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Towards multi-exponential analysis in optically stimulated luminescence

机译:走向光激发发光的多指数分析

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Optically stimulated luminescence (OSL) data from quartz can follow different mathematical forms depending on the stimulation mode. These data can be described in terms of different multi-exponential models and can be numerically fitted using several well-known methods. Here we make a comparative analysis of the performance and stability of two models, the decay and peak form, and we consider different transformation methods for obtaining the peak form. For the numerical computations we use a nonlinear least squares (NLS) method and a method based on a first-kind Fredholm integral equation (FIE). Our analysis uses artificial data with three components (seven parameters including the background) and ten different levels of background, both the signal and the background contain Poisson distributed noise. Parameters derived using both models are acceptable (statistically consistent and on an average within ~1% of the expected value) and no obvious preference is observed for any particular model, although there may be a suggestion that peak-form data show a smaller mean bias. This conclusion seems to be independent of the type of peak transformations investigated here. Furthermore, it is found that transformation of OSL decay data to a peak form gives better results than direct measurement of peak-form data by, for example, varying the stimulation light intensity. The comparison of the two numerical methods suggests that the NLS method performs somewhat better than the FIE method; however, the latter has the advantage that it does not require the user's judgement on the number of components in the data. Testing of the NLS procedure on a measured quartz time-resolved OSL signal transformed into peak form yielded reliable parameter estimates even when the signal intensity was deliberately reduced by a factor of 16.
机译:来自石英的光激发发光(OSL)数据可以遵循不同的数学形式,具体取决于激发模式。这些数据可以用不同的多指数模型来描述,并且可以使用几种众所周知的方法进行数值拟合。在这里,我们对衰减和峰形这两个模型的性能和稳定性进行了比较分析,并考虑了获得峰形的不同转换方法。对于数值计算,我们使用非线性最小二乘法(NLS)和基于第一类Fredholm积分方程(FIE)的方法。我们的分析使用了具有三个成分(包括背景的七个参数)和十个不同背景水平的人工数据,信号和背景均包含泊松分布噪声。使用这两个模型得出的参数都是可以接受的(统计上一致,并且平均在预期值的大约1%之内),并且对任何特定模型都没有观察到明显的偏爱,尽管可能暗示峰形数据显示出较小的平均偏差。该结论似乎与此处研究的峰转换类型无关。此外,发现通过例如改变刺激光强度,将OSL衰减数据转换成峰形比直接测量峰形数据提供更好的结果。两种数值方法的比较表明,NLS方法的性能优于FIE方法。但是,后者的优点是不需要用户对数据中的组件数量进行判断。即使将信号强度故意降低了16倍,对在转换为峰值形式的石英时间分辨OSL信号上进行的NLS程序测试也得出了可靠的参数估计值。

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