General Relativistic Radiative Transfer

We present a general method to calculate radiative transfer including scattering in the continuum as well as in lines in spherically symmetric systems that are influenced by the effects of general relativity (GR). We utilize a comoving wavelength ansatz that allows to resolve spectral lines throughout the atmosphere. The used numerical solution is an operator splitting (OS) technique that uses a characteristic formal solution. The bending of photon paths and the wavelength shifts due to the effects of GR are fully taken into account, as is the treatment of image generation in a curved spacetime. We describe the algorithm we use and demonstrate the effects of GR on the radiative transport of a two level atom line in a neutron star like atmosphere for various combinations of continuous and line scattering coefficients. In addition, we present grey continuum models and discuss the effects of different scattering albedos on the emergent spectra and the determination of effective temperatures and radii of neutron star atmospheres

Rigid open-cell polyurethane foam for cryogenic insulation

Lightweight polyurethane foam assembled in panels is effective spacer material for construction of self-evacuating multilayer insulation panels for cryogenic liquid tanks. Spacer material separates radiation shields with barrier that minimizes conductive and convective heat transfer between shields

Inference with interference between units in an fMRI experiment of motor inhibition

An experimental unit is an opportunity to randomly apply or withhold a treatment. There is interference between units if the application of the treatment to one unit may also affect other units. In cognitive neuroscience, a common form of experiment presents a sequence of stimuli or requests for cognitive activity at random to each experimental subject and measures biological aspects of brain activity that follow these requests. Each subject is then many experimental units, and interference between units within an experimental subject is likely, in part because the stimuli follow one another quickly and in part because human subjects learn or become experienced or primed or bored as the experiment proceeds. We use a recent fMRI experiment concerned with the inhibition of motor activity to illustrate and further develop recently proposed methodology for inference in the presence of interference. A simulation evaluates the power of competing procedures.Comment: Published by Journal of the American Statistical Association at http://www.tandfonline.com/doi/full/10.1080/01621459.2012.655954 . R package cin (Causal Inference for Neuroscience) implementing the proposed method is freely available on CRAN at https://CRAN.R-project.org/package=ci

Bulk gravitons from a cosmological brane

We investigate the emission of gravitons by a cosmological brane into an Anti de Sitter five-dimensional bulk spacetime. We focus on the distribution of gravitons in the bulk and the associated production of `dark radiation' in this process. In order to evaluate precisely the amount of dark radiation in the late low-energy regime, corresponding to standard cosmology, we study numerically the emission, propagation and bouncing off the brane of bulk gravitons.Comment: 27 pages, 5 figures, minor corrections. Final versio

Binary black holes in circular orbits. II. Numerical methods and first results

We present the first results from a new method for computing spacetimes representing corotating binary black holes in circular orbits. The method is based on the assumption of exact equilibrium. It uses the standard 3+1 decomposition of Einstein equations and conformal flatness approximation for the 3-metric. Contrary to previous numerical approaches to this problem, we do not solve only the constraint equations but rather a set of five equations for the lapse function, the conformal factor and the shift vector. The orbital velocity is unambiguously determined by imposing that, at infinity, the metric behaves like the Schwarzschild one, a requirement which is equivalent to the virial theorem. The numerical scheme has been implemented using multi-domain spectral methods and passed numerous tests. A sequence of corotating black holes of equal mass is calculated. Defining the sequence by requiring that the ADM mass decrease is equal to the angular momentum decrease multiplied by the orbital angular velocity, it is found that the area of the apparent horizons is constant along the sequence. We also find a turning point in the ADM mass and angular momentum curves, which may be interpreted as an innermost stable circular orbit (ISCO). The values of the global quantities at the ISCO, especially the orbital velocity, are in much better agreement with those from third post-Newtonian calculations than with those resulting from previous numerical approaches.Comment: 27 pages, 20 PostScript figures, improved presentation of the regularization procedure for the shift vector, new section devoted to the check of the momentum constraint, references added + minor corrections, accepted for publication in Phys. Rev.

Evolution of Protoneutron Stars

We study the thermal and chemical evolution during the Kelvin-Helmholtz phase of the birth of a neutron star, employing neutrino opacities that are consistently calculated with the underlying equation of state (EOS). Expressions for the diffusion coefficients appropriate for general relativistic neutrino transport in the equilibrium diffusion approximation are derived. The diffusion coefficients are evaluated using a field-theoretical finite temperature EOS that includes the possible presence of hyperons. The variation of the diffusion coefficients is studied as a function of EOS and compositional parameters. We present results from numerical simulations of protoneutron star cooling for internal stellar properties as well as emitted neutrino energies and luminosities. We discuss the influence of the initial stellar model, the total mass, the underlying EOS, and the addition of hyperons on the evolution of the protoneutron star and upon the expected signal in terrestrial detectors.Comment: 67 pages, 25 figure

Traversable Wormholes in Geometries of Charged Shells

We construct a static axisymmetric wormhole from the gravitational field of two charged shells which are kept in equilibrium by their electromagnetic repulsion. For large separations the exterior tends to the Majumdar-Papapetrou spacetime of two charged particles. The interior of the wormhole is a Reissner-Nordstr\"om black hole matching to the two shells. The wormhole is traversable and connects to the same asymptotics without violation of energy conditions. However, every point in the Majumdar-Papapetrou region lies on a closed timelike curve.Comment: 9 pages, LaTeX, 1 figur

Laue diffraction lenses for astrophysics: From theory to experiments

Based on the laws of X-ray diffraction in crystals, Laue lenses offer a promising way to achieve the sensitivity and angular resolution leap required for the next generation of hard X-ray and gamma-ray telescopes. The present paper describes the instrumental responses of Laue diffraction lenses designed for nuclear astrophysics. Different possible geometries are discussed, as well as the corresponding spectral and imaging capabilities. These theoretical predictions are then compared with Monte-Carlo simulations and experimental results (ground and stratospheric observations from the CLAIRE project)

Generalized Vaidya Solutions

A large family of solutions, representing, in general, spherically symmetric Type II fluid, is presented, which includes most of the known solutions to the Einstein field equations, such as, the monopole-de Sitter-charged Vaidya ones.Comment: Gen. Relativ. Grav. 31 (1), 107-114 (1999

Tensor Regression with Applications in Neuroimaging Data Analysis

Classical regression methods treat covariates as a vector and estimate a corresponding vector of regression coefficients. Modern applications in medical imaging generate covariates of more complex form such as multidimensional arrays (tensors). Traditional statistical and computational methods are proving insufficient for analysis of these high-throughput data due to their ultrahigh dimensionality as well as complex structure. In this article, we propose a new family of tensor regression models that efficiently exploit the special structure of tensor covariates. Under this framework, ultrahigh dimensionality is reduced to a manageable level, resulting in efficient estimation and prediction. A fast and highly scalable estimation algorithm is proposed for maximum likelihood estimation and its associated asymptotic properties are studied. Effectiveness of the new methods is demonstrated on both synthetic and real MRI imaging data.Comment: 27 pages, 4 figure