About

NEST (Noble Element Simulation Technique) is an unprecedentedly accurate and comprehensive simulation of the scintillation, ionization, and electroluminescence processes in noble elements. It has many applications, including direct dark matter detectors, double beta decay searches, PET scans, and general radiation detection technology, and has been validated against a long list of past experimental results.

The latest NEST release (Version 2.0.0) works for xenon in all three phases, and will soon include models for other noble elements such as argon. NEST is a standalone C++ package which generates a compiled library for linking (useful for external applications) as well as tools for quick calculations. Furthermore, users can now easily create their own custom detectors for generating fast detector simulations, taking into account various effects such as detector efficiencies, operational parameters (e.g. temperature, pressure), position dependence, optics, and electric field variations.

Unlike previous versions, this release does not require GEANT4 or ROOT libraries. However, it does allow for optional GEANT4 integration (for use of the NEST calculator in full detector simulations) and optional compilation of useful ROOT tools. Details regarding prerequisites, installation, and GEANT4 integration are included in the package documentation.

While the existing GEANT4 simulation package can perform simplistic calculations of scintillation in noble elements, NEST provides a far more robust calculation of the scintillation and ionization yields using empirical models which take into account the energy and field dependence, as well as the intrinsic fluctuations and recombination physics.

NEST is of particular use for low-energy nuclear recoils like you'd see from dark matter. Currently, GEANT4 makes no effort to implement the proper scintillation reduction for nuclear recoils vis-a-vis electron recoils in a noble element like xenon, and NEST fixes that.

Please download it and test it for yourself! See if it can predict/postdict your very own experimental data.