Evolving Antennas for Ultra-High Energy Neutrino Detection
This work addresses the need for better detection hardware in neutrino physics, but it appears incremental as it applies existing evolutionary methods to a specific domain.
The GENETIS collaboration tackled the problem of designing more sensitive antennas for ultra-high energy neutrino detection by using genetic algorithms to evolve antenna designs, achieving improved sensitivity compared to current designs.
Evolutionary algorithms borrow from biology the concepts of mutation and selection in order to evolve optimized solutions to known problems. The GENETIS collaboration is developing genetic algorithms for designing antennas that are more sensitive to ultra-high energy neutrino induced radio pulses than current designs. There are three aspects of this investigation. The first is to evolve simple wire antennas to test the concept and different algorithms. Second, optimized antenna response patterns are evolved for a given array geometry. Finally, antennas themselves are evolved using neutrino sensitivity as a measure of fitness. This is achieved by integrating the XFdtd finite-difference time-domain modeling program with simulations of neutrino experiments.