This dataset contains FTIR hyperspectral measurement and simulation data, as well as the correpsonding Python scripts, including scripts for producing the figures of the publication M. Marschall, A. Hornemann, G. Wübbeler, A. Hoehl, E. Rühl, B. Kästner, and C. Elster, "Compressed FTIR spectroscopy using low-rank matrix reconstruction," Opt. Express 28, 38762 (2020). DOI: 10.1364/OE.404959 Abstract: Fourier transform infrared (FTIR) spectroscopy is a powerful technique in analytical chemistry. Typically, spatially distributed spectra of the substance of interest are conducted simultaneously using FTIR spectrometers equipped with array detectors. Scanning-based methods such as near-field FTIR spectroscopy, on the other hand, are a promising alternative providing higher spatial resolution. However, serial recording severely limits their application due to the long acquisition times involved and the resulting stability issues. We demonstrate that it is possible to significantly reduce the measurement time of scanning methods by applying the mathematical technique of low-rank matrix reconstruction. Data from a previous pilot study of Leishmania strains are analyzed by randomly selecting 5% of the interferometer samples. The results obtained for bioanalytical fingerprinting using the proposed approach are shown to be essentially the same as those obtained from the full set of data. This finding can significantly foster the practical applicability of high-resolution serial scanning techniques in analytical chemistry and is also expected to improve other applications of FTIR spectroscopy and spectromicroscopy.

Funding: European Metrology Programme for Innovation and Research (18HLT06RaCHy); Deutsche Forschungsgemeinschaft (EL 492/1-1, RU 420/13-1).