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Design and development of a data acquisition software pipeline for superconducting tunnel junction sensors in the BeEST and SALER experiments, The
Waters, Benjamin D.
Waters, Benjamin D.
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2024
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Expanding the frontiers of nuclear and subatomic physics research demands highly specialized data acquisition systems that can handle the complexities of modern quantum sensing technologies. This thesis details the creation of a dedicated data acquisition software pipeline tailored to the unique requirements of superconducting tunnel junction (STJ) sensors in the BeEST and SALER experiments. Central to this system is SALERScope, a versatile, multi-threaded C backend that interfaces with MPX-32d digitizers developed by XIA LLC. SALERScope, in conjunction with a high-performance Python API, provides researchers with the tools to quickly build custom interfaces and automate procedures, enabling flexible and efficient experimentation with STJ arrays. This hybrid architecture seamlessly integrates Python’s intuitive control with C’s speed and stability, coordinating high-throughput data collection while managing complex functionalities like automated STJ bias adjustments, peak tracking, spectrum generation, and preliminary analysis. Serving as a powerful alternative to XIA native software, ProSpect, the SALERScope platform overcomes limitations in handling STJ-specific data acquisition and control needs, offering superior flexibility and operational reliability. Paired with a Python-based graphical user interface, the software provides immediate diagnostic feedback and long-term data acquisition capabilities, making it a robust, adaptable platform for STJ applications. This system achieves new levels of automation, data accuracy, and user-friendliness, paving the way for expanded experimental capabilities and more efficient workflows in research with STJs.
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