2020-07-31 –, Green Track
I'll talk about my experience developing the Inflation.jl package in my research as a graduate student, and what I think Julia can do for computational and theoretical cosmology.
The talk should appeal to anyone interested in Julia's differential equations and parameter estimation suites, symbolic computation, package development, or the early universe.
The early universe is a terribly violent place, but within the first 10<sup>-30</sup> seconds, cosmologists believe a process called inflation smoothed out the primordial universe into something that could expand and cool into our universe today.
Simulating this process is a necessity for understanding the early universe, but in practice this means symbolically generating and then solving a challenging set of PDEs, and comparing their solutions to cosmological data. When the model includes unknown parameters, some parameter estimation is needed as well. I'll describe how Julia is the right tool for every step in this process.
Inflation.jl generates the symbolic PDEs with a symbolic tensor manipulation engine built on SymPy.jl and sympy.tensor.tensor. Then DifferentialEquations.jl and related parameter estimation routines solve the PDEs, having little trouble even with high-dimensional inflation models.
The presentation will be organized into the lessons I learned while developing the package, and what I think we can all learn and apply to our own scientific computing projects, in cosmology and other fields.
Physics PhD student at University of Texas at Austin