一种迭代的动态稳定的数据展开方法
An iterative, dynamically stabilized method of data unfolding
摘要：
我们提出了一种新的迭代展开方法的实验数据，利用正则化函数。使用这个函数可以建立一个改进的归一化程序的蒙特卡罗光谱，无偏的数据中可能存在的新结构。我们能够展开，在一个动态稳定的方式，数据光谱，可以强烈地受到波动的背景减除，同时重建结构，最初没有模拟。当执行校正系统检测器效应的事件传输时，该方法还允许控制展开光谱的bin之间引入的相关性的量。
英文摘要：
We propose a new iterative unfolding method for experimental data, making use of a regularization function. The use of this function allows one to build an improved normalization procedure for Monte Carlo spectra, unbiased by the presence of possible new structures in data. We are able to unfold, in a dynamically stable way, data spectra which can be strongly affected by fluctuations in the background subtraction and simultaneously reconstruct structures which were not initially simulated. This method also allows one to control the amount of correlations introduced between the bins of the unfolded spectrum, when the transfers of events correcting the systematic detector effects are performed.
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。
