Physics – Condensed Matter – Disordered Systems and Neural Networks
Scientific paper
2003-08-31
High Performance Computing in Science and Engineering Garching 2004, A. Bode, F. Durst (Eds.), Springer Verlag, 2005, pp 237-2
Physics
Condensed Matter
Disordered Systems and Neural Networks
13 pages, 10 figures
Scientific paper
Taking into account that a proper description of disordered systems should focus on distribution functions, the authors develop a powerful numerical scheme for the determination of the probability distribution of the local density of states (LDOS), which is based on a Chebyshev expansion with kernel polynomial refinement and allows the study of large finite clusters (up to $100^3$). For the three-dimensional Anderson model it is demonstrated that the distribution of the LDOS shows a significant change at the disorder induced delocalisation-localisation transition. Consequently, the so-called typical density of states, defined as the geometric mean of the LDOS, emerges as a natural order parameter. The calculation of the phase diagram of the Anderson model proves the efficiency and reliability of the proposed approach in comparison to other localisation criteria, which rely, e.g., on the decay of the wavefunction or the inverse participation number.
Fehske Holger
Schubert Gerald
Weisse Alexander
Wellein Gerhard
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