# Inflation.jl

A Julia package for numerical evaluation of cosmic inflation models. Perturbations are evolved with the transport method. It supports symbolic calculation of the equations of motion, and remains efficient at a high number of fields, even with non-canonical kinetic terms. If you use this in a publication, please cite via the Zenodo link.

`Inflation.jl`

automatically applies the horizon-crossing approximation, if the potential is detected to be sum-separable. Support is planned for automatic application of other approximations when they are valid as well.

Watch the talk given about this package at JuliaCon 2020: https://www.youtube.com/watch?v=gvUZiPPB3nI

## Installation

For now, Inflation.jl is an unregistered Julia package. It can be installed with

```
julia> import Pkg
julia> Pkg.add("https://github.com/rjrosati/Inflation.jl")
```

## an example

```
using Inflation
using SymPy
# this is a quadratic inflation model with 10 fields and randomly selected masses
# set the field space dimension
d = 10
# set the model parameters, and their values
params = [symbols("m$i") for i in 1:d]
pvalues = rand(d)*1e-9
function G(Phi,p)
d = length(Phi)
g = Matrix{eltype(Phi)}(I,d,d)
return g
end
function V(Phi,p)
m = p
return sum([ m[i]*Phi[i]^2)/2 for i in 1:d])
end
# set the initial conditions
Pi0 = zeros(d) # zero initial velocity
# pick a position randomly over the sphere, with radius to give ~N0 e-folds
N0 = 100
Phi0 = randn(d)
Phi0 ./= norm(Phi0)
Phi0 .*= sqrt(4*N0)
# symbolically construct the equations of motion
# because this potential is sum-separable, the horizon-crossing approximation will automatically be calculated
funcs = inflation_setup(d,V,G,params)
# solve the background equations of motion
sol = background_evolve(Phi0,Pi0,pvalues,funcs,verbose=true)
# solve the 2-pt correlation function equations of motion
# by default, use 7 k-values centered at a pivot scale of 0.002 Mpc^-1
tsol = transport_perturbations(sol,pvalues,funcs,verbose=true)
println(tsol)
```

see the `examples`

directory for more complicated potentials and metrics, how to scan parameter space, evaluate several simulations in parallel, output and analyze data.

At the moment, `Inflation.jl`

can only solve the 2-pt correlation function equations of motion. Solving for higher-point correlation functions is possible with PyTransport/CppTransport.