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This study deals with a narrow escape problem, a well-know difficult problem of evaluating the probability for a diffusing particle to reach a small part of a boundary far away from the starting position of the particle. A direct simulation of the diffusion trajectories would take an enormous computer simulation time. Instead, we use a different approach which drastically improves the efficiency of the diffusion trajectory tracking algorithm by introducing an artificial drift velocity directed to the target position. The method can be efficiently applied to solve narrow escape problems for domains of long extension in one direction which is the case in many practical problems in biology and chemistry. The algorithm is meshless both in space and time, and is well applied to solve high-dimensional problems in complicated domains. We present in this paper a detailed numerical analysis of the method for the case of a rectangular parallelepiped. Both stationary and transient diffusion problems are handled. [ABSTRACT FROM AUTHOR]

Density functional theory as proposed by Rosenfeld [Phys. Rev. Lett. 63, 980 (1989)] is used to study hard sphere mixture exposed by cylindrically symmetric external field. Exploiting the symmetry of the system, explicit formulas for the weighted densities are derived. The resulting density profiles are compared with new grand canonical Monte Carlo simulations. The comparison reveals very good agreement between the predicted and simulated results even at high densities and very narrow pores. Finally, simple algorithms for computing complete elliptic functions of the first and second kinds that occur in the derived formulae are presented to make the paper self-contained. [ABSTRACT FROM AUTHOR]

Population Monte Carlo (PMC) sampling methods are powerful tools for approximating distributions of static unknowns given a set of observations. These methods are iterative in nature: at each step they generate samples from a proposal distribution and assign them weights according to the importance sampling principle. Critical issues in applying PMC methods are the choice of the generating functions for the samples and the avoidance of the sample degeneracy. In this paper, we propose three new schemes that considerably improve the performance of the original PMC formulation by allowing for better exploration of the space of unknowns and by selecting more adequately the surviving samples. A theoretical analysis is performed, proving the superiority of the novel schemes in terms of variance of the associated estimators and preservation of the sample diversity. Furthermore, we show that they outperform other state of the art algorithms (both in terms of mean square error and robustness w.r.t. initialization) through extensive numerical simulations. [ABSTRACT FROM AUTHOR]

This paper compares the performance of source-tuner noise-parameter extraction methods used to measure noise parameters of low-noise amplifiers that have very low (<1 dB) noise figures. The methods discussed are known as the Cold method and the modified Y-factor method (or Hot-Cold method). The paper describes equations used in the extraction algorithms. In a Monte Carlo analysis by randomly adding various sources of uncertainties to "measurements," created with a computer simulation, performances of the noise parameter extraction methods are compared. It is shown that the iterative Cold method and the direct Cold method are the best at extracting Rn and Γopt noise parameters in terms of lowest standard deviation and close proximity of the extracted mean values to the true values. The simplified Cold method, used in a number of commercial systems, has largest systematic offsets in extracted noise parameters while being the quickest to perform. The modified Y-factor method is the slowest to perform due to additional time required for hot measurements. This method is marginally the most accurate to extract Fmin. These conclusions are also supported with measurement results. This study assembles in one place necessary theoretical background information to serve as a reference for those who are working in the field of noise parameter extraction using tuner-based methods. [ABSTRACT FROM AUTHOR]

Yukawa potentials may be long-ranged when the Debye screening length is large. In computer simulations, such long-ranged potentials have to be taken into account with convenient algorithms to avoid systematic bias in the sampling of the phase space. Recently, we provided Ewald sums for quasi-two-dimensional systems with Yukawa interaction potentials [J. Chem. Phys. 126, 056101 (2007); Molec. Phys. paper I of this series]. Sometimes, Lekner sums are used as an alternative to Ewald sums for Coulomb systems. In the present work, we derive the Lekner sums for quasi-two-dimensional systems with Yukawa interaction potentials and we give numerical tests for practical implementations. The main result of this paper is to emphasize that Lekner sums cannot be considered as an alternative to Ewald sums for Yukawa potentials. As a conclusion to this work: Lekner sums should not be used for quasi-two-dimensional systems with Yukawa interaction potentials. [ABSTRACT FROM AUTHOR]

A key problem of mobile robots is that of the positioning capability in order to detect their locations in the operating environment. A promising technology used in indoor localization recently is Visible Light Communication (VLC). In this paper, an integrated Angle of Arrival-Received Signal Strength (AOA-RSS) localization method using the VLC, which could get high accuracy with simple hardware, is proposed. In addition, the Extended Kalman Filter (EKF) and Particle Filter (PF) algorithms are combined with the proposed AOA-RSS localization method in order to achieve higher accuracy of the mobile robot positioning. By computer simulation, the performance of the proposed AOA-RSS localization method combined with the EKF and PF algorithms are compared. The combination scheme outperforms the individual VLC localization with small error approximation of a few centimetres. [ABSTRACT FROM AUTHOR]

