Inelastic Scattering, Emergent Interactions of Solitons in the Zakharov-Kuznetsov Equation through Conservative and non-Conservative Physics-Informed Neural Networks
A. Nakamula, K. Obuse, N. Sawado, K. Shimasaki, Y. Shimazaki, Y. Suzuki, K. Toda

TL;DR
This paper uses physics-informed neural networks to analyze soliton collisions in the Zakharov-Kuznetsov equation, introducing conservative PINNs to ensure conservation laws are satisfied and revealing emergent interactions during collisions.
Contribution
It introduces conservative PINNs for the Zakharov-Kuznetsov equation, enabling conservation law adherence and uncovering emergent interactions through inverse analysis.
Findings
Conservative PINNs successfully enforce conservation laws during soliton collisions.
Inverse analysis reveals significant coefficient changes indicating emergent interactions.
Recalculated equations with modulated coefficients improve conservation adherence.
Abstract
The Zakharov-Kuznetsov equation, originally a three dimensional mathematical model of plasma with a uniform magnetic field, is a direct extension of the KdV equation into higher dimensions and is a typical quasi-integrable system. Physics-Informed Neural Networks (PINNs) are used to study the collision of soliton solutions in the 2+1 dimensional Zakharov-Kuznetsov equation. PINNs are able to successfully solve the equations in the forward process, and the solutions are obtained using a mesh-free approach and automatic differentiation, taking into account conservation laws. In the inverse process, the proper form of the equation can be successfully derived from a given training data. However, the situation becomes intractable in the collision process. The forward analysis result no longer adheres to the laws of conservation, and is better described as a dynamically incompatible field…
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Taxonomy
TopicsSpectroscopy and Laser Applications · Seismic Waves and Analysis · Nonlinear Photonic Systems
