Speaker
Description
UCN data is often analyzed by empirical models and fit parameters. This limits interpretability of measurements, projecting away information of well understood particle level dynamics. We present a physical inference on UCN storage and accumulation data from the SuperSUN source at the ILL, allowing for reconstruction of in-situ total energy spectra and associated physics. The model will be presented alongside data, and possibilities to further the understanding of downstream experiments in the context of nEDM systematics for PanEDM will be discussed.
In parallel, Monte-Carlo simulations are used to produce robust training datasets to link simulation inputs, i.e. physical parameters, to observed data using new simulation-based inference (SBI) techniques. The methods apply in principle to much more complex experiments, such as nEDM measurements or future in-situ experiments. We present the status of simulations of time-of-flight experiments, which utilize the analytical methods alongside SBI to model SuperSUN.