Metadata-Version: 2.1
Name: lholipop
Version: 0.0.1
Summary: Python Boilerplate contains all the boilerplate you need to create a Python package.
Home-page: https://github.com/grburgess/lholipop
Author: J. Michael Burgess
Author-email: jburgess@mpe.mpg.de
License: GPL-2+
Project-URL: Bug Tracker, https://github.com/grburgess/lholipop/issues
Project-URL: Source Code, https://github.com/grburgess/lholipop
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Environment :: Console
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU General Public License v2 or later (GPLv2+)
Classifier: Operating System :: POSIX
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Topic :: Scientific/Engineering :: Physics
Description-Content-Type: text/markdown
License-File: LICENSE

# lholipop
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![alt text](https://raw.githubusercontent.com/grburgess/lholipop/master/docs/media/logo.png)

The **Lepto-Hadronic ObservationaL Intrinsic Population** synthesis framework allows for
multimessenger data from photons, neutrinos, and cosmic-rays to be generated by
folding the multi-species output of the [SOPRANO]() radiative code through
various instrument responses (e.g. photometric optical telescopes, x-ray
telescaopes, Fermi-LAT, IceCube). The intrinsic inputs for each observations are
sampled from an input cosmological population using [popsynth](), then fed to
SOPRANO resulting in fluxes of various species which can then be converted to
data via instrument responses and selection effects applied.

The modeling and reconstruction of both spectra and observations use a
combination of neural networks for speed. Datasets can be analyzed with 3ML to
produce reduced observables or combined in a high-level analysis to assess
association properties.

* Free software: GNU General Public License v3
* Documentation: https://lholipop.readthedocs.io.


## Features


* TODO

## Credits

