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“Data analysis links all fields of science.”
PhD project title:
From Dark Matter to the Earth’s Deep Interior - There and Back Again.
Project description:
At first glance, dark matter and the Earth’s deep interior have nothing to do with each other. One is far above our heads, the other is just beneath our feet. We have very little idea of what makes up one, and concrete ideas about what makes up the other. But when you think for a little bit, similarities arise. Both live on spherical domains (the celestial sphere and the Earth). We can’t observe either of them directly (dark matter doesn’t interact with light and we can’t dig down very far), so we have to rely on inferences made from the effects they have on other things, such as light and seismic waves.
Data analysis is common to all fields of science, manipulating the numbers to understand what is being observed. Similarities between fields indicate that similar techniques can be used, and yet individual fields like their own techniques. My project will look at bridging a gap between cosmology and seismology, by taking data analysis techniques from one field to the other. Specifically, I will use spherical wavelet analysis and Bayesian Hierarchical, common in dark matter studies, for seismic tomography studies. Going the other way, I will take transdimensional inversion techniques from seismic tomography and apply them to dark matter mapping. All this with perhaps some machine learning in between.