TPC simulation and 3D imaging at SBND using Wire-Cell

The SBND experiment is a 112 ton active volume liquid argon time projection chamber (LArTPC), located about ~110m from the BNB neutrino source at Fermilab. One of its main purposes is to allow precision measurements of short-baseline neutrino oscillations. Neutrino events in SBND will produce both ionization electrons and light, which will be detected at the Anode Plane Assemblies (APAs) and the Photon Detection System (PDS), respectively. Wire-Cell is a standalone software package for TPC simulation, ionization signal processing, and 3D event reconstruction for LArTPC experiments, enabling high performance physics analyses in those experiments. Its kernel simulates a realistic 2D long-range induction of ionization electrons in the central +-10 nearby wires. One of the implementations of Wire-Cell is the use of a Deep Neural Network (DNN) to identify ROI regions in the induction/collection wires, as a complement of its traditional ROI algorithm. Regarding high-level reconstruction, one of Wire-Cell algorithms is 3D-imaging. The creation of a 3D image of ionization electrons is the first step in the high-level reconstruction chain. In this talk I will present the implementation and optimization of the Wire-Cell DNN-ROI and 3D-imaging algorithms in SBND using commissioning data, which will be collected by the first half of 2024.