Free open source software
As part of our ongoing activities, we are engaged in the development of software to analyze the data from our experiments. With mature THz-TDS setups from various manufacturers now offering sufficient stability, we are dedicating resources to developing tools specifically tailored for data analysis. We believe that the field has reached a stage where robust data analysis is essential for advancing into analytical fields, including precise spectroscopy for research and sensing applications.
Among the software tools we are developing are Correct@tds and Fit@tds:
Correct@TDS
Correct@tds is designed to denoise and analyze uncertainties in recorded THz Time Domain experiments. It estimates the covariance and precision matrices of time traces, providing a corrected estimator with reduced bias compared to simple averaging. Written in Python 3, it features a graphical interface and utilizes the NumPy, SciPy, and Scikit-learn libraries. While currently a private project on GitHub until the related paper is published, interested parties can contact us to test the code.
Fit@TDS
Fit@tds focuses on curve fitting of THz-TDS data to extract physical and spectroscopic parameters of samples. Given reference and sample time traces as input, it outputs parameters like frequency and damping rate of electronic or photonic oscillators. Versions released in 2018 and 2024 are publicly available on GitHub, with a third version in development to include uncertainties in retrieved parameters. This will soon become a public project, and interested parties can contact us to test the code.
Additionally, we are developing a data acquisition software specifically tailored for our Terasmart system from Menlo Systems, coupled with thermal or mechanical control systems. Feel free to reach out if you're interested in this aspect of our work. We're also open to collaboration on code or instruments like FTIR, so don't hesitate to contact us to explore potential partnerships.