Efficient tight-binding Monte Carlo structural sampling of complex materials

PACS. 71.55.Jv – Disordered structures; amorphous and glassy solids. PACS. 61.43.Dq – Amorphous semiconductors, metals, and alloys. Abstract. – While recent work towards the development of tight-binding and ab initio algorithms has focused on molecular dynamics, Monte Carlo methods can often lead to better results with relatively little effort. We present here a multi-step Monte Carlo algorithm that makes use of the possibility of quickly evaluating local energies. For the thermalization of a 1000-atom configuration of a-Si, this algorithm gains about an order of magnitude in speed over standard molecular dynamics. The algorithm can easily be ported to a wide range of materials and can be dynamically optimized for a maximum efficiency. Monte Carlo techniques are extensively used in statistical physics, but have received rela-tively little attention in the materials theory community. Most of the recent efforts towards the development of fast tight-binding or ab initio codes, for example, have been done within the framework of molecular dynamics (MD) [1–3]. Since all atoms move simultaneously within MD, there are limitations to the approaches that can be used. In particular, the most promis-ing order-N MD-based methods [4–6] are only applicable to materials with a well-define