English

Power-law localization in one-dimensional systems with nonlinear disorder under fixed input conditions

Disordered Systems and Neural Networks 2024-08-30 v1

Abstract

We conduct a numerical investigation into wave propagation and localization in one-dimensional lattices subject to nonlinear disorder, focusing on cases with fixed input conditions. Utilizing a discrete nonlinear Schr\"odinger equation with Kerr-type nonlinearity and a random coefficient, we compute the averages and variances of the transmittance, TT, and its logarithm, as functions of the system size LL, while maintaining constant intensity for the incident wave. In cases of purely nonlinear disorder, we observe power-law localization characterized by TLγa\langle T \rangle \propto L^{-\gamma_a} and lnTγglnL\langle \ln T \rangle \approx -\gamma_g \ln L for sufficiently large LL. At low input intensities, a transition from exponential to power-law decay in T\langle T \rangle occurs as LL increases. The exponents γa\gamma_a and γg\gamma_g are nearly identical, converging to approximately 0.5 as the strength of the nonlinear disorder, β\beta, increases. Additionally, the variance of TT decays according to a power law with an exponent close to 1, and the variance of lnT\ln T approaches a small constant as LL increases. These findings are consistent with an underlying log-normal distribution of TT and suggest that wave propagation behavior becomes nearly deterministic as the system size increases. When both linear and nonlinear disorders are present, we observe a transition from power-law to exponential decay in transmittance with increasing LL when the strength of linear disorder, VV, is less than β\beta. As VV increases, the region exhibiting power-law localization diminishes and eventually disappears when VV exceeds β\beta, leading to standard Anderson localization.

Keywords

Cite

@article{arxiv.2408.09339,
  title  = {Power-law localization in one-dimensional systems with nonlinear disorder under fixed input conditions},
  author = {Ba Phi Nguyen and Kihong Kim},
  journal= {arXiv preprint arXiv:2408.09339},
  year   = {2024}
}

Comments

8 pages, 7 figures

R2 v1 2026-06-28T18:15:44.088Z