用于超高能中微子探测的不断发展的微电子纳
Evolving Antennas for Ultra-High Energy Neutrino Detection
摘要：
进化算法从生物学中借用了变异和选择的概念，以进化出已知问题的优化解决方案。GENETIS合作正在开发遗传算法，用于设计对超高能中微子感应无线电脉冲比当前设计更敏感的天线。这次调查有三个方面。第一种是进化简单的线天线来测试概念和不同的算法。第二，优化天线响应模式演变为一个给定的阵列几何形状。最后，天线本身是用中微子灵敏度作为适应性的衡量标准来进化的。这是通过将XFdtd时域有限差分模拟程序与中微子实验相结合来实现的。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
