Speaker
Raymundo Ramos
(Korea Institute for Advanced Study)
Description
In this work, we attempt to classify regions in a multidimensional parameter space according to their importance during a simulation. Considering that the parameter space could be high dimensional and the simulated process could result in arbitrary shapes, we involve a neural network in the process of guessing such shapes without running the full simulation for every point. We illustrate the process with a few examples, including scattering processes with several outgoing particles and compare with other known techniques for Monte Carlo simulations.
Primary authors
Dr
Kayoung Ban
(Korea Institute for Advanced Study)
Prof.
Myeonghun Park
(Seoultech)
Raymundo Ramos
(Korea Institute for Advanced Study)
