Evolving Antennas for Ultra-High Energy Neutrino Detection

Evolutionary algorithms borrow from biology the concepts of mutation and selection in order to evolve optimized solutions to known problems. We are developing genetic algorithms to design antennas that are more sensitive to UHE neutrino-induced radio pulses than current designs. We are taking two parallel approaches. The first is to evolve antenna response patterns that give the highest effective volume for detecting neutrinos for a given array geometry. The second is to evolve the antennas themselves using neutrino sensitivity as a measure of fitness. The projects integrate the XFdtd finite-difference time domain modeling program with simulations of neutrino experiments to assign a fitness score for each evolved solution, based on neutrino sensitivities. We will summarize initial results.