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Deconvolution of Rutherford backscattering spectra: An inverse problem

机译:卢瑟福背向散射光谱的反卷积:一个反问题

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摘要

We review the problems associated with resolution correction and discuss some of the most promising procedures to solve them. We select four methods to deconvolute heavy particle backscattering spectra: (i) parametrization of the theoretical function, (ii) using histograms with variable bin width, (iii) modified Land-weber iterations, and (iv) using mollifiers. To judge the quality of the methods, we treat simulated backscattering spectra as obtained in Rutherford backscattering measurements with solid-state detectors. Our results are as follows: When a priori information on the shape of the spectra is available, parametrization of the problem is superior to all other methods. When information on high-frequency components of the spectrum (e.g., on sharp edges) is of primary interest, the use of histograms with variable-bin width might provide good results. In all other cases, the choice of the best procedure depends on the specific problem and our ability to optimize the adjustable parameter of the specific method.
机译:我们回顾了与分辨率校正相关的问题,并讨论了一些最有希望的解决方案。我们选择四种方法对重粒子反向散射光谱进行反卷积:(i)理论函数的参数化;(ii)使用具有可变bin宽度的直方图;(iii)改进的Land-weber迭代;以及(iv)使用缓和器。为了判断方法的质量,我们使用固态探测器处理在卢瑟福反向散射测量中获得的模拟反向散射光谱。我们的结果如下:当可以获得有关光谱形状的先验信息时,该问题的参数化优于所有其他方法。当主要关注频谱的高频分量信息(例如尖锐边缘)时,使用具有可变bin宽度的直方图可能会提供良好的结果。在所有其他情况下,最佳程序的选择取决于特定的问题以及我们优化特定方法的可调参数的能力。

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