Advanced Data Processing in Spectroscopy
Digital transformation is mainly leveraging "big data" for emergent pattern recongnition and "buried" information retrieval. Large data sets, however, cause a dramatic data deluge, which is difficult to handle with. In imaging and transient spectroscopy large data volumes are common. Thus, it is desirable to have smart collection methods to deal with fast undersampled processes, whose information is preserved and digitally retrieved.
Compressed Sensing for Operando XAFS
It is familiar the practice to compress digital files in formats such as ZIP, or JPG for images, or MP3 for audio. The process is done in a way that the original information is still accessible, though at reduced level of detail. While in non-compressed files that level of details contributes to the overall quality of the visual or auditive experience, it is redundant to recongnize the specific picture or sound. The signal is largerly oversampled with respect to the information retrieval. Compression methods thus "reduce it to the essential".
In scientific applications, such as analytical spectroscopy it is not really the beauty of the signal that is in first-place important, rather the information within. We deploy digital strategies to "efficient-ize" data collection as well as their processing in chemical analysis. Be it for chemical imaging of 3D hyperspectral mappings, or transient signals of a large number of states or compounds, the ability to focus on the least sufficient data set is extremely valuable in terms of information coverage as well as space/time resolution. The traditional Nyquist limit is beaten adopting newest methods of compressed sensing.
Ultra-High Resolution Mass Spectrometry
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