Evolving Antennas for Ultra-High Energy Neutrino Detection

@article{Rolla2021EvolvingAF,
  title={Evolving Antennas for Ultra-High Energy Neutrino Detection},
  author={Julie Rolla and A. Connolly and Kai Staats and Stephanie Wissel and Dean Y. Arakaki and Ian Best and Adam Blenk and B. A. Clark and Maximillian Clowdus and Suren Gourapura and Corey Harris and Hannah Hasan and Luke Letwin and David W. Liu and Carl Pfendner and Jordan Potter and Cade Sbrocco and Tom Sinha and Jacob Trevithick},
  journal={ArXiv},
  year={2021},
  volume={abs/2005.07772}
}
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… 

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