Abstract Within seismology, geology, civil and structural engineering, deep learning (DL), especially via generative adversarial networks (GANs), represents an innovative, engaging, advantageous way to generate reliable synthetic data that represent actual samples’ characteristics, providing a handy augmentation tool. Indeed, in many practical applications, obtaining significant number of high-...

We investigate the role of neutron star superfluidity for magnetar oscillations. Using a plane-wave analysis we estimate the effects of a neutron superfluid in the elastic crust region. We demonstrate that the superfluid imprint is likely to be more significant than the effects of the crustal magnetic field. We also consider the region immediately beneath the crust, where superfluid neutrons ar...

Introduction: The most detailed knowledge that we have on the interior structure so far concerning planetary bodies besides the Earth is the Moon. The Apollo seismic data have provided us with a unique opportunity to elucidate the internal structure of the Moon. The primary data set employed here are the Apollo seismic data which were obtained in the period from 1969 to 1972 when the US Apollo ...

T he foundation of seismology is the theory of wave motion, a complicated concept that is still after centuries of experiments and speculations by many of the very greatest scientists an area of active research in many disciplines. Even simple forms of wave motion are difficult to describe verbally; but, ironically, the simplest type of wave is remarkably easy to describe (and subsequently anal...