2 papers
physics.ins-det2026
Real-Time Wiener Deconvolution for feature reconstruction in JUNO
L. Lastrucci, M. Grassi, A. Triossi +74
In particle physics, experiments generate substantial amounts of data that can be difficult to process without preliminary scaling. To avoid losing potentially crucial data, experi…
physics.data-an2025
Simulation-based inference for Precision Neutrino Physics through Neural Monte Carlo tuning
A. Gavrikov, A. Serafini, D. Dolzhikov +63
Precise modeling of detector energy response is crucial for next-generation neutrino experiments which present computational challenges due to lack of analytical likelihoods. We pr…