study of the electronic structure and the stability of C(60) dianions in the gas phase. Monoanions were extracted from a plasma source and converted to dianions by electron transfer in a Na vapor cell. The dianions were then stored in an electrostatic ring, and their near-infrared absorption spectrum was measured by observation of laser induced electron detachment. From the time dependence of the detachment after photon absorption, we conclude that the reaction has contributions from both direct electron tunneling to the continuum and vibrationally assisted tunneling after internal conversion. This implies that the height of the Coulomb barrier confining the attached electrons is at least similar to 1.5 eV. For C(60)(2-) ions in solution electron spin resonance measurements have indicated a singlet ground state, and from the similarity of the absorption spectra we conclude that also the ground state of isolated C(60)(2-) ions is singlet. The observed spectrum corresponds to an electronic transition from a t(1u) lowest unoccupied molecular orbital (LUMO) of C(60) to the t(1g) LUMO+1 level. The electronic levels of the dianion are split due to Jahn-Teller coupling to quadrupole deformations of the molecule, and a main absorption band at 10723 cm(-1) corresponds to a transition between the Jahn-Teller ground states. Also transitions from pseudorotational states with 200 cm(-1) and (probably) 420 cm(-1) excitation are observed. We argue that a very broad absorption band from about 11 500 cm(-1) to 13 500 cm(-1) consists of transitions to so-called cone states, which are Jahn-Teller states on a higher potential-energy surface, stabilized by a pseudorotational angular momentum barrier. A previously observed, high-lying absorption band for C(60)(-) may also be a transition to a cone state

A variational description of the quantum phase transition in the sub-Ohmic spin-boson model

The sub-ohmic spin-boson model is known to possess a novel quantum phase transition at zero temperature between a localised and delocalised phase. We present here an analytical theory based on a variational ansatz for the ground state, which describes a continuous localization transition with mean-field exponents for $0<s<0.5$. Our results for the critical properties show good quantitiative agreement with previous numerical results, and we present a detailed description of all the spin observables as the system passes through the transition. Analysing the ansatz itself, we give an intuitive microscopic description of the transition in terms of the changing correlations between the system and bath, and show that it is always accompanied by a divergence of the low-frequency boson occupations. The possible relevance of this divergence for some numerical approaches to this problem is discussed and illustrated by looking at the ground state obtained using density matrix renormalisation group methods

Resilient Quantum Computation in Correlated Environments: A Quantum Phase Transition Perspective

We analyze the problem of a quantum computer in a correlated environment protected from decoherence by QEC using a perturbative renormalization group approach. The scaling equation obtained reflects the competition between the dimension of the computer and the scaling dimension of the correlations. For an irrelevant flow, the error probability is reduced to a stochastic form for long time and/or large number of qubits; thus, the traditional derivation of the threshold theorem holds for these error models. In this way, the ``threshold theorem'' of quantum computing is rephrased as a dimensional criterion.Comment: 4.1 pages, minor correction and an improved discussion of Eqs. (4) and (14

Foreground removal from WMAP 7yr polarization maps using an MLP neural network

One of the fundamental problems in extracting the cosmic microwave background signal (CMB) from millimeter/submillimeter observations is the pollution by emission from the Milky Way: synchrotron, free-free, and thermal dust emission. To extract the fundamental cosmological parameters from CMB signal, it is mandatory to minimize this pollution since it will create systematic errors in the CMB power spectra. In previous investigations, it has been demonstrated that the neural network method provide high quality CMB maps from temperature data. Here the analysis is extended to polarization maps. As a concrete example, the WMAP 7-year polarization data, the most reliable determination of the polarization properties of the CMB, has been analysed. The analysis has adopted the frequency maps, noise models, window functions and the foreground models as provided by the WMAP Team, and no auxiliary data is included. Within this framework it is demonstrated that the network can extract the CMB polarization signal with no sign of pollution by the polarized foregrounds. The errors in the derived polarization power spectra are improved compared to the errors derived by the WMAP Team.Comment: Accepted for publication in Astrophysics & Space Scienc

