  The characteristics of the surface waves along the interface between a plasma
and a dielectric material have been investigated using kinetic Particle-In-Cell
(PIC) simulations. A microwave source of GHz frequency has been used to trigger
the surface wave in the system. The outcome indicates that the surface wave
gets excited along the interface of plasma and the dielectric tube and appears
as light and dark patterns in the electric field profiles. The dependency of
radiation pressure on the dielectric permittivity and supplied input frequency
has been investigated. Further, we assessed the capabilities of neural networks
to predict the radiation pressure for a given system. The proposed Deep Neural
Network model is aimed at developing accurate and efficient data-driven plasma
surface wave devices.
