![Clio Johnson](https://www.lancaster.ac.uk/2021ugconference/wp-content/themes/lancaster2021/images/profile.png)
Clio Johnson
The central dilemma of quantum mechanics is often how best to solve the Schrödinger wave equation in order to find the wavefunction and allowed energies of a system. This becomes much harder the larger or more complicated a system of particles gets, requiring numerical methods to solve. One such class of methods are quantum Monte Carlo (QMC) simulations, defined by their use of random number generation. At the start of a QMC simulation an initial guess must be made or generated. The convergence of QMC simulations is sensitive to the accuracy of these initial configurations. This project aimed to explore various algorithms to generate initial electron distributions within a QMC program called CASINO. The default algorithm simply placed electrons randomly within 2 Bohr radii of a given nucleus. Algorithms explored by this project included samplers with probability density functions based on hydrogenic orbitals, approximate charge densities and Slater-type orbitals.