134 research outputs found
Neutron Moderation in the Oklo Natural Reactor and the Time Variation of alpha
In the analysis of the Oklo (gabon) natural reactor to test for a possible
time variation of the fine structure constant alpha, a Maxwell-Boltzmann low
energy neutron spectrum was assumed. We present here an analysis where a more
realistic spectrum is employed and show that the most recent isotopic analysis
of samples implies a non-zero change in alpha, over the last two billion years
since the reactor was operating, of \Delta\alpha/\alpha\geq 4.5\times 10^{-8}
(6\sigma confidence). Issues regarding the interpretation of the shifts of the
low energy neutron resonances are discussed.Comment: 7 pages, 4 figures; version 2 included reference to Flambaum/Shuryak
work and corrects error in abstract version three corrects a few points and
adds discussion on hydrogen and impurity concentration
Properties making a chaotic system a good Pseudo Random Number Generator
We discuss two properties making a deterministic algorithm suitable to
generate a pseudo random sequence of numbers: high value of Kolmogorov-Sinai
entropy and high-dimensionality. We propose the multi dimensional Anosov
symplectic (cat) map as a Pseudo Random Number Generator. We show what chaotic
features of this map are useful for generating Pseudo Random Numbers and
investigate numerically which of them survive in the discrete version of the
map. Testing and comparisons with other generators are performed.Comment: 10 pages, 3 figures, new version, title changed and minor correction
A Comparative Study of Some Pseudorandom Number Generators
We present results of an extensive test program of a group of pseudorandom
number generators which are commonly used in the applications of physics, in
particular in Monte Carlo simulations. The generators include public domain
programs, manufacturer installed routines and a random number sequence produced
from physical noise. We start by traditional statistical tests, followed by
detailed bit level and visual tests. The computational speed of various
algorithms is also scrutinized. Our results allow direct comparisons between
the properties of different generators, as well as an assessment of the
efficiency of the various test methods. This information provides the best
available criterion to choose the best possible generator for a given problem.
However, in light of recent problems reported with some of these generators, we
also discuss the importance of developing more refined physical tests to find
possible correlations not revealed by the present test methods.Comment: University of Helsinki preprint HU-TFT-93-22 (minor changes in Tables
2 and 7, and in the text, correspondingly
Analysis of Sample Correlations for Monte Carlo Rendering
Modern physically based rendering techniques critically depend on approximating integrals of high dimensional functions representing radiant light energy. Monte Carlo based integrators are the choice for complex scenes and effects. These integrators work by sampling the integrand at sample point locations. The distribution of these sample points determines convergence rates and noise in the final renderings. The characteristics of such distributions can be uniquely represented in terms of correlations of sampling point locations. Hence, it is essential to study these correlations to understand and adapt sample distributions for low error in integral approximation. In this work, we aim at providing a comprehensive and accessible overview of the techniques developed over the last decades to analyze such correlations, relate them to error in integrators, and understand when and how to use existing sampling algorithms for effective rendering workflows.publishe
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