This project focuses on the analysis of data from the phase-stabilized fiber optic network for high-precision frequency dissemination. This network was established in the SNSF project F-5117.30110 and is currently being operated as part of this small-scale project. In continuous operation, this network produces large amounts of data containing information about the interference processes that the optical fiber is exposed to. Initial explorations have shown that a detailed analysis of this data can be relevant for seismology as well as for the precise characterization of anthropogenic noise signals (e.g. rail and passenger transport traffic).
Accordingly, the two main project aims are:
- Analysis and classification of anthropogenic acoustic noise signals. This analysis is carried out as an interdisciplinary collaboration with the data science team. The large amount of data will be processed and analyzed using machine learning and neural network tools. The results of this analysis can help to identify ideal conditions for frequency transmission (e.g. time interval of particularly low anthropogenic influences). Furthermore, the large amount of continuous data provides an ideal toolbox for the data science team.
- Analysis and modeling of interference signals from specific seismic events (earthquakes). This part of the study is undertaken in collaboration with the Seismology and Wavephysics Group at ETH Zurich (Prof. A. Fichtner) and has already showed very promising results.