Gas source localization (GSL) is a critical component in wireless sensor network (WSN) which can be used to estimate the position of gas leaks through the gas concentration measured by the monitoring nodes. In this paper, we first derive a gas diffusion model under windy conditions based on the gas diffusion theory. Because of the nonlinearity of the gas diffusion model under windy conditions, the traditional weighted centroid algorithm for gas source localization produces very inaccurate estimation of the source location. To address this problem, we propose a novel gas source localization algorithm which combines the weighted centroid method and particle filter. Simulation results validate the effectiveness of our algorithm under unknown gas source strength. Compared to weighted centroid method alone, our algorithm shows a higher accuracy in location. Moreover, its convergence rate is improved by the preestimation of initial value. [ABSTRACT FROM AUTHOR]

If the three dimensional self-avoiding walk (SAW) is conformally invariant, then one can compute the hitting densities for the SAW in a half-space and in a sphere (Kennedy in Phys Rev Lett 111: 165703, ). The ensembles of SAW's used to define these hitting densities involve walks of arbitrary lengths, and so these ensembles cannot be directly studied by the pivot Monte Carlo algorithm for the SAW. We show that these mixed length ensembles should have the same scaling limit as certain weighted ensembles that only involve walks with a single length, thus providing a fast method for simulating these ensembles. Preliminary simulations which found good agreement between the predictions and Monte Carlo simulations for the SAW were reported in Kennedy (Phys Rev Lett 111: 165703, ). In this paper we present more accurate simulations testing the predictions and find even stronger support for the prediction that the SAW is conformally invariant in three dimensions. [ABSTRACT FROM AUTHOR]

Monte Carlo algorithms are nearly always based on the concept of detailed balance and ergodicity. In this paper we focus on algorithms that do not satisfy detailed balance. We introduce a general method for designing non-detailed balance algorithms, starting from a conventional algorithm satisfying detailed balance. This approach is first applied to a very simple model, which shows the basic viability of the method. Then we apply it to the Ising model, where we find that the method is an improvement compared to the standard Metropolis algorithm, be it with a modest gain of a factor 2.3. [ABSTRACT FROM AUTHOR]

Fisher distribution is the most commonly used probability density function for discontinuity orientations. Based on Fisher distribution, Monte Carlo simulation method for discontinuity orientations was reviewed and improved. Those orientations extending beyond the edge of an upper hemisphere projection (OEBEUHP) often have an important influence on both the mean orientation and Fisher constant K, thus affecting simulation results. The detailed algorithms for identifying and adjusting those OEBEUHP were developed in this paper. Based on the improved method, a program for generating discontinuity orientations and plotting their stereographic projection maps, named as MCSDO, was developed. Due to the aforementioned adjustment, the generated orientations by MCSDO are close to the original discontinuity orientations, which were mapped in field, and satisfactory. Only the original orientations and target number of generated orientations need to be input. By running the program we can directly obtain the follows: orientations of generated discontinuities, mean orientations of both original and generated discontinuities, Fisher constant K of both original and generated discontinuities, and stereographic projection maps of both original and generated discontinuities. MCSDO is a freeware designed for researchers and practicing engineers, and can be easily mastered with a little computer knowledge. [ABSTRACT FROM AUTHOR]

This paper develops a sequential trans-dimensional Monte Carlo algorithm for geoacoustic inversion in a strongly range-dependent environment. The algorithm applies advanced Markov chain Monte Carlo methods in combination with sequential techniques (particle filters) to carry out geoacoustic inversions for consecutive data sets acquired along a track. Changes in model parametrization along the track (e.g., number of sediment layers) are accounted for with trans-dimensional partition modeling, which intrinsically determines the amount of structure supported by the data information content. Challenging issues of rapid environmental change between consecutive data sets and high information content (peaked likelihood) are addressed by bridging distributions implemented using annealed importance sampling. This provides an efficient method to locate high-likelihood regions for new data which are distant and/or disjoint from previous high-likelihood regions. The algorithm is applied to simulated reflection-coefficient data along a track, such as can be collected using a towed array close to the seabed. The simulated environment varies rapidly along the track, with changes in the number of layers, layer thicknesses, and geoacoustic parameters within layers. In addition, the seabed contains a geologic fault, where all layers are offset abruptly, and an erosional channel. Changes in noise level are also considered. [ABSTRACT FROM AUTHOR]

