asympTotic lIkelihood Tests for daRk mAtTer sEarch
Project description
# asymp*T*otic l*I*kelihood-based T*ests* for da*R*k m*A*t*T*er s*E*arch [<img src=”https://anaconda.org/conda-forge/titrate/badges/version.svg”>](https://anaconda.org/conda-forge/titrate) <img src=”https://anaconda.org/conda-forge/titrate/badges/platforms.svg”> [<img src=”https://badge.fury.io/py/titrate.svg”>](https://pypi.org/project/titrate/)
This package is based on the paper [Asymptotic formulae for likelihood-based tests of new physics](https://arxiv.org/abs/1007.1727).
(your daily dose of [meme](https://i.imgflip.com/7v739g.jpg))
## Why does this package exist?
Well, I’m currently doing my PhD on dark matter search with Imaging Air Cherenkov Telescopes (IACTs) and during my research, I looked into a good share of DM papers… Turns out none of the ones I’ve read really explained how they are calculating their upper limits and most of them lack a good explanation for upper limit vs dark matter mass plots.
So to understand what’s going on I went back in time…on arxiv. I thought, for sure the CERN people will know this stuff since calculating upper limits is daily business for them. I quickly found the paper mentioned above and it only took me three months to understand it.
(╯°□°)╯︵ ┻━┻
What have I learned? 1. Statistical tests are difficult to understand 2. The decentralized $chi^2$-distribution is the final boss 3. A lot of researchers use a test statistic that is physically not meaningfull (signal strength can be smaller than zero) 4. A lot of researchers calculate the median upper limits and bands for the expected signal by using a bunch of toy MCs, which is not necessarily needed if asymptotics are valid
## What does this package offer?
Adding Asimov datasets to gammapy :heavy_check_mark:
Adding test statistics to gammapy :heavy_check_mark:
Validation of test statistics :heavy_check_mark:
Calculation of ULs :heavy_check_mark:
Calculation of median ULs and bands with asymptotic formulae and asimov datasets (faster than toy MCs) :heavy_check_mark:
## Disclaimer This is not a finished version yet and can contain drastic changes
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