化学计量学
先验与后验
飞秒
计算机科学
参数统计
时间分辨光谱学
吸收(声学)
参数化模型
领域(数学)
瞬态(计算机编程)
光谱学
实验数据
生物系统
概率逻辑
统计模型
人工智能
机器学习
光学
物理
激光器
数学
统计
操作系统
哲学
认识论
量子力学
纯数学
生物
作者
Cyril Ruckebusch,Michel Sliwa,Pascal Pernot,Anna de Juan,Romà Tauler
标识
DOI:10.1016/j.jphotochemrev.2011.10.002
摘要
Nowadays, time-resolved spectroscopy data can be routinely and accurately collected in UV–vis femtosecond transient absorption spectroscopy. However, the data analysis strategy and the postulation of a physically valid model for this kind of measurements may be tackled with many different approaches ranging from pure soft-modeling (model-free) to hard-modeling, where the elaboration of a parametric spectro-temporal model may be required. This paper reviews methods that are used in practice for the analysis of femtosecond transient absorption spectroscopy data. Model-based methods, common in photochemistry, are revisited, and soft-modeling methods, which originate from the chemometrics field and that recently disseminated in the photo(bio)chemistry literature, are presented. These soft-modeling methods are designed to suit the intrinsic nature of the multivariate (or multi-way) measurement. Soft-modeling tools do not require a priori physical or mechanistic models to provide a decomposition of the data on the time and wavelength dimensions, the only requirement being that these two (or more) dimensions are separable. Additionally, Bayesian data analysis, which provides a probabilistic framework for data analysis, is considered in detail, since it allows uncertainty quantification and validation of the model selection step.
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