7,385 research outputs found
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.
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
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
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