Generalised 11-dimensional supergravity

The low-energy effective dynamics of M-theory, eleven-dimensional supergravity, is taken off-shell in a manifestly supersymmetric superspace formulation. We show that a previously proposed relaxation of the torsion constraints can indeed accomodate a current supermultiplet. We comment on the relation and application of this completely general formalism to higher-derivative (R^4) corrections. This talk was presented by Bengt EW Nilsson at the Triangle Meeting 2000 ``Non-perturbative Methods in Field and String Theory'', NORDITA, Copenhagen, June 19-22, 2000, and by Martin Cederwall at the International Conference ``Quantization, Gauge Theory and Strings'' in memory of Efim Fradkin, Moscow, June 5-10, 2000

Nonparametric regression with parametric help

In this paper we propose a new nonparametric regression technique. Our proposal has common ground with existing two-step procedures in that it starts with a parametric model. However, our approach di↵ers from others in the choice of parametric start within the parametric family. Our proposal chooses a function that is the projection of the unknown regression function onto the parametric family in a certain metric, while the existing methods select the best approximation in the usual L2 metric. We find that the di↵erence leads to substantial improvement in the performance of regression estimators in comparison with direct one-step estimation, irrespective of the choice of a parametric model. This is in contrast with the existing two-step methods, which fail if the chosen parametric model is largely misspecified. We demonstrate this with sound theory and numerical experiment

Operational time and in-sample density forecasting

In this paper we consider a new structural model for in-sample density forecasting. In-sample density forecasting is to estimate a structured density on a region where data are observed and then re-use the estimated structured density on some region where data are not observed. Our structural assumption is that the density is a product of one-dimensional functions with one function sitting on the scale of a transformed space of observations. The transformation involves another unknown one-dimensional function, so that our model is formulated via a known smooth function of three underlying unknown one-dimensional functions. We present an innovative way of estimating the one-dimensional functions and show that all the estimators of the three components achieve the optimal one-dimensional rate of convergence. We illustrate how one can use our approach by analyzing a real dataset, and also verify the tractable finite sample performance of the method via a simulation study

Low computational complexity mode division multiplexed OFDM transmission over 130 km of few mode fiber

We demonstrate 337.5-Gb/s MDM-8QAM-OFDM transmission over 130 km of FMF. This confirms that OFDM can significantly reduce the required DSP complexity to compensate for differential mode delay, a key step towards real-time MDM transmission

The Ecology of Pulse Events: Insights From an Extreme Climatic Event in a Polar Desert Ecosystem

Climate change is occurring globally, with wide ranging impacts on organisms and ecosystems alike. While most studies focus on increases in mean temperatures and changes in precipitation, there is growing evidence that an increase in extreme events may be particularly important to altering ecosystem structure and function. During extreme events organisms encounter environmental conditions well beyond the range normally experienced. Such conditions may cause rapid changes in community composition and ecosystem states. We present the impact of an extreme pulse event (a flood) on soil communities in an Antarctic polar desert. Taylor Valley, McMurdo Dry Valleys, is dominated by large expanses of dry, saline soils. During the austral summer, melting of glaciers, snow patches and subsurface ice supplies water to ephemeral streams and wetlands. We show how the activation of a non‐annual ephemeral stream, Wormherder Creek, and the associated wetland during an exceptional high‐flow event alters soil properties and communities. The flow of water increased soil water availability and decreased salinity within the wetted zone compared with the surrounding dry soils. We propose that periodic leaching of salts from flooding reduces soil osmotic stress to levels that are more favorable for soil organisms, improving the habitat suitability, which has a strong positive effect on soil animal abundance and diversity. Moreover, we found that communities differentiated along a soil moisture gradient and that overland water flow created greater connectivity within the landscape, and is expected to promote soil faunal dispersal. Thus, floods can ‘precondition\u27 soils to support belowground communities by creating conditions below or above key environmental thresholds. We conclude that pulse events can have significant long‐term impacts on soil habitat suitability, and knowledge of pulse events is essential for understanding the present distribution and functioning of communities in soil ecosystems