Seismic tomography, frozen Gaussian approximation and deep learning - Associate Professor Xu Yang (UC Santa Barbara)
Three-dimensional (3-D) elastic wave propagation and seismic tomography is computationally challenging in large scales and high-frequency regime. In this talk, we propose the frozen Gaussian approximation (FGA) to compute the 3-D elastic wave propagation and use it as the forward modeling tool for seismic tomography with high-frequency data. The accuracy and parallelizability of the FGA algorithm is illustrated by comparing to the spectral element method. With a parallel FGA solver built as a computational platform, we explore various applications in 3-D seismic tomography, including seismic travel time tomography and full waveform inversion, respectively. Global minimization for seismic tomography is investigated based on particle swarm algorithm. We also apply the FGA algorithm to train deep neural networks to learn the object of low velocity in the interested areas.
About Applied and computational maths seminars
Our seminars bring together UQ's applied and computational mathematics communities.
UQ and invited scientists deliver the presentations, which are informal and promote discussion.
We welcome suggestions for speakers and topics from staff, students and visitors, and encourage students to share their work.
Our seminars are usually held on Thursdays from 3pm to 4pm.
To suggest a topic or speaker, and for more information, contact Dr Dietmar Oelz or Dr Cecilia Gonzalez Tokman.