Welcome to Dark-Mark’s documentation!
Dark-MaRK (Dark Matter Rate Kalculator) is an open source Python 3 package created to generate bespoke predictions for direct detection dark matter experiments. Dark-MaRK allows users to generate these predictions using input galaxy simulations or arrays of velocities from a given model. The package allows for both the prediction, and constraining, of important input parameters as well as generating annual modulation predictions for these experiments.
Dark-MaRK defines a class, Nibbler, which contains all pertinent information regarding both the astrophysical inputs and detector characteristics like halo model, velocity distribution of dark matter, detector materials, dark matter mass and cross-section. Dark-MaRK uses Pynbody to sample dark matter properties from the input simulation, or accepts an analytical model of the distribution of dark matter, like the Maxwell Boltzmann speed distribution. It then calculates the differential spectral rate function, \(\frac{dR}{dE_R}\), which will demonstrate the expected event rate at a given day of the year, over a range of energies (either recoil or quenched, electron-equivalent). Users have the option to specify an energy window of interest, in order to generate annual modulation curve predictions.
Dark-MaRK can be installed via the source code here.