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Stationary waves on nonlinear quantum graphs: General framework and canonical perturbation theory
Sven Gnutzmann1, Daniel Waltner2
1School of Mathematical Sciences, University of Nottingham, Nottingham NG7 2RD, United Kingdom.
Physical Review. E
|April 15, 2016
Summary
We present a framework for solving the stationary nonlinear Schrödinger equation (NLSE) on networks. This method simplifies complex differential equations into algebraic ones, aiding in analyzing wave phenomena on graphs.
Area of Science:
- Mathematical Physics
- Nonlinear Dynamics
- Graph Theory
Background:
- The stationary nonlinear Schrödinger equation (NLSE) models various physical phenomena.
- Solving NLSE on complex network structures like metric graphs is challenging.
- Existing methods often struggle with the nonlinearity and network topology.
Purpose of the Study:
- To develop a general framework for solving the stationary NLSE on metric graphs.
- To provide a method for analyzing wave propagation in 1D wire networks.
- To simplify the mathematical treatment of nonlinear systems on graphs.
Main Methods:
- Modeling 1D wires as a metric graph with vertex matching conditions.
- Deriving a nonlinear transfer operation for the wave function and its derivative.
- Expressing the nonlinear transfer for cubic NLSE using Jacobi elliptic functions.
- Reducing differential equations to a system of nonlinear algebraic equations.
Main Results:
- A formal solution is established for the stationary NLSE on metric graphs.
- The nonlinear transfer operation is explicitly defined for the cubic NLSE.
- The problem is successfully reduced to solving a finite set of algebraic equations.
- Canonical perturbation theory is applied to extract leading nonlinear corrections for small amplitudes.
Conclusions:
- The proposed framework offers an efficient method for solving NLSE on network structures.
- The use of Jacobi elliptic functions provides an explicit solution for the cubic NLSE.
- The approach facilitates the analysis of nonlinear wave phenomena in complex systems.
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