将背景估计中的统计不确定性纳入信号上限
Incorporation of the statistical uncertainty in the background estimate into the upper limit on the signal
摘要：
我们提出了一个程序，用于计算上限的信号事件的数量，其中包括泊松不确定性的背景下，估计从控制区域的一个或两个维度。对于少量的信号事件，得到的上限是更严格的比提取不包括泊松不确定性。这种趋势持续到背景事件的数量与信号相当。当背景事件的数量与信号相当或大于信号时，所获得的上限比不包括泊松不确定性提取的上限不那么严格。因此，将泊松不确定性纳入上限是很重要的;否则所获得的上限可能过于严格。
英文摘要：
We present a procedure for calculating an upper limit on the number of signal events which incorporates the Poisson uncertainty in the background, estimated from control regions of one or two dimensions. For small number of signal events, the upper limit obtained is more stringent than that extracted without including the Poisson uncertainty. This trend continues until the number of background events is comparable with the signal. When the number of background events is comparable or larger than the signal, the upper limit obtained is less stringent than that extracted without including the Poisson uncertainty. It is therefore important to incorporate the Poisson uncertainty into the upper limit; otherwise the upper limit obtained could be too stringent.
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。
