DEAP (Dark Matter Experiment using Argon Pulse-shape) is a direct dark matter search experiment using liquid argon as target material. DEAP utilizes background discrimination based on the characteristic scintillation pulse-shape in argon. A first-generation detector (DEAP-1) with a 7 kg target mass operated at Queen's University to test the available pulse-shape discrimination at low recoil energies in liquid argon, and was moved to SNOLAB in October 2007 and ran into 2011. Discrimination of beta and gamma events from nuclear recoils in the energy region of interest (near 20 keV of electron energy) is required to be better than 1 in 10 to sufficiently suppress backgrounds in the DEAP-1 detector. DEAP-3600 with 3600 kg of active mass is planned for operation beginning in mid 2015, with sensitivity to WIMP-nucleon scattering cross-sections as low as 10 cm² at 100 GeV. A later ton-scale detector is planned.
DEAP is a four letter acronym, which may refer to:
- Dielectric elastomers (Dielectric Electro-active Polymers)
- Dark Matter Experiment using Argon Pulse-shape discrimination
- Distributed Evolutionary Algorithms in Python
Distributed Evolutionary Algorithms in Python (DEAP) is an evolutionary computation framework for rapid prototyping and testing of ideas . It incorporates the data structures and tools required to implement most common evolutionary computation techniques such as genetic algorithm, genetic programming, evolution strategies, particle swarm optimization, differential evolution and estimation of distribution algorithm. It is developed at Université Laval since 2009.