Code for project on Particle Track Reconstruction - trackml dataset

The repository has code for project done under Dr. Kinjal Banerjee

This is all sharad's work, I have just used his repo. and parts of it to improve my own implemenations. Current Progress:

• Initial data exploration
• Clustering
• Neural Network - FC: 86%
• Random Forest: 93%
• Gradient Boosted Classifiers: 96%
• XGBoost Classifier, 500 trees and (max_depth = 25), Trained on 1 event: 98.1%
• Exploration of different Neural Network architectures

Particle Physics and Quantum Mechanics:

• Chapter 1 Griffiths
• Chapter 2 Griffiths
• Introductory Quantum Mechanics

Current Approach:

1. Classification of 2 hits as promising or not
2. Classification of a third promising hit
3. Reconstruction of the trajectory based on the three hits classified as promising

• The current models are trained 1st step(i.e., classification of 2 hits as promising or not), since the same model can be extended in the second step
• In the final step, the hits that are closest to the reconstructed trajectory will be selected