dmdd 0.2

A python package that enables simple simulation and Bayesian posterior analysis of nuclear-recoil data from dark matter direct detection experiments for a wide variety of theories of dark matter-nucleon interactions.

dmdd has the following features:

• Calculation of the nuclear-recoil rates for various non-standard momentum-, velocity-, and spin-dependent scattering models.

• Calculation of the appropriate nuclear response functions triggered by the chosen scattering model.

• Inclusion of natural abundances of isotopes for a variety of target elements: Xe, Ge, Ar, F, I, Na.

• Simple simulation of data (where data is a list of nuclear recoil energies, including Poisson noise) under different models.

• Bayesian analysis (parameter estimation and model selection) of data using MultiNest.

All rate and response functions directly implement the calculations of Anand et al. (2013) and Fitzpatrick et al. (2013) (for non-relativistic operators, in rate_genNR and rate_NR), and Gresham & Zurek (2014) (for UV-motivated scattering models in rate_UV). Simulations follow the prescription from Gluscevic & Peter (2014) and Gluscevic et al. (2015).

pip install dmdd

git clone https://github.com/veragluscevic/dmdd.git
cd dmdd
python setup.py install