Inferring physical properties of stellar collapse by third-generation gravitational-wave detectors

Chaitanya Afle^1,2, Duncan A. Brown^{1, 2}

¹Department of Physics, Syracuse University, Syracuse, NY 13244, USA

²Kavli Institute for Theoretical Physics, University of California, Santa Barbara, CA 93106, USA

Introduction

This notebook is a companion to Afle & Brown (2020) posted at arxiv:2010.00719. In the paper we investigate the ability of Advanced LIGO, Cosmic Explorer 1, and Cosmic Explorer 2 to measure the physical propeties of core-collapse supernovae through its gravitational-wave radiation. This notebook demonstrates the three salient results of this work:

1. Principal components that form our waveform model. The principal components are stored in principal_components.hdf.

2. The map between the model parameters (principal components and their coefficients) and physical parameters (core rotation rate $\beta$ and postbounce oscillation frequency $f_{peak}$).

3. Extracting the posteriors of model parameters from posterior files and using the map to transform these posteriors of physical parameters.

License

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 United States License.

Runing this notebook in a Docker container

This notebook can be run from a PyCBC Docker container, or a machine with PyCBC installed. Instructions for downloading the docker container are available from the PyCBC home page. To start a container with instance of Jupyter notebook, run the commands

docker pull pycbc/pycbc-el7:v1.16.9
docker run -p 8888:8888 --name pycbc_notebook -it pycbc/pycbc-el7:v1.16.9 /bin/bash -l

Once the container has started, this git repository can be downloaded with the command:

git clone https://github.com/sugwg/sn-core-bounce-pe.git

The notebook server can be started inside the container with the command:

jupyter notebook --ip 0.0.0.0 --no-browser

You can then connect to the notebook server at the URL printed by jupyter. Navigate to the directory sn-core-bounce-pe in the cloned git repository and open data_release.ipynb, the notebook that demonstrates use of these reults.

Acknowledgements

The authors thank Adam Burrows, Daniel Finstad, and Chris Fryer for helpful discussions and the Kavli Institute for Theoretical Physics for hospitality.

Funding

The authors were supported by National Science Foundation awards PHY-1707954, PHY-1836702, and PHY-2011655. The authors thank the partial support from National Science Foundation award PHY-1748958. Computational work was supported by Syracuse University and National Science Foundation award OAC-1541396.

Authors contributions

Conceptualization, CA and DAB; Methodology, CA and DAB; Software: CA; Investigation: CA; Resources: DAB; Writing: CA and DAB; Visualization: CA and DAB; Supervision: DAB; Project Administration: DAB; Funding Acquisition: DAB.