Speaker
Yuxuan Wang
(California Institute of Technology)
Description
We present a data-driven charge–light matching technique for DUNE ND-LAr, in which an attention-based network trained on single-flash data predicts the light response of topologically clustered charge deposits and assigns each cluster a nanosecond-precision t_0 via likelihood alignment. Performance is demonstrated both in high-pile-up ND-LAr simulation and on real 2×2 Demonstrator data in the NuMI beam.
Author
Yuxuan Wang
(California Institute of Technology)