Using evolutionary algorithms to design antennas with greater sensitivity to ultrahigh energy neutrinos

Created by W.Langdon from gp-bibliography.bib Revision:1.8276

@Article{Rolla:2023:PhyRevD,

• author = "J. Rolla and A. Machtay and A. Patton and W. Banzhaf and A. Connolly and R. Debolt and L. Deer and E. Fahimi and E. Ferstle and P. Kuzma and C. Pfendner and B. Sipe and K. Staats and S. A. Wissel",
• title = "Using evolutionary algorithms to design antennas with greater sensitivity to ultrahigh energy neutrinos",
• journal = "Physical Review D",
• year = "2023",
• volume = "108",
• issue = "10",
• pages = "102002",
• month = nov,
• keywords = "genetic algorithms, genetic programming, Radio, microwave, sub-mm astronomy, Neutrino detection",
• ISSN = "2470-0010",
• publisher = "American Physical Society",
• URL = "http://hdl.handle.net/10150/671538",
• URL = "https://repository.arizona.edu/handle/10150/671538",
• URL = "https://repository.arizona.edu/bitstream/handle/10150/671538/PhysRevD.108.102002.pdf",
• URL = "https://link.aps.org/doi/10.1103/PhysRevD.108.102002",
• DOI = "doi:10.1103/PhysRevD.108.102002",
• size = "17 page",
• abstract = "The Genetically Evolved NEutrino Telescopes for Improved Sensitivity project seeks to optimize detectors in physics for science outcomes in high-dimensional parameter spaces. In this project, we designed an antenna using a genetic algorithm with a science outcome directly as the sole figure of merit. This paper presents initial results on the improvement of an antenna design for in-ice neutrino detectors using the current Askaryan Radio Array (ARA) experiment as a baseline. By optimizing for the effective volume using the evolved antenna design in ARA, we improve upon ARAs simulated sensitivity to ultrahigh energy neutrinos by 11 percent, despite using limited parameters in this initial investigation. Future improvements will continue to increase the computational efficiency of the genetic algorithm and the complexity and fitness of the antenna designs. This work lays the foundation for continued research and development of methods to increase the sensitivity of detectors in physics and other fields in parameter spaces of high dimensionality.",
• collaboration = "GENETIS Collaboration",
• notes = "Also known as \cite{PhysRevD.108.102002}",

}

Genetic Programming entries for Julie A Rolla Alexander Machtay Alexander Patton Wolfgang Banzhaf Amy Connolly Ryan Debolt Leo Deer Ethan Fahimi Eliot Ferstle P Kuzma Carl Pfendner Ben Sipe Kai Staats Stephanie Wissel

Citations