Welcome to panco2’s documentation!

panco2 is a Python library dedicated to extracting measurements of the pressure profile of the hot gas inside galaxy clusters from millimeter-wave observations. The extraction is performed using forward modeling the millimeter-wave signal of clusters and MCMC sampling of a posterior distribution for the parameters given the input data. Many characteristic features of millimeter-wave observations can be taken into account, such as filtering (both through PSF smearing and transfer functions), point source contamination, and correlated noise. panco2 is further described in [2].

Installation

To install, clone the repository and use pip:

git clone git@github.com:fkeruzore/panco2.git
cd panco2
pip install .

Contents:

• panco2’s methodology
  • Forward modeling of thermal SZ signal
  • Pressure profile fitting
• Examples
  • Running example: Pressure profile of a mock cluster from a mock NIKA2 map
  • Computing and using noise covariance matrices
  • Simulating data to check analysis options
  • Running example: Marginalizing over point source contamination or masking it
• API
  • panco2.panco2
  • panco2.results
  • panco2.noise_covariance
  • panco2.masks
• References

Indices and tables

• Index

• Module Index

• Search Page

License & Attribution

Copyright 2022 Florian Kéruzoré and contributors. panco2 is free software made available under the MIT License. For details see the LICENSE.md file in the git repository. If you use panco2 in your research, please cite [2]:

@article{keruzore_panco2_2023,
  title = {Panco2: A {{Python}} Library to Measure Intracluster Medium Pressure Profiles from {{Sunyaev-Zeldovich}} Observations},
  shorttitle = {panco2},
  author = {K{\'e}ruzor{\'e}, Florian and Mayet, Fr{\'e}d{\'e}ric and Artis, Emmanuel and {Mac{\'i}as-P{\'e}rez}, Juan-Francisco and {Mu{\~n}oz-Echeverr{\'i}a}, Miren and Perotto, Laurence and Ruppin, Florian},
  year = {2023},
  month = mar,
  journal = {The Open Journal of Astrophysics},
  volume = {6},
  publisher = {{Maynooth Academic Publishing}},
  doi = {10.21105/astro.2212.01439},
  urldate = {2023-03-14},
  langid = {english},
}