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        "author": "Logan Morrison and Adam Coogan",
        "author_email": "loanmorr@ucsc.edu",
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        "description": "[![CircleCI](https://circleci.com/gh/LoganAMorrison/Hazma.svg?style=svg)](https://circleci.com/gh/LoganAMorrison/Hazma)\n[![Documentation Status](https://readthedocs.org/projects/hazma/badge/?version=latest)](https://hazma.readthedocs.io/en/latest/?badge=latest)\n[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3347114.svg)](https://doi.org/10.5281/zenodo.3347114)\n\nHazma is a tool for studying indirect detection of sub-GeV dark. Its main uses are:\n\n- Computing gamma-ray and electron/positron spectra from dark matter annihilations;\n- Setting limits on sub-GeV dark matter using existing gamma-ray data;\n- Determining the discovery reach of future gamma-ray detectors;\n- Deriving accurate CMB constraints.\n\nHazma comes with [several](https://hazma.readthedocs.io/en/latest/models.html) sub-GeV dark matter models, for which it provides functions to compute dark matter annihilation cross sections and mediator decay widths. A variety of low-level tools are provided to make it straightforward to [define new models](https://hazma.readthedocs.io/en/latest/usage.html#user-defined-models).\n\n## Installation\n\nHazma can be installed from PyPI using:\n\n    pip install hazma\n\nAlternatively, you can download Hazma directly from this page, navigate to the package directory using the command line and run\n\n    pip install .\n\nor\n\n    python setup.py install\n\nSince Hazma utilizes C to rapidly compute gamma ray, electron and positron spectra, you will need to have the cython package installed.\n\nAnother way to run Hazma is by using docker. If you have docker installed on your machine, clone the Hazma repository and in the Hazma directory, run:\n\n    docker build --rm -t jupyter/hazma .\n\nThis will build the docker image called `jupyter/hazma`. Then to start a jupyter notebook, run:\n\n    docker run -it -p 8888:8888 -v /path/to/hazma/tutorials:/home/jovyan/work --rm --name jupyter jupyter/hazma\n\nThis will start a jupyter kernel.\n\n## Other information\n\nIf you use Hazma in your own research, please cite [our paper](https://arxiv.org/abs/1907.11846):\n```\n@article{Coogan:2019qpu,\n      author         = \"Coogan, Adam and Morrison, Logan and Profumo, Stefano\",\n      title          = \"{Hazma: A Python Toolkit for Studying Indirect Detection\n                        of Sub-GeV Dark Matter}\",\n      year           = \"2019\",\n      eprint         = \"1907.11846\",\n      archivePrefix  = \"arXiv\",\n      primaryClass   = \"hep-ph\"\n}\n```\n\nLogo design: David Reiman and Adam Coogan; icon from Freepik from [flaticon.com](https://www.flaticon.com/).\n\n\n",
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