Two different Reverse Monte Carlo strategies, RMC++ and RMCPOW, have been compared for determining the microscopic structure of some liquid and amorphous solid systems on the basis of neutron diffraction measurements. The first, $g(r)$ route, exploit
s the isotropic nature of liquids and calculates the total scattering structure factor, $S(Q)$, via a one-dimensional Fourier transform of the radial distribution function. The second, called crystallography route, is based on the direct calculation of $S(Q)$ in the reciprocal space from the atomic positions in the simulation box. We describe these two methods and apply them to four disordered systems of increasing complexity. The two approaches yield structures in good agreement to the level of two- and three body correlations; consequently, it has been proven that the crystallography route can also deal perfectly with disordered materials. This finding is important for future studies of liquids confined in porous media, where handling Bragg and diffuse scattering simultaneously is unavoidable.
We investigate Monte Carlo simulation strategies for determining the effective (depletion) potential between a pair of hard spheres immersed in a dense sea of much smaller hard spheres. Two routes to the depletion potential are considered. The first
is based on estimates of the insertion probability of one big sphere in the presence of the other; we describe and compare three such methods. The second route exploits collective (cluster) updating to sample the depletion potential as a function of the separation of the big particles; we describe two such methods. For both routes we find that the sampling efficiency at high densities of small particles can be enhanced considerably by exploiting `geometrical shortcuts that focus the computational effort on a subset of small particles. All the methods we describe are readily extendable to particles interacting via arbitrary potentials.
