Nonlinear and -clock models on sparse random graphs: mode-locking transition of localized waves
arXiv:1411.4674 · doi:10.1103/PhysRevB.91.054201
Abstract
A statistical mechanic study of the model with nonlinear interaction is presented on bipartite sparse random graphs. The model properties are compared to those of the -clock model, in which the planar continuous spins are discretized into values. We test the goodness of the discrete approximation to the XY spins to be used in numerical computations and simulations and its limits of convergence in given, -dependent, temperature regimes. The models are applied to describe the mode-locking transition of the phases of light-modes in lasers at the critical lasing threshold. A frequency is assigned to each variable node and function nodes implement a frequency matching condition. A non-trivial unmagnetized phase-locking occurs at the phase transition, where the frequency dependence of the phases turns out to be linear in a broad range of frequencies, as in standard mode-locking multimode laser at the optical power threshold.
13 pages, 13 figures
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- Self-starting nonlinear mode-locking in random lasers
- Statistical physical theory of mode-locking laser generation with a frequency comb
- The random field XY model on sparse random graphs shows replica symmetry breaking and marginally stable ferromagnetism
- Comparison of Gabay-Toulouse and de Almeida-Thouless instabilities for the spin glass XY model in a field on sparse random graphs
- Regularization and decimation pseudolikelihood approaches to statistical inference in -spin models
- Multi-body quenched disordered and -clock models on random graphs
- Low energy excitations of mean-field glasses
- Improved Pseudolikelihood Regularization and Decimation methods on Non-linearly Interacting Systems with Continuous Variables
- Inverse problem for multi-body interaction of nonlinear waves
- Inference for interacting linear waves in ordered and random media
- Mean-field theory of vector spin models on networks with arbitrary degree distributions