Introduction

This repository contains codes used to train 2D layered CNNs for performing signal-background classification on ATLAS RPV-SUSY data.

Tools for use for other datasets:

1. Data visulizaiton
2. Training CNN
3. Viewing model results: learning curves and predictions

Dataset

The dataset consists of simulation results for the ATLAS experiment. The signal is RPV-SUSY and background is QCD. For further information refer: https://arxiv.org/abs/1711.03573

Further details:

• To see plots of raw data, use the jupyter notebook data_visualization/1_view_data.ipynb
• The code containing codes to train data atlas_cnn/main_code/code/
• Code that trains a set of CNNs on ATLAS SUSY data The folder main_code/jpt_notebooks/ : contains Jupyter notebooks that can read models and plot roc curves.

For example, main_code/jpt_notebooks/2_cnn_yaml_config.ipynb has widgets to achieve this.

The notebook main_code/jpt_notebooks/2_cnn_yaml_config.ipynb performs full training and testing.