We develop a new Lagrangian primitive, named Langevin particle, to incorporate turbulent flow details in fluid simulation. A group of the particles are distributed inside the simulation domain based on a turbulence energy model with turbulence viscosity. A particle in particular moves obeying the generalized Langevin equation, a well known stochastic differential equation that describes the par...

We consider the single particle relaxation rate of 2D electrons subject to a random magnetic field. The density of states (DOS) oscillations in a uniform magnetic field (in addition to a random one) are studied. It is shown that the infrared singularities appearing in perturbation theory for the single particle relaxation rate are spurious and can be regularized by a proper choice of gauge. We ...

A stochastic inverse technique based on a genetic algorithm (GA) to invert particle-size distribution from angular light-scattering data is developed. This inverse technique is independent of any given a priori information of particle-size distribution. Numerical tests show that this technique can be successfully applied to inverse problems with high stability in the presence of random noise an...

This paper investigates convex belief propagation algorithms for Markov random fields (MRFs) with continuous variables. Our first contribution is a theorem generalizing properties of the discrete case to the continuous case. Our second contribution is an algorithm for computing the value of the Lagrangian relaxation of the MRF in the continuous case based on associating the continuous variables...

We study the directional far-field response of a spherical nanoantenna via engineering the plasmonic nanosphere's distance, size, and material. A unified pattern synthesis approach based on the T-matrix method and the particle swarm optimization is proposed for the directional beamforming of the nanoantenna. The angular response of the directional nanoantenna is very sensitive to the material c...

In this paper, we propose to enhance particle-based stochastic optimization methods (SO) by using Principal Component Analysis (PCA) to build an approximation of the cost function in a neighborhood of particles during optimization. Then we use it to shift the samples in the direction of maximum cost change. We provide theoretical basis and experimental results showing that such enhancement impr...

We discuss properties of the quadrupole collective excitation of the deformed neutronrich nucleus Mg within the framework of quasi-particle random phase approximation (QRPA). We first solve the coupled-channels equations to obtain the single-particle levels, and construct the ground state by treating the pairing correlations in the BCS approximation. We then solve the QRPA equation using the re...

In this paper, a generalized particle system (GPS) method, a general method to describe multiple strong form representation based particle methods is described. Gradient, divergence, and Laplacian operators used in various strong form based particle method such as moving particle semi-implicit (MPS) method, smooth particle hydrodynamics (SPH), and peridynamics, can be described by the GPS metho...