TY - DATA T1 - Data and software underlying the publication "Laser-cut Patterned, Micrometer-thin Diamond Membranes with Coherent Color Centers for Open Microcavities" PY - 2025/06/27 AU - Yanik Herrmann AU - Julia M. Brevoord AU - Julius Fischer AU - Stijn Scheijen AU - Colin Sauerzapf AU - Nina Codreanu AU - Leonardo G. C. Wienhoven AU - Yuran M. Q. van der Graaf AU - Cornelis F. J. Wolfs AU - Régis Méjard UR - DO - 10.4121/a8e32e27-5a91-4a4a-abfc-e5bd884317ae.v1 KW - Diamond KW - Fiber-based Cavity KW - Optical Cavity KW - Nitrogen-Vacancy Center KW - Tin-Vacancy Center KW - Quantum Optics KW - Laser-cutting KW - Quantum Networks KW - Scanning Cavity Microscopy KW - Nanofabrication N2 -
The data and software underlying the research article "Laser-cut Patterned, Micrometer-thin Diamond Membranes with Coherent Color Centers for Open Microcavities". In this physics paper, we present a new method to pattern diamond microdevices utilizing laser cutting, followed by reactive ion etching to thin them down. We compare this fabrication method to an established method using e-beam lithography and a silicon nitride hard mask. Devices obtained from both fabrication methods are characterized by scanning cavity microscopy, showing that high cavity finesse can be reached. In addition, we perform low-temperature spectroscopy to show that the devices contain optically coherent Tin- and Nitrogen-Vacancy centers. The measurements are performed in quantum optics laboratories.
The dataset contains the measured data and the Python code to analyse and reproduce the figures shown in the paper. Most measurements are conducted with the Python 3 framework Quantum Measurement Infrastructure (QMI) and the data acquisition framework Quantify. The measured data is stored in individual HDF5 files, with a unique timestamp and identifier. Analysed data is stored in HDF5 and JSON files named processed dataset or quantities of interest. The white light interferometer data is stored in text files.
Please see the README.md file for instructions on how to run the Python code to reproduce the figures.
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