We have developed a general-purpose Monte Carlo simulation code, called penMesh, that combines the accuracy of the radiation transport physics subroutines from PENELOPE and the flexibility of a geometry based on triangle meshes. While the geometric models implemented in most general-purpose codes-such as PENELOPE's quadric geometry-impose some limitations in the shape of the objects that can be simulated, triangle meshes can be used to describe any free-form (arbitrary) object. Triangle meshes are extensively used in computer-aided design and computer graphics. We took advantage of the sophisticated tools already developed in these fields, such as an octree structure and an efficient ray-triangle intersection algorithm, to significantly accelerate the triangle mesh ray-tracing. A detailed description of the new simulation code and its ray-tracing algorithm is provided in this paper. Furthermore, we show how it can be readily used in medical imaging applications thanks to the detailed anatomical phantoms already available. In particular, we present a whole body radiography simulation using a triangulated version of the anthropomorphic NCAT phantom. An example simulation of scatter fraction measurements using a standardized abdomen and lumbar spine phantom, and a benchmark of the triangle mesh and quadric geometries in the ray-tracing of a mathematical breast model, are also presented to show some of the capabilities of penMesh. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, a two-consecutive steps anodic dissolution mechanism is simulated at the atomic level by a Monte Carlo algorithm on a 3D lattice. In contrast with a previous work restricted to the 2D flat case, it is shown that the steady state and transient behaviors are controlled not only by the adsorbed intermediate coverage degree but also by the area of the rough interface build up by the dissolution of interfacial atoms. It is established that the complex impedance behavior results from a combination of the individual frequency responses of these two quantities. The emphasis is put on the specific properties of the impedance induced by the surface roughness relaxation for which a kinetic description is proposed and compared to the Monte Carlo data. It is clearly concluded that, by taking into consideration the surface re-arrangement, the number of frequency domains in the impedance may be larger than predicted by the derivation of a kinetic model on a flat interface. [Copyright &y& Elsevier]

In this paper, an efficient detector is developed to address the blind detection problem for an orthogonal-frequency-division-multiplexing (OFDM) system in the presence of phase noise and unknown multipath fading, even with channel order that is possibly not known and time varying. The proposed maximum a posteriori detector is a combination of the sequential Monte Carlo (SMC) method and the variance reduction strategy known as Rao-Blackwellization. Being blind, the developed detector, does not rely on pilot tones for the detection of the transmitted data. However, as in most work found in the literature, the aforementioned detector, which we call the RB-SMC detector, invokes the assumption of a fixed and known channel order, which may be a limitation in a number of scenarios. Therefore, to relax this assumption, we model channel order uncertainty via a first-order Markov process and subsequently introduce appropriate extensions to the RB-SMC detector, thereby proposing a novel algorithm called the E-RB-SMC detector. The performance of the novel SMC-based detectors are validated through computer simulations. It is shown that the proposed SMC-based detectors achieve near bound performance. In terms of convergence speed, the proposed E-RB-SMC detector also shows the smallest acquisition time amongst the considered algorithms. [ABSTRACT FROM AUTHOR]

With the advent of powerful computers and parallel processing including Grid technology, the use of Monte Carlo (MC) techniques for radiation transport simulation has become the most popular method for modeling radiological imaging systems and particularly X-ray computed tomography (CT). The stochastic nature of involved processes such as X-ray photons generation, interaction with matter and detection makes MC the ideal tool for accurate modeling. MC calculations can be used to assess the impact of different physical design parameters on overall scanner performance, clinical image quality and absorbed dose assessment in CT examinations, which can be difficult or even impossible to estimate by experimental measurements and theoretical analysis. Simulations can also be used to develop and assess correction methods and reconstruction algorithms aiming at improving image quality and quantitative procedures. This paper focuses mainly on recent developments and future trends in X-ray CT MC modeling tools and their areas of application. An overview of existing programs and their useful features will be given together with recent developments in the design of computational anthropomorphic models of the human anatomy. It should be noted that due to limited space, the references contained herein are for illustrative purposes and are not inclusive; no implication that those chosen are better than others not mentioned is intended. [ABSTRACT FROM AUTHOR]

A deterministic algorithm is proposed to compute the contribution of first-order Compton- and Rayleigh-scattered radiation in X-ray imaging. This algorithm has been implemented in a simulation code named virtual X-ray imaging. The physical models chosen to account for photon scattering are the well-known form factor and incoherent scattering function approximations, which are recalled in this paper and whose limits of validity are briefly discussed. The proposed algorithm, based on a voxel discretization of the inspected object, is presented in detail, as well as its results in simple configurations, which are shown to converge when the sampling steps are chosen sufficiently small. Simple criteria for choosing correct sampling steps (voxel and pixel size) are established. The order of magnitude of the computation time necessary to simulate first-order scattering images amounts to hours with a PC architecture and can even be decreased down to minutes, if only a profile is computed (along a linear detector). Finally, the results obtained with the proposed algorithm are compared to the ones given by the Monte Carlo code Geant4 and found to be in excellent accordance, which constitutes a validation of our algorithm. The advantages and drawbacks of the proposed deterministic method versus the Monte Carlo method are briefly discussed. [Copyright &y& Elsevier]

This paper presents concentrator and lens models for the detector and emitter, respectively, upon which a Monte Carlo ray-tracing algorithm allows the evaluation of impulse response on infrared (IR) wireless indoor channels. We also present computer simulation results that show the effects of concentrator FOV and reception direction on the impulse response, received optical power, and channel rms delay spread, which allow us to propose structures for angle-diversity receivers. © 2003 Wiley Periodicals, Inc. Microwave Opt Technol Lett 36: 262–267, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.10738 [ABSTRACT FROM AUTHOR]