Spectram: A MATLAB® and GNU Octave Toolbox for Transition Model Guided Deconvolution of Dynamic Spectroscopic Data

• Main Author: Martin Rabe
• Format: Article
• Language: English
• Published: Ubiquity Press 2020-06-01
• Series: Journal of Open Research Software
• Subjects: singular value decomposition; matrix least squares; optical spectroscopy; ir-spectroscopy; uv/vis-spectroscopy; spectral deconvolution; multivariate data analysis
• Online Access: https://openresearchsoftware.metajnl.com/articles/323

Spectroscopic data, depending on an experimentally controllable variable, contains a wealth of information for researchers. However, complex spectra with overlapping peaks and multiple transitions complicate its straightforward interpretation and often the full contained information cannot be extracted. Here, the Spectram toolbox for MATLAB® and GNU Octave is described which was developed to analyse such data by a method based on singular value decomposition (SVD) and transition model coupled recombination. The method employs user-defined transition models, which depend on the control variable and are often known, or empirical descriptions of the transitions, which often can be guessed, to deconvolute such data. The outcome are the spectral components associated to the transitions and the model parameters. Both can be directly interpreted in terms of their physical meaning. Spectram can be applied to any desired spectroscopic technique and gives full freedom in the choice of the applied models, making it highly reusable.   Funding statement: Funding by the European Union’s Horizon 2020 research and innovation program under a Marie Skłodowska-Curie Grant (Agreement No. 705857) is acknowledged.