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The paper introduces mrfmsim, an open-source Python package designed for simulating magnetic resonance force microscopy (MRFM) experiments. It addresses the challenges of simulating continuously evolving experiments in research settings by using directed acyclic graphs (DAGs) and a plugin system for modularity and extensibility. The authors demonstrate that mrfmsim provides accurate results and accelerates development compared to ad-hoc simulation approaches, highlighting the importance of a well-designed simulation platform for MRFM.
Stop rewriting your simulation code every time your MRFM experiment changes: mrfmsim offers a modular and extensible platform that adapts to evolving research needs.
We present mrfmsim, an open-source package that facilitates the design, simulation, and signal validation of magnetic resonance force microscopy experiments. The mrfmsim package uses directed acyclic graphs (DAGs) to model experiments and employs a plugin system that enables adding custom experiments and functionalities. Unlike common DAG-powered workflow packages, mrfmsim allows flexible customization of experiments post-definition, such as optimized looping, without requiring rewriting the internal model. In this paper, we highlight the challenges of building simulation packages for experiments that undergo continuous development in a graduate research setting. We demonstrate how a one-off approach to experimental simulation yielded erroneous results, and how the modularity, extendibility, and readability of the new platform enabled correct results and a significantly accelerated development cycle.
