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arXiv 1209.2227hep-phhep-ex
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利用多堆中微子确定质量等级

Mass Hierarchy Determination Using Neutrinos from Multiple Reactors

Emilio Ciuffoli, Jarah Evslin, Xinmin Zhang

摘要:

本文报道了中基线反应堆中微子实验的蒙特卡罗模拟结果。大亚湾和岭澳反应堆的1 km间距导致的基线差异降低了低能1-3振荡的振幅,降低了对中微子质量等级的敏感性。垂直的探测器位置消除了这种影响。我们模拟了大亚湾/岭澳反应堆垂直的几座山下的实验,特别考虑了台山和阳江反应堆的背景。一般来说,在距离大亚湾44.5公里的白云嶂1000米的山体下面可以最可靠地确定层次结构。如果一些计划中的反应堆没有建成,那么在47-51公里基线处的700米高的山脉附近会获得一点优势。忽略它们的低开销负担,东坑附近的山丘将是最佳位置。我们使用加权傅立叶变换,以避免虚假的依赖于高能量中微子光谱,并发现神经网络可以提取的数量,确定的层次略优于传统的RL + PV。

英文摘要:

We report the results of Monte Carlo simulations of a medium baseline reactor neutrino experiment. The difference in baselines resulting from the 1 km separations of Daya Bay and Ling Ao reactors reduces the amplitudes of 1-3 oscillations at low energies, decreasing the sensitivity to the neutrino mass hierarchy. A perpendicular detector location eliminates this effect. We simulate experiments under several mountains perpendicular to the Daya Bay/Ling Ao reactors, considering in particular the background from the TaiShan and YangJiang reactor complexes. In general the hierarchy can be determined most reliably underneath the 1000 meter mountain BaiYunZhang, which is 44.5 km from Daya Bay. If some planned reactors are not built then nearby 700 meter mountains at 47-51 km baselines gain a small advantage. Neglecting their low overhead burdens, hills near DongKeng would be the optimal locations. We use a weighted Fourier transform to avoid a spurious dependence on the high energy neutrino spectrum and find that a neural network can extract quantities which determine the hierarchy marginally better than the traditional RL + PV.

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。

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