Physics – Condensed Matter – Disordered Systems and Neural Networks
Scientific paper
1999-12-07
Zh.Eksp.Teor.Fiz. 111 (1997) 220-249
Physics
Condensed Matter
Disordered Systems and Neural Networks
17 pages, PDF
Scientific paper
Asymptotically exact results are obtained for the average Green function and density of states of a disordered system for a renormalizable class of models (as opposed to the lattice models examined previously [Zh. Eksp. Teor. Fiz. 106 (1994) 560-584]). For N\sim 1 (where N is an order of the perturbation theory), only the parquet terms corresponding to the highest powers of large logarithms are retained. For large N, this approximation is inadequate because of the fast growth with N of the coefficients for the lower powers of the logarithms. The latter coefficients are calculated in the leading order in N from the Callan-Symanzik equation with results of the Lipatov method using as boundary conditions. For calculating the self-energy at finite momentum, a modification of the parquet approximation is used, that allows the calculations to be done in an arbitrary finite logarithmic approximation but in the leading order in N. It is shown that the phase transition point shifts in the complex plane, thereby insuring regularity of the density of states for all energies. The "spurious" pole is avoided in such a way that effective interaction remains logarithmically weak.
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