Computer generated hologram from point cloud using graphics processor

Computer generated holography is an extremely demanding and complex task when it comes to providing realistic reconstructions with full parallax, occlusion, and shadowing. We present an algorithm designed for data-parallel computing on modern graphics processing units to alleviate the computational burden. We apply Gaussian interpolation to create a continuous surface representation from discrete input object points. The algorithm maintains a potential occluder list for each individual hologram plane sample to keep the number of visibility tests to a minimum.We experimented with two approximations that simplify and accelerate occlusion computation. It is observed that letting several neighboring hologramplane samples share visibility information on object points leads to significantly faster computation without causing noticeable artifacts in the reconstructed images. Computing a reduced sample set via nonuniform sampling is also found to be an effective acceleration technique. © 2009 Optical Society of America.

Uniform stability of a particle approximation of the optimal filter derivative

Sequential Monte Carlo methods, also known as particle methods, are a widely used set of computational tools for inference in non-linear non-Gaussian state-space models. In many applications it may be necessary to compute the sensitivity, or derivative, of the optimal filter with respect to the static parameters of the state-space model; for instance, in order to obtain maximum likelihood model parameters of interest, or to compute the optimal controller in an optimal control problem. In Poyiadjis et al. [2011] an original particle algorithm to compute the filter derivative was proposed and it was shown using numerical examples that the particle estimate was numerically stable in the sense that it did not deteriorate over time. In this paper we substantiate this claim with a detailed theoretical study. Lp bounds and a central limit theorem for this particle approximation of the filter derivative are presented. It is further shown that under mixing conditions these Lp bounds and the asymptotic variance characterized by the central limit theorem are uniformly bounded with respect to the time index. We demon- strate the performance predicted by theory with several numerical examples. We also use the particle approximation of the filter derivative to perform online maximum likelihood parameter estimation for a stochastic volatility model.

High-power laser beam shaping by inseparable two-dimensional binary-phase gratings for surface modification of stamping dies

For surface modification of stamping dies, an inseparable two-dimensional binary-phase gratings is introduced to implement the wavefront transformation of high-power laser beams. The design and fabrication of the gratings are described in detail. Two-dimensional even sampling encoding scheme is adopted to overcome the limitations of conventional Dammann grating in the design of two-dimensional output patterns. High diffractive efficiency (>70%) can be achieved through the transformation of the Gaussian laser beam into several kinds of two-dimensional arrays in focal plan. The application of the binary-phase gratings in the laser surface modification of ductile iron is investigated, and the results show that the hardness and the wear resistance of the sample surface were improved significantly by using the binary-phase gratings. (C) 2008 Elsevier Ltd. All rights reserved.

Forward Smoothing Using Sequential Monte Carlo

Sequential Monte Carlo (SMC) methods are a widely used set of computational tools for inference in non-linear non-Gaussian state-space models. We propose a new SMC algorithm to compute the expectation of additive functionals recursively. Essentially, it is an on-line or "forward only" implementation of a forward filtering backward smoothing SMC algorithm proposed by Doucet, Godsill and Andrieu (2000). Compared to the standard \emph{path space} SMC estimator whose asymptotic variance increases quadratically with time even under favorable mixing assumptions, the non asymptotic variance of the proposed SMC estimator only increases linearly with time. We show how this allows us to perform recursive parameter estimation using an SMC implementation of an on-line version of the Expectation-Maximization algorithm which does not suffer from the particle path degeneracy problem.

Thermal fatigue on pistons induced by shaped high power laser. Part I: Experimental study of transient temperature field and temperature oscillation

Thermal fatigue behavior is one of the foremost considerations in the design and operation of diesel engines. It is found that thermal fatigue is closely related to the temperature field and temperature fluctuation in the structure. In this paper, spatially shaped high power laser was introduced to simulate thermal loadings on the piston. The incident Gaussian beam was transformed into concentric multi-circular beam of specific intensity distribution with the help of diffractive optical element (DOE), and the transient temperature fields in the piston similar to those under working conditions could be achieved by setting up appropriate loading cycles. Simulation tests for typical thermal loading conditions, i.e., thermal high cycle fatigue (HCF) and thermal shock (or thermal low cycle fatigue, LCF) were carried out. Several important parameters that affect the transient temperature fields and/or temperature oscillations, including controlling mode, intensity distribution of shaped laser, laser power, temporal profile of laser pulse, heating time and cooling time in one thermal cycle, etc., were investigated and discussed. The results show that as a novel method, the shaped high power laser can simulate thermal loadings on pistons efficiently, and it is helpful in the study of thermal fatigue behavior in pistons. (C) 2007 Elsevier Ltd. All rights reserved.