One of the most remarkable basis of the gravity data inversion is the recognition of sharp boundaries between an ore body and its host rocks during the interpretation step. Therefore, in this work, it is attempted to develop an inversion approach to determine a 3D density distribution that produces a given gravity anomaly. The subsurface model consists of a 3D rectangular prisms of known sizes ...

reflection and refraction of em signals at both horizontal and vertical interfaces separate media of different electrical parameters, geoelectromagnetic methods have been developed and employed to recognize the geological features and particularly fault zones in many regions. to achieve higher lateral resolution and also greater depth penetration, the mt method is one of the most effective elec...

one of the most remarkable basis of the gravity data inversion is the recognition of sharp boundaries between an ore body and its host rocks during the interpretation step. therefore, in this work, it is attempted to develop an inversion approach to determine a 3d density distribution that produces a given gravity anomaly. the subsurface model consists of a 3d rectangular prisms of known sizes ...

The manipulation of topologically protected field configurations, already predicted and experimentally observed in non-centrosymmetric magnets, as skyrmions, merons antimerons could definitely have potential applications logic gate operations carriers information. Here, we present elaborate a proof concept on how to construct three-input non-canonical majority kagome ferromagnet lacking inversi...

The Su-Schrieffer-Heeger . (SSH) chain is a one-dimensional lattice that comprises two dimerized sublattices. Recently, Zhu, Prodan, and Ahn (ZPA) [Phys. Rev. B 99, 041117(R) (2019)] proposed flat bands can occur at the topological domain walls of two-dimensional array SSH chains. Here, we suggest insulator protected by inversion time-reversal symmetries without spin-orbit coupling. It shown ch...

Abstract Conventional linear iterative methods for magnetotelluric sounding (MT) suffer from considerable limitations related to difficulties in selecting the initial model and local optima. On other hand, conventional intelligent nonlinear exhibit slow convergence low accuracy. In this study, we propose an inversion strategy based on deep learning (DL) belief network (DBN) realise instantaneou...