42,574 research outputs found
Fusion process of Lennard-Jones clusters: global minima and magic numbers formation
We present a new theoretical framework for modelling the fusion process of
Lennard-Jones (LJ) clusters. Starting from the initial tetrahedral cluster
configuration, adding new atoms to the system and absorbing its energy at each
step, we find cluster growing paths up to the cluster sizes of up to 150 atoms.
We demonstrate that in this way all known global minima structures of the
LJ-clusters can be found. Our method provides an efficient tool for the
calculation and analysis of atomic cluster structure. With its use we justify
the magic number sequence for the clusters of noble gas atoms and compare it
with experimental observations. We report the striking correspondence of the
peaks in the dependence on cluster size of the second derivative of the binding
energy per atom calculated for the chain of LJ-clusters based on the
icosahedral symmetry with the peaks in the abundance mass spectra
experimentally measured for the clusters of noble gas atoms. Our method serves
an efficient alternative to the global optimization techniques based on the
Monte-Carlo simulations and it can be applied for the solution of a broad
variety of problems in which atomic cluster structure is important.Comment: 47 pages, MikTeX, 17 figure
Solving Shift Register Problems over Skew Polynomial Rings using Module Minimisation
For many algebraic codes the main part of decoding can be reduced to a shift
register synthesis problem. In this paper we present an approach for solving
generalised shift register problems over skew polynomial rings which occur in
error and erasure decoding of -Interleaved Gabidulin codes. The algorithm
is based on module minimisation and has time complexity where
measures the size of the input problem.Comment: 10 pages, submitted to WCC 201
A PCA-based automated finder for galaxy-scale strong lenses
We present an algorithm using Principal Component Analysis (PCA) to subtract
galaxies from imaging data, and also two algorithms to find strong,
galaxy-scale gravitational lenses in the resulting residual image. The combined
method is optimized to find full or partial Einstein rings. Starting from a
pre-selection of potential massive galaxies, we first perform a PCA to build a
set of basis vectors. The galaxy images are reconstructed using the PCA basis
and subtracted from the data. We then filter the residual image with two
different methods. The first uses a curvelet (curved wavelets) filter of the
residual images to enhance any curved/ring feature. The resulting image is
transformed in polar coordinates, centered on the lens galaxy center. In these
coordinates, a ring is turned into a line, allowing us to detect very faint
rings by taking advantage of the integrated signal-to-noise in the ring (a line
in polar coordinates). The second way of analysing the PCA-subtracted images
identifies structures in the residual images and assesses whether they are
lensed images according to their orientation, multiplicity and elongation. We
apply the two methods to a sample of simulated Einstein rings, as they would be
observed with the ESA Euclid satellite in the VIS band. The polar coordinates
transform allows us to reach a completeness of 90% and a purity of 86%, as soon
as the signal-to-noise integrated in the ring is higher than 30, and almost
independent of the size of the Einstein ring. Finally, we show with real data
that our PCA-based galaxy subtraction scheme performs better than traditional
subtraction based on model fitting to the data. Our algorithm can be developed
and improved further using machine learning and dictionary learning methods,
which would extend the capabilities of the method to more complex and diverse
galaxy shapes
Graph colouring for office blocks
The increasing prevalence of WLAN (wireless networks) introduces the potential of electronic information leakage from one company's territory in an office block, to others due to the long-ranged nature of such communications. BAE Systems have developed a system ('stealthy wallpaper') which can block a single frequency range from being transmitted through a treated wall or ceiling to the neighbour. The problem posed to the Study Group was to investigate the maximum number of frequencies ensure the building is secure. The Study group found that this upper bound does not exist, so they were asked to find what are "good design-rules" so that an upper limit exists
Multiobjective genetic algorithm strategies for electricity production from generation IV nuclear technology
Development of a technico-economic optimization strategy of cogeneration systems of electricity/hydrogen, consists in finding an optimal efficiency of the generating cycle and heat delivery system, maximizing the energy production and minimizing the production costs. The first part of the paper is related to the development of a multiobjective optimization library (MULTIGEN) to tackle all types of problems arising from cogeneration. After a literature review for identifying the most efficient methods, the MULTIGEN library is described, and the innovative points are listed. A new stopping criterion, based on the stagnation of the Pareto front, may lead to significant decrease of computational times, particularly in the case of problems involving only integer variables. Two practical examples are presented in the last section. The former is devoted to a bicriteria optimization of both exergy destruction and total cost of the plant, for a generating cycle coupled with a Very High Temperature Reactor (VHTR). The second example consists in designing the heat exchanger of the generating turbomachine. Three criteria are optimized: the exchange surface, the exergy destruction and the number of exchange modules
Equi-energy sampler with applications in statistical inference and statistical mechanics
We introduce a new sampling algorithm, the equi-energy sampler, for efficient
statistical sampling and estimation. Complementary to the widely used
temperature-domain methods, the equi-energy sampler, utilizing the
temperature--energy duality, targets the energy directly. The focus on the
energy function not only facilitates efficient sampling, but also provides a
powerful means for statistical estimation, for example, the calculation of the
density of states and microcanonical averages in statistical mechanics. The
equi-energy sampler is applied to a variety of problems, including exponential
regression in statistics, motif sampling in computational biology and protein
folding in biophysics.Comment: This paper discussed in: [math.ST/0611217], [math.ST/0611219],
[math.ST/0611221], [math.ST/0611222]. Rejoinder in [math.ST/0611224].
Published at http://dx.doi.org/10.1214/009053606000000515 in the Annals of
Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical
Statistics (http://www.imstat.org
A simple algorithm for optimization and model fitting: AGA (asexual genetic algorithm)
Context. Mathematical optimization can be used as a computational tool to
obtain the optimal solution to a given problem in a systematic and efficient
way. For example, in twice-differentiable functions and problems with no
constraints, the optimization consists of finding the points where the gradient
of the objective function is zero and using the Hessian matrix to classify the
type of each point. Sometimes, however it is impossible to compute these
derivatives and other type of techniques must be employed such as the steepest
descent/ascent method and more sophisticated methods such as those based on the
evolutionary algorithms. Aims. We present a simple algorithm based on the idea
of genetic algorithms (GA) for optimization. We refer to this algorithm as AGA
(Asexual Genetic Algorithm) and apply it to two kinds of problems: the
maximization of a function where classical methods fail and model fitting in
astronomy. For the latter case, we minimize the chi-square function to estimate
the parameters in two examples: the orbits of exoplanets by taking a set of
radial velocity data, and the spectral energy distribution (SED) observed
towards a YSO (Young Stellar Object). Methods. The algorithm AGA may also be
called genetic, although it differs from standard genetic algorithms in two
main aspects: a) the initial population is not encoded, and b) the new
generations are constructed by asexual reproduction. Results. Applying our
algorithm in optimizing some complicated functions, we find the global maxima
within a few iterations. For model fitting to the orbits of exoplanets and the
SED of a YSO, we estimate the parameters and their associated errors.Comment: 10 pages, 8 figures, Astronomy and Astrophysics (in press
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