稀疏谱信号发现的贝叶斯分析
Signal discovery in sparse spectra: a Bayesian analysis
摘要：
贝叶斯分析的概率信号的存在下的背景，并提出了标准，声称证据，或发现的信号。该方法是通用的，特别适用于稀疏填充的光谱。描述了用于评估实验灵敏度的Monte Carlo技术。作为一个例子，本文方法被用来计算GERDA实验对无中微子双β衰变的灵敏度。
英文摘要：
A Bayesian analysis of the probability of a signal in the presence of background is developed, and criteria are proposed for claiming evidence for, or the discovery of a signal. The method is general and in particular applicable to sparsely populated spectra. Monte Carlo techniques to evaluate the sensitivity of an experiment are described. As an example, the method is used to calculate the sensitivity of the GERDA experiment to neutrinoless double beta decay.
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。
