Short-range plasma model for intermediate spectral statistics

E. Bogomolny, U. Gerland, C. Schmit

Research output: Contribution to journalArticlepeer-review

74 Scopus citations

Abstract

We propose a plasma model for spectral statistics displaying level repulsion without long-range spectral rigidity, i.e. statistics intermediate between random matrix and Poisson statistics similar to the ones found numerically at the critical point of the Anderson metal-insulator transition in disordered systems and in certain dynamical systems. The model emerges from Dysons one-dimensional gas corresponding to the eigenvalue distribution of the classical random matrix ensembles by restricting the logarithmic pair interaction to a finite number k of nearest neighbors. We calculate analytically the spacing distributions and the two-level statistics. In particular we show that the number variance has the asymptotic form ∑2(L) ∼ χL for large L and the nearest-neighbor distribution decreases exponentially when s → ∞, P(s) ∼ exp(-Λs) with A = 1/χ = kβ + 1, where β is the inverse temperature of the gas (β = 1, 2 and 4 for the orthogonal, unitary and symplectic symmetry class respectively). In the simplest case of k = β= 1, the model leads to the so-called Semi-Poisson statistics characterized by particular simple correlation functions e.g. P(S) = 4s exp(-2s). Furthermore we investigate the spectral statistics of several pseudointegrable quantum billiards numerically and compare them to the Semi-Poisson statistics.

Original languageEnglish
Pages (from-to)121-132
Number of pages12
JournalEuropean Physical Journal B
Volume19
Issue number1
DOIs
StatePublished - 1 Jan 2001
Externally publishedYes

Keywords

  • 03.65.Sq Semiclassical theories and applications
  • 05.40.-a Fluctuation phenomena, random processes, noise and Brownian motion
  • 05.45.-a Nonlinear dynamics and nonlinear dynamical systems

Fingerprint

Dive into the research topics of 'Short-range plasma model for intermediate spectral statistics'. Together they form a unique fingerprint.

Cite this