First Records of \u3ci\u3eCecidomyia Candidipes\u3c/i\u3e (Diptera: Cecidomyiidae) in Wisconsin

First report of Cecidomyia candidipes from five Wisconsin counties

New Records of Rhopalosomatidae (Hymenoptera: Vespoidea) From Wisconsin

The rhopalosomatid Olixon banksii is recorded from Wisconsin for the first time

Vacancy diffusion in the triangular lattice dimer model

We study vacancy diffusion on the classical triangular lattice dimer model, sub ject to the kinetic constraint that dimers can only translate, but not rotate. A single vacancy, i.e. a monomer, in an otherwise fully packed lattice, is always localized in a tree-like structure. The distribution of tree sizes is asymptotically exponential and has an average of 8.16 \pm 0.01 sites. A connected pair of monomers has a finite probability of being delocalized. When delocalized, the diffusion of monomers is anomalous:Comment: 15 pages, 27 eps figures. submitted to Physical Review

Notes on \u3ci\u3eTaeniogonalos Gundlachii\u3c/i\u3e (Hymenoptera: Trigonalidae) From Wisconsin

This is the first report of Taeniogonalos gundlachii (Cresson) (Hymenoptera: Trigonalidae) from Wisconsin and of this hyperparasitoid reared from the initial host Euchaetes egle (Drury) (Lepidoptera: Arctiidae). Data are provided from 30 Malaise trap specimens and from a single reared specimen

Selective-pivot sampling of radial distribution functions in asymmetric liquid mixtures

We present a Monte Carlo algorithm for selectively sampling radial distribution functions and effective interaction potentials in asymmetric liquid mixtures. We demonstrate its efficiency for hard-sphere mixtures, and for model systems with more general interactions, and compare our simulations with several analytical approximations. For interaction potentials containing a hard-sphere contribution, the algorithm yields the contact value of the radial distribution function.Comment: 5 pages, 5 figure

A Rapid Dynamical Monte Carlo Algorithm for Glassy Systems

In this paper we present a dynamical Monte Carlo algorithm which is applicable to systems satisfying a clustering condition: during the dynamical evolution the system is mostly trapped in deep local minima (as happens in glasses, pinning problems etc.). We compare the algorithm to the usual Monte Carlo algorithm, using as an example the Bernasconi model. In this model, a straightforward implementation of the algorithm gives an improvement of several orders of magnitude in computational speed with respect to a recent, already very efficient, implementation of the algorithm of Bortz, Kalos and Lebowitz.Comment: RevTex 7 pages + 4 figures (uuencoded) appended; LPS preprin