Search results for "probability density function"
showing 10 items of 183 documents
Searches for B0 decays to combinations of charmless isoscalar mesons
2004
We search for B meson decays into two-body combinations of eta, eta', omega, and phi mesons from 89 million B B-bar pairs collected with the BaBar detector at the PEP-II asymmetric-energy e+e- collider at SLAC. We find the branching fraction BF(B0 -> eta omega) = (4.0^{+1.3}_{-1.2} +- 0.4) x 10^-6 with a significance of 4.3 sigma. For all the other decay modes we set the following 90% confidence level upper limits on the branching fractions, in units of 10^-6 : BF(B0 -> eta eta)<2.8, BF(B0 -> eta eta')<4.6, BF(B0 -> eta' eta')<10, BF(B0 -> eta'omega)<2.8, BF(B0 -> eta phi)<1.0, BF(B0 -> eta' phi)<4.5, BF(B0 -> phi phi)<1.5.
Breakdown of separability due to confinement
2017
A simple system of two particles in a bidimensional configurational space S is studied. The possibility of breaking in S the time-independent Schrodinger equation of the system into two separated one-dimensional one-body Schrodinger equations is assumed. In this paper, we focus on how the latter property is countered by imposing such boundary conditions as confinement to a limited region of S and/or restrictions on the joint coordinate probability density stemming from the sign-invariance condition of the relative coordinate (an impenetrability condition). Our investigation demonstrates the reducibility of the problem under scrutiny into that of a single particle living in a limited domain …
Quantitative analysis of crystal/grain sizes and their distributions in 2D and 3D
2011
Abstract We review methods to estimate the average crystal (grain) size and the crystal (grain) size distribution in solid rocks. Average grain sizes often provide the base for stress estimates or rheological calculations requiring the quantification of grain sizes in a rock’s microstructure. The primary data for grain size data are either 1D (i.e. line intercept methods), 2D (area analysis) or 3D (e.g., computed tomography, serial sectioning). These data have been used for different data treatments over the years, whereas several studies assume a certain probability function (e.g., logarithm, square root) to calculate statistical parameters as the mean, median, mode or the skewness of a cr…
Relevance of Tool Life Testing for Tool Replacement Strategies
1986
Several analytical and simulation models have been proposed in order to select the optimal tool replacement strategies both in single and multi-tool machining operations. All of these models, however, assume as known the probability density function that describes the stochastic behaviour of tool life. The costly efforts required in order to achieve an accurate estimate of the p.d.f. limits the use in the shop practice of the above models.
Determination of highly porous plastic foam structural characteristics by processing light microscopy images data
2013
Mathematical modelling of physical and mechanical properties of plastic foam as well as numerous practical applications requires knowledge of foam structural characteristics. A necessity exists to determine the characteristics of the spatial structure of inhomogeneous materials comprising inclusions of other material, e.g., polyurethane foam without destructing the material and analysis of each element. A methodology is elaborated for preparing highly porous plastic foam specimens and investigation of foam strut-like structure with light microscopy (LM) by taking images in three mutually perpendicular planes. A mathematical model is developed for highly porous plastic foam for the determina…
Stochastic reconstruction of sandstones
2000
A simulated annealing algorithm is employed to generate a stochastic model for a Berea and a Fontainebleau sandstone with prescribed two-point probability function, lineal path function, and ``pore size'' distribution function, respectively. We find that the temperature decrease of the annealing has to be rather quick to yield isotropic and percolating configurations. A comparison of simple morphological quantities indicates good agreement between the reconstructions and the original sandstones. Also, the mean survival time of a random walker in the pore space is reproduced with good accuracy. However, a more detailed investigation by means of local porosity theory shows that there may be s…
Stochastic analysis of external and parametric dynamical systems under sub-Gaussian Levy white-noise
2008
In this study stochastic analysis of non-linear dynamical systems under α-stable, multiplicative white noise has been conducted. The analysis has dealt with a special class of α-stable stochastic processes namely sub-Gaussian white noises. In this setting the governing equation either of the probability density function or of the characteristic function of the dynamical response may be obtained considering the dynamical system forced by a Gaussian white noise with an uncertain factor with α/2- stable distribution. This consideration yields the probability density function or the characteristic function of the response by means of a simple integral involving the probability density function …
Non Gaussian closure techniques for the analysis of R-FBI isolation system
1997
The Resilient-Friction Base Isolator (R-FBI) stochastic response under severe ground motion modelled as a stationary and non-stationary zero mean stochastic white noise processes is performed. The moment equation approach is applied and the non-normal response is obtained by means of a non-Gaussian closure technique, based on the Gram-Charlier asymptotic expansion of the response probability density function. Results are compared with the equivalent non linearization technique and with results obtained by means of Monte Carlo simulation.
A Local Selection Algorithm for Switching Function Minimization
1984
The minimization algorithms which do not require any preliminary generation of all the prime implicants (PI's) of a function are the most efficient. In this work a new algorithm is described which follows such an approach. It is based on a local selection of PI's carried out by examining a set of vertices whose number is never greater than the number of PI's of a minimum cost cover. This algorithm takes advantage of a technique which uses numerical equivalents of the function vertices as pointers. For this reason it is well suited for implementation by computer. To illustrate the features of this algorithm a few examples are reported.
Adaptive Gaussian particle method for the solution of the Fokker-Planck equation
2012
The Fokker-Planck equation describes the evolution of the probability density for a stochastic ordinary differential equation (SODE). A solution strategy for this partial differential equation (PDE) up to a relatively large number of dimensions is based on particle methods using Gaussians as basis functions. An initial probability density is decomposed into a sum of multivariate normal distributions and these are propagated according to the SODE. The decomposition as well as the propagation is subject to possibly large numeric errors due to the difficulty to control the spatial residual over the whole domain. In this paper a new particle method is derived, which allows a deterministic error…