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We report on a flexible platform for molecular sensing in the terahertz range. Merging the well-established technologies of near-infrared electro-optic modulation and photomixing realizes a spectrally adaptable terahertz source, which is combined with a new generation of compact gas cells, so-called substrate-integrated hollow waveguides (iHWGs). iHWGs have been developed in the mid-infrared and provide flexibility in the design of the optical absorption path. Here, we demonstrate its suitability for the terahertz domain by presenting its low propagation losses and by measuring rotational transitions of nitrious oxide (N2O). A fast frequency sideband modulation technique results in substantially reduced measurement times and increased accuracy compared to a standard wavelength tuning method.

Artificial neural networks are capable of fitting highly non-linear and complex systems. Such complicated systems can be found everywhere in nature, including the non-linear interaction between optical modes in laser resonators. In this work, we demonstrate artificial neural networks trained to model these complex interactions in the cavity of a Quantum Cascade Random Laser. The neural networks are able to predict modulation schemes for desired laser spectra in real-time. This radically novel approach makes it possible to adapt spectra to individual requirements without the need for lengthy and costly simulation and fabrication iterations.