论文标题
超高能中微子检测的不断发展的天线
Evolving Antennas for Ultra-High Energy Neutrino Detection
论文作者
论文摘要
进化算法从生物学中借用突变和选择的概念，以进化针对已知问题的优化解决方案。 Genetis协作正在开发遗传算法，用于设计对超高能量中微子诱导的无线电脉冲比当前设计更敏感的天线。这项调查有三个方面。首先是进化简单的线天线以测试概念和不同的算法。其次，针对给定阵列几何形状进化了优化的天线响应模式。最后，使用中微子敏感性作为适应性的量度来进化天线本身。这是通过将XFDTD有限差异时间域建模程序与中微子实验的模拟整合在一起来实现的。
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.
