Notebook Archive
Powered by Wolfram Notebook Technology
Predicting the Electron Invariant Mass from the CERN Dielectron Collision Data
Shivam Sawarn
Author
Shivam Sawarn
Title
Predicting the Electron Invariant Mass from the CERN Dielectron Collision Data
Description
The project aims at exploring various features of the dielectron collision using rigorous data analysis tools. The dataset consisting of 100,000 dielectron events in the invariant mass range 2-110 GeV is also used to train the neural network. The neural network is used on test dataset to predict the invariant mass of the electron.
Category
Essays, Posts & Presentations
Keywords
Invariant mass, particle physics, Neural Network
URL
http://www.notebookarchive.org/2022-01-5kbhz3u/
DOI
https://notebookarchive.org/2022-01-5kbhz3u
Date Added
2022-01-12
Date Last Modified
2022-01-12
File Size
40.83 megabytes
Supplements
Rights
Redistribution rights reserved
Cite this as: Shivam Sawarn, "Predicting the Electron Invariant Mass from the CERN Dielectron Collision Data" from the Notebook Archive (2022), https://notebookarchive.org/2022-01-5kbhz3u
Download