CLEAN中事件重构的空间方法
Spatial methods for event reconstruction in CLEAN
摘要：
在CLEAN（Cryogenic Low Energy Astrophysics with Noble Gases）中，如果能够以高精度确定电离辐射事件的位置，则背景鉴别是可能的。CLEAN是一种建议的中微子和暗物质探测器。我们模拟电离辐射事件，产生多个闪烁光子内充满液体氖的球形检测体积。我们估计一个特定的电离辐射事件的径向位置的基础上观察到的计数数据对应于该事件。计数数据由安装在检测体积的球形边界处的检测器收集。我们忽略吸收，但考虑瑞利散射。为了解释闪烁光的波长漂移，我们假设光子在探测器处被吸收并重新发射。在这里，我们开发了空间极大似然方法的事件重建，并研究其性能在计算机模拟实验。我们还研究了一种基于观测计数数据质心的方法。我们根据训练数据校准我们的估计。
英文摘要：
In CLEAN (Cryogenic Low Energy Astrophysics with Noble gases), a proposed neutrino and dark matter detector, background discrimination is possible if one can determine the location of an ionizing radiation event with high accuracy. We simulate ionizing radiation events that produce multiple scintillation photons within a spherical detection volume filled with liquid neon. We estimate the radial location of a particular ionizing radiation event based on the observed count data corresponding to that event. The count data are collected by detectors mounted at the spherical boundary of the detection volume. We neglect absorption, but account for Rayleigh scattering. To account for wavelength-shifting of the scintillation light, we assume that photons are absorbed and re-emitted at the detectors. Here, we develop spatial Maximum Likelihood methods for event reconstruction, and study their performance in computer simulation experiments. We also study a method based on the centroid of the observed count data. We calibrate our estimates based on training data.
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