Our research began by studying the Perfect Simulation idea developed by Propp and Wilson. In Article 1 we present the “One-Shot CFTP” framework, a general Perfect Simulation algorithm that constructs a Markov chain with a given target density as its equilibrium density and then carries out Perfect Simulation on this chain. The method is based on the Read-Once CFTP idea of Wilson and the Gibbs s...

A mathematical system for modeling the effects of symmetrized instrumental aberrations has been developed. The is composed truncated Gaussian, sheared and Rosin-Rammler-type functions. shape function can uniquely be determined by standard deviation kurtosis. practical method to evaluate convolution with Lorentzian results application analysis experimental powder diffraction data are briefly des...

Sparsity is a fundamental topic in highdimensional data analysis. Perhaps the most common measures of sparsity are the `norms, for 0 ≤ p < 2. In this paper, we study an alternative measure of sparsity, the truncated `-norm, which is related to other `-norms, but appears to have some unique and useful properties. Focusing on the ndimensional Gaussian location model, we derive exact asymptotic mi...

We consider the problem of reasoning with linear temporal logic on truncated paths. A truncated path is a path which is finite, but not necessarily maximal. Truncated paths arise naturally in several areas, among which are incomplete verification methods (such as simulation or bounded model checking) and hardware resets. We present a formalism for reasoning about truncated paths, and analyze it...

We demonstrate a production of large-area $^{87}$Rb Bose-Einstein condensates (BECs) using non-Gaussian optical dipole trap (ODT). The ODT is formed by focusing symmetrically truncated Gaussian laser beam and it shown that the clipping causes geometry elongated flattened along axis direction. In clipped-Gaussian ODT, an elongated, highly oblate BEC generated with length width approximately $470...

Summary The covariance structure of multivariate functional data can be highly complex, especially if the dimension is large, making extensions statistical methods for standard to setting challenging. For example, Gaussian graphical models have recently been extended by applying coefficients truncated basis expansions. However, compared with data, a key difficulty that operator compact and thus...