This code is intended to be used as per the procedure detailed in the article on arXiv.
The codes given are tested using Ubuntu 20.04 and the following softwares/packages are required:
Python 3.10+
NumPy 1.23+
SciPy 1.9+
Matplotplib 3.6+
LaTeX
Please maintain the same directory structure as in this repository. Ensure that a folder named data is in the same location as the scripts to save the simulation data in text files. Further, a directory named modes is needed within data to save simulation data of each mode of fluctuations.
Otherwise, please specify the location where you intend to save the data files wherever required in the scripts.
The script inf_dyn_background.py concerns simulation of background dynamics and quantum fluctuations under slow-roll approximation. The values of parameters Nt and v0 need to be fixed as per CMB observations.
Once these values are fixed, you can save the data in the file inf_bg_data.txt within the data folder (or any other specified filename and location).
The size of the file can be varied by adjusting the number of time steps for solving the ODEs.
For phase space analysis, it is recommended that you enter the initial conditions as described in the article and save the data for dynamics due to each set of initial conditions separately, labelling the text file with the value of xi used.
ex: inf_bg_data_5.0.txt
The different data files, corresponding to different sets of initial conditions can then be plotted in the same plot.
If only the plot of phase space behaviour is required, then the script inf_dyn_phase.py will generate it.
The script inf_dyn_MS_full.py concerns simulation of (background, along with ) scalar as well as tensor fluctuations. This makes use of the data from the background simulation to read values of initial conditions. There are no parameters whose values need to be fixed in this script, although the value of v0 can be set more precisely by matching the numerical results with CMB data. In this case, please make the corresponding change in the background script as well and save background data again.
The data for each mode can be saved in files named inf_MS_data_Nk.txt, where Nk corresponds to different modes.
If you plan to work with multiple models of inflation, it is recommended you create separate scripts for each model and specify the same in all filenames for convenience.
ex: quad_dyn_background.py or Starobinsky_MS_data_60.0.txt
This code is meant to be pedagogical in nature. In the process of fixing the various parameters, entering suitable initial conditions, etc the user will get a clear understanding of inflationary dynamics. We are developing a much more modular and direct PYTHON package akin to a black box which would allow users to compute specific aspects and predictions of inflationary models without having to traverse through all the dynamics manually. Updates regarding the same will be posted here as and when progress is made.
Thank you for taking interest in our work!
For any queries, please contact:
[email protected]
or
[email protected]
Numerical simulations of inflationary dynamics: slow roll and beyond © 2022 by Siddharth Bhatt, Swagat Mishra, Soumen Basak and Surya Sahoo is licensed under Creative Commons Attribution 4.0 International