Low-energy Sim/Reco Capability Xin Qian (BNL) Tingjun Yang (FNAL) 1

time Example with Single-Phase LArTPC 2 Number of ionized electrons Signal on Wire Plane Field Response Signal to be digitized by ADC Electronics Response High-level tracking … Noise Filter Charge Extraction Number of Ionized electrons

Challenges of Event Reconstruction in LArTPCs Event topology: – Tracks, showers, unknown vertex in LArTPCs – Simple tracks in collider’s gas TPCs 3 Wire vs. Pixel readout – Large LArTPCs has to use wire readout due to power consumption of electronics and costs – Puedo-3D detector

Review of Existing Approaches 2D matching  3D3D tomography 4

Strategy Comparison 2D Matching Start with 2D (time+wire x 3) 2D pattern recognition – Particle track/cluster information Matching 2D patterns into 3D objects – Time information (start/end of clusters) – Geometry information – Some charge information to remove ambiguities in matching 3D Tomography Start with 2D (wire+wire+wire at fixed time slice) 2D image reconstruction – Explicit Time + Geometry + Charge information – Some connectivity information can be used 3D image reconstruction – Straight forward 3D pattern recognition – Particle track/cluster information (tracks, showers) 5 Each approach uses the same set information in different order!

Partial Summary of Existing Work Line Cluster, Kalman Track Fitting, BlurredCluster, EM Shower, Cluster3D … Pandora: a pattern recognition package (currently 2D  3D), hit based Projection Matching Algorithm (PMA): a pattern recognition package (also 2D  3D) – Image based content recognition (shower vs. track) Wire-Cell Imaging: 3D imaging, 3D pattern recognition is in progress 6

Single-Phase TPC Signal Formation Induction wire is essential due to lack of amplification and limitations in power consumption Induction signal strongly depends on the local charge distribution 7 Number of ionized electrons Signal on Wire Plane Field Response Signal to be digitized by ADC Electronics Response Number of ionized electrons (Charge Extraction) v q : velocity E w : weighting field q: charge Shockley–Ramo theorem Example

8 cm Events from MicroBooNE 8 A B

Upcoming Improvements in Simulation Improved Noise Simulation Correct simulation of induction plane signals – Impact on the charge resolution from induction plane – Impact on 3D reconstruction  dQ/dx to dE/dx conversion – Also missed points in event clustering Light simulation? 9

About Reconstruction Energy: – Impact from electron lifetime determination and drift time – Uniformity of the detector response (electronics, induction field response) – Quenching correction Angle: – 3D determination of the angle is important – Important of not missing small dots Also match between charge and light PID? 10