ComsicAnalysis

ROOT-based analysis to study cosmic muons.

MC

A through-going cosmic muon sample is stored at /eos/experiment/wcte/MC_Production/v1.4.1/cosmics/. The production and analysis environment can be accessed by

/eos/experiment/wcte/MC_Production/ContainerImage/run_container.sh /eos/experiment/wcte/MC_Production/ContainerImage/softwarecontainer_workshop.sif

fiTQun reconstruction is run on this sample, and the output is stored in /eos/experiment/wcte/MC_Production/v1.4.1/cosmics/fiTQun/.

AnalyzeCosmicsMC.c

To select muons that enter through the top cap and exit through the bottom cap, create a set of plots in fig/ to study cut values on number of PMT hits and charge ratios in different sections (top cap, barrel, bottom cap).

root -l -b -q AnalyzeCosmicsMC.c

Then we derive a set of selection cuts:

• number of PMT hits > 1000
• Top/Total charge < 0.07
• 0.38 < Barrel/Total charge < 0.6
• 0.38 < Bottom/Total charge < 0.6

To further improve selection purity, the fiTQun reconstructed vertex and direction are extrapolated to find the muon entrance and exit positions at the tank surface. Then we only keep muons with:

• reconstructed entrance point on the top cap
• reconstructed exit point on the top cap

After the selection, 26% of all the muons remain. The selection efficiency and purity of top-down events are 85% and 93% respectively. Meanwhile over 99% of the selected events are with truth cos(zenith_angle)>0.7.

convert_to_h5.py

Convert wcsim and fiTQun root files into a single h5 for ML studies. The h5 file contains the following arrays:

• vertex: truth vertex (nevents,3)=shape, outside the tank
• direction: truth direction (nevents,3)
• entrance_pos: truth entrance point (nevents,3)
• exit_pos: truth exit point (nevents,3)
• is_top_down: truth top-down flag (nevents)
• momentum: truth momentum at vertex (nevents)
• pmtQ: total charge per PMT (nevents,npmts)
• pmtT: first hit time per PMT (nevents,npmts)
• fq_entrance_pos: fiTQun reconstructed entrance point (nevents,3)
• fq_exit_pos: fiTQun reconstructed exit point (nevents,3)
• fq_direction: fiTQun reconstructed direction (nevents,3)
• fq_momentum: fiTQun reconstructed momentum (nevents)
• pass_selection: pass selection flag (nevents)

To load the arrays,

import h5py
import torch

with h5py.File('wcte_cosmics_mc.h5','r') as f:
    entrance_pos = torch.as_tensor(f['entrance_pos'][:]) # shape=[nevents,3]
    exit_pos = torch.as_tensor(f['exit_pos'][:]) # [nevents,3]
    is_top_down = torch.as_tensor(f['is_top_down'][:]) # [nevents]
    pmtQ = torch.as_tensor(f['pmtQ'][:]) # [nevents,npmts]
    # etc.

Data