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首页> 外文期刊>The journal of physical chemistry, A. Molecules, spectroscopy, kinetics, environment, & general theory >Model-free deconvolution of femtosecond kinetic data
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Model-free deconvolution of femtosecond kinetic data

机译：飞秒动力学数据的无模型反卷积

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摘要

Though shorter laser pulses can also be produced, pulses of the 100 fs range are typically used in femtosecond kinetic measurements, which are comparable to characteristic times of the studied processes, making detection of the kinetic response functions inevitably distorted by convolution with the pulses applied. A description of this convolution in terms of experiments and measurable signals is given, followed by a detailed discussion of a large number of available methods to solve the convolution equation to get the undistorted kinetic signal, without any presupposed kinetic or photophysical model of the underlying processes. A thorough numerical test of several deconvolution methods is described, and two iterative time-domain methods (Bayesian and Jansson deconvolution) along with two inverse filtering frequency-domain methods ( adaptive Wiener filtering and regularization) are suggested to use for the deconvolution of experimental femtosecond kinetic data sets. Adaptation of these methods to typical kinetic curve shapes is described in detail. We find that the modelfree deconvolution gives satisfactory results compared to the classical "reconvolution" method where the knowledge of the kinetic and photophysical mechanism is necessary to perform the deconvolution. In addition, a model-free deconvolution followed by a statistical inference of the parameters of a model function gives less biased results for the relevant parameters of the model than simple reconvolution. We have also analyzed real-life experimental data and found that the model-free deconvolution methods can be successfully used to get undistorted kinetic curves in that case as well. A graphical computer program to perform deconvolution via inverse filtering and additional noise filters is also provided as Supporting Information. Though deconvolution methods described here were optimized for femtosecond kinetic measurements, they can be used for any kind of convolved data where measured experimental shapes are similar.
机译：尽管也可以产生更短的激光脉冲，但是飞秒动力学测量中通常使用100 fs范围的脉冲，这与研究过程的特征时间相当，从而使动力学响应函数的检测不可避免地因所施加的脉冲的卷积而失真。从实验和可测量信号的角度对这种卷积进行了描述，然后详细讨论了许多解决卷积方程的方法，以得到未失真的动力学信号，而没有任何潜在的过程动力学或光物理模型。描述了几种解卷积方法的全面数值测试，并建议将两种迭代时域方法（贝叶斯和扬森解卷积）以及两种逆滤波频域方法（自适应维纳滤波和正则化）用于实验飞秒的解卷积动力学数据集。详细介绍了这些方法对典型动力学曲线形状的适应性。我们发现，与经典的“反卷积”方法相比，无模型的反卷积给出了令人满意的结果，在经典的“反卷积”方法中，必须具备动力学和光物理机制的知识才能执行反卷积。此外，与简单的反卷积相比，无模型的反卷积以及随后模型函数参数的统计推断得出的模型相关参数的偏差结果更少。我们还分析了现实生活中的实验数据，发现在这种情况下，无模型反褶积方法也可以成功用于获得未失真的动力学曲线。还通过支持滤波提供了通过逆滤波和附加噪声滤波器执行反卷积的图形计算机程序。尽管此处描述的解卷积方法已针对飞秒动力学测量进行了优化，但它们可用于测量实验形状相似的任何类型的卷积数据。

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