Better than counting: Density profiles from force sampling

Calculating one-body density profiles in equilibrium via particle-based simulation methods involves counting of events of particle occurrences at (histogram-resolved) space points. Here we investigate an alternative method based on a histogram of the local force density. Via an exact sum rule the density profile is obtained with a simple spatial integration. The method circumvents the inherent ideal gas fluctuations. We have tested the method in Monte Carlo, Brownian Dynamics and Molecular Dynamics simulations. The results carry a statistical uncertainty smaller than that of the standard, counting, method, reducing therefore the computation time

Beyond Poisson-Boltzmann: Numerical sampling of charge density fluctuations

We present a method aimed at sampling charge density fluctuations in Coulomb systems. The derivation follows from a functional integral representation of the partition function in terms of charge density fluctuations. Starting from the mean-field solution given by the Poisson-Boltzmann equation, an original approach is proposed to numerically sample fluctuations around it, through the propagation of a Langevin like stochastic partial differential equation (SPDE). The diffusion tensor of the SPDE can be chosen so as to avoid the numerical complexity linked to long-range Coulomb interactions, effectively rendering the theory completely local. A finite-volume implementation of the SPDE is described, and the approach is illustrated with preliminary results on the study of a system made of two like-charge ions immersed in a bath of counter-ions

Density estimation for grouped data with application to line transect sampling

Line transect sampling is a method used to estimate wildlife populations, with the resulting data often grouped in intervals. Estimating the density from grouped data can be challenging. In this paper we propose a kernel density estimator of wildlife population density for such grouped data. Our method uses a combined cross-validation and smoothed bootstrap approach to select the optimal bandwidth for grouped data. Our simulation study shows that with the smoothing parameter selected with this method, the estimated density from grouped data matches the true density more closely than with other approaches. Using smoothed bootstrap, we also construct bias-adjusted confidence intervals for the value of the density at the boundary. We apply the proposed method to two grouped data sets, one from a wooden stake study where the true density is known, and the other from a survey of kangaroos in Australia.Comment: Published in at http://dx.doi.org/10.1214/09-AOAS307 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

The Size and Shape of Voids in Three-Dimensional Galaxy Surveys

The sizes and shapes of voids in a galaxy survey depend not only on the physics of structure formation, but also on the sampling density of the survey and on the algorithm used to define voids. Using an N-body simulation with a CDM power spectrum, we study the properties of voids in samples with different number densities of galaxies, both in redshift space and in real space. When voids are defined as regions totally empty of galaxies, their characteristic volume is strongly dependent on sampling density; when they are defined as regions whose density is 0.2 times the mean galaxy density, the dependence is less strong. We compare two void-finding algorithms, one in which voids are nonoverlapping spheres, and one, based on the algorithm of Aikio and Mahonen, which does not predefine the shape of a void. Regardless of the algorithm chosen, the characteristic void size is larger in redshift space than in real space, and is larger for low sampling densities than for high sampling densities. We define an elongation statistic Q which measures the tendency of voids to be stretched or squashed along the line of sight. Using this statistic, we find that at sufficiently high sampling densities (comparable to the number densities of galaxies brighter than L_*), large voids tend to be slightly elongated along the line of sight in redshift space.Comment: LaTex, 21 pages (including 7 figures), ApJ, submitte