Overview of plasma observations during the Halley flybys

In-situ observations made by the various plasma experiments onboard Giotto, Vega 1 and 2, Suisei, Sakigake, and ICE during the Halley flybys are summarized and discussed, starting with the phenomena furthest away (pick-up ions, plasma waves) and ending with the phenomena closest to the nucleus (magnetic cavity)

The ESA mission to Comet Halley

The Europeon Space Agency's approximately Giotto mission plans for a launch in July 1985 with a Halley encounter in mid-March 1986 4 weeks after the comet's perihelion passage. Giotto carries 10 scientific experiments, a camera, neutral, ion and dust mass spectrometers, a dust impact detector system, various plasma analyzers, a magnetometer and an optical probe. The instruments are described, the principles on which they are based are described, and the experiment key performance data are summarized. The launch constraints the helicentric transfer trajectory, and the encounter scenario are analyzed. The Giotto spacecraft major design criteria, spacecraft subsystem and the ground system are described. The problem of hypervelocity dust particle impacts in the innermost part of the coma, the problem of spacecraft survival, and the adverse effects of impact-generated plasma aroung the spacecraft are considered

Membrane adhesion and domain formation

We review theoretical results for the adhesion-induced phase behavior of biomembranes. The focus is on models in which the membranes are represented as discretized elastic sheets with embedded adhesion molecules. We present several mechanism that lead to the formation of domains during adhesion, and discuss the time-dependent evolution of domain patterns obtained in Monte-Carlo simulations. The simulated pattern dynamics has striking similarities to the pattern evolution observed during T cell adhesion.Comment: 68 pages, 29 figure

Diagonalization- and Numerical Renormalization-Group-Based Methods for Interacting Quantum Systems

In these lecture notes, we present a pedagogical review of a number of related {\it numerically exact} approaches to quantum many-body problems. In particular, we focus on methods based on the exact diagonalization of the Hamiltonian matrix and on methods extending exact diagonalization using renormalization group ideas, i.e., Wilson's Numerical Renormalization Group (NRG) and White's Density Matrix Renormalization Group (DMRG). These methods are standard tools for the investigation of a variety of interacting quantum systems, especially low-dimensional quantum lattice models. We also survey extensions to the methods to calculate properties such as dynamical quantities and behavior at finite temperature, and discuss generalizations of the DMRG method to a wider variety of systems, such as classical models and quantum chemical problems. Finally, we briefly review some recent developments for obtaining a more general formulation of the DMRG in the context of matrix product states as well as recent progress in calculating the time evolution of quantum systems using the DMRG and the relationship of the foundations of the method with quantum information theory.Comment: 51 pages; lecture notes on numerically exact methods. Pedagogical review appearing in the proceedings of the "IX. Training Course in the Physics of Correlated Electron Systems and High-Tc Superconductors", Vietri sul Mare (Salerno, Italy, October 2004

The Skyrme Interaction in finite nuclei and nuclear matter

Self-consistent mean-field models are a powerful tool in the investigation of nuclear structure and low-energy dynamics. They are based on effective energy-density functionals, often formulated in terms of effective density-dependent nucleon-nucleon interactions. The free parameters of the functional are adjusted to empirical data. A proper choice of these parameters requires a comprehensive set of constraints covering experimental data on finite nuclei, concerning static as well as dynamical properties, empirical characteristics of nuclear matter, and observational information on nucleosynthesis, neutron stars and supernovae. This work aims at a comprehensive survey of the performance of one of the most successful non-relativistic self-consistent method, the Skyrme-Hartree-Fock model (SHF), with respect to these constraints. A full description of the Skyrme functional is given and its relation to other effective interactions is discussed. The validity of the application of SHF far from stability and in dense environments beyond the nuclear saturation density is critically assessed. The use of SHF in models extended beyond the mean field approximation by including some correlations is discussed. Finally, future prospects for further development of SHF towards a more consistent application of the existing and promisingly newly developing constraints are outlined.Comment: 71 pages, 22 figures. Accepted for publication in Prog.Part.Nucl.Phy

spam: A Sparse Matrix R Package with Emphasis on MCMC Methods for Gaussian Markov Random Fields

spam is an R package for sparse matrix algebra with emphasis on a Cholesky factorization of sparse positive definite matrices. The implemantation of spam is based on the competing philosophical maxims to be competitively fast compared to existing tools and to be easy to use, modify and extend. The first is addressed by using fast Fortran routines and the second by assuring S3 and S4 compatibility. One of the features of spam is to exploit the algorithmic steps of the Cholesky factorization and hence to perform only a fraction of the workload when factorizing matrices with the same sparsity structure. Simulations show that exploiting this break-down of the factorization results in a speed-up of about a factor 5 and memory savings of about a factor 10 for large matrices and slightly smaller factors for huge matrices. The article is motivated with Markov chain Monte Carlo methods for Gaussian Markov random fields, but many other statistical applications are mentioned that profit from an efficient Cholesky factorization as well.

A spatial analysis of multivariate output from regional climate models

Climate models have become an important tool in the study of climate and climate change, and ensemble experiments consisting of multiple climate-model runs are used in studying and quantifying the uncertainty in climate-model output. However, there are often only a limited number of model runs available for a particular experiment, and one of the statistical challenges is to characterize the distribution of the model output. To that end, we have developed a multivariate hierarchical approach, at the heart of which is a new representation of a multivariate Markov random field. This approach allows for flexible modeling of the multivariate spatial dependencies, including the cross-dependencies between variables. We demonstrate this statistical model on an ensemble arising from a regional-climate-model experiment over the western United States, and we focus on the projected change in seasonal temperature and precipitation over the next 50 years.Comment: Published in at http://dx.doi.org/10.1214/10-AOAS369 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Cooperative wrapping of nanoparticles by membrane tubes

The bioactivity of nanoparticles crucially depends on their ability to cross biomembranes. Recent simulations indicate the cooperative wrapping and internalization of spherical nanoparticles in tubular membrane structures. In this article, we systematically investigate the energy gain of this cooperative wrapping by minimizing the energies of the rotationally symmetric shapes of the membrane tubes and of membrane segments wrapping single particles. We find that the energy gain for the cooperative wrapping of nanoparticles in membrane tubes relative to their individual wrapping as single particles strongly depends on the ratio of the particle radius and the range of the particle-membrane adhesion potential. For a potential range of the order of one nanometer, the cooperative wrapping in tubes is highly favorable for particles with a radius of tens of nanometers and intermediate adhesion energies, but not for particles that are significantly larger.Comment: 9 pages, 7 figures; to appear in Soft Matte