Creating a Particle Physics Simulation using AI
Advisor(s)
Dr. Rick Cavanaugh, Fermilab
Location
Room A113-1
Start Date
26-4-2019 11:05 AM
End Date
26-4-2019 11:20 AM
Abstract
For many years, the Monte Carlo simulation has been the prevalent method of measuring probabilities when it comes to the field of particle physics. While it has traditionally been built on the usage of regular probabilities and the fundamental practices of the standard model, there has been a push for an updated version of this simulation, and so this experiment aims to do so by building the Monte Carlo using AI to expedite the process. While this is the end goal, the first year was spent primarily in development of the neural network environment, and learning how to build such a network in Python. As such, the development of the neural network will continue into the next year, at which point results will be available for analysis.
Creating a Particle Physics Simulation using AI
Room A113-1
For many years, the Monte Carlo simulation has been the prevalent method of measuring probabilities when it comes to the field of particle physics. While it has traditionally been built on the usage of regular probabilities and the fundamental practices of the standard model, there has been a push for an updated version of this simulation, and so this experiment aims to do so by building the Monte Carlo using AI to expedite the process. While this is the end goal, the first year was spent primarily in development of the neural network environment, and learning how to build such a network in Python. As such, the development of the neural network will continue into the next year, at which point results will be available for analysis.