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# Statement of need
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Advancements in experimental physics and device manufacturing depend on the precise characterisation of material properties under extreme physical conditions (low temperature and high magnetic/electric fields). For automating experiments, researchers have to choose between expensive proprietary graphical programming environments or developing a custom measurement script from scratch.
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While powerful ecosystem libraries such as PyVISA [@grecco2023pyvisa] and PyMeasure [@pymeasure_2025] provide the foundational drivers for instrumental communication, they are fundamentally software libraries that require the user to write and maintain code, which creates a barrier to entry for researchers requiring direct data acquisition without the overhead of developing and maintaining a custom codebase.
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While powerful ecosystem libraries such as PyVISA [@grecco2023pyvisa] and PyMeasure [@pymeasure_2025] provide the foundational drivers for instrument communication, they are fundamentally software libraries that require the user to write and maintain code, which creates a barrier to entry for researchers requiring direct data acquisition without the overhead of developing and maintaining a custom codebase.
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PICA addresses this gap by functioning as a turnkey application rather than as a library. It offers a "ready-to-run" graphical interface that abstracts the underlying control logic, allowing experimentalists to focus on data acquisition without needing to develop custom software scripts for the supported hardware configurations.
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PICA’s architecture is designed to be highly configurable, enabling users to readily adapt it to their specific requirements and to implement user‑defined protocols in addition to the standard measurement protocols already provided. It eliminates the need for reconfiguring the measurement setup to achieve comprehensive characterisation, enabling continuous operation across the full range from Delta-mode low-resistance measurements (the current reversal technique effectively removes constant offsets and improves the signal-to-noise ratio) to high-impedance electrometric measurements, ranging from low-noise superconductors to high-band gap insulators (covering 24 orders of magnitude in resistance) using a single unified framework.

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