Speaker
Description
Beam loss events at SuperKEKB represent a major operational challenge, threatening both the Belle II detector and accelerator components while significantly impacting data-taking rates, with diamond doses reaching several thousand mrad per event.
The current abort system relies on loss monitors positioned outside the beam pipe and at the interaction point. However, for Sudden Beam Loss (SBL) events, where significant current can be lost within a single turn, faster abort triggers are required.
We show that bunch oscillation recorders (BOR), which provide turn-by-turn position data at ~200 MHz, contain precursor signals that can be utilized for early warning.
We develop and compare three classes of anomaly detection algorithms on BOR data: sliding-window variance, Kalman filters, and a multivariate DeepLSTM forecasting model. We demonstrate that all three methods can successfully identify oscillation precursors ahead of conventional loss monitors, with the multivariate DeepLSTM offering the best performance. These findings establish the feasibility of BOR-based early warning triggers for beam loss mitigation at SuperKEKB.