SciPost Submission Page

How to GAN Event Subtraction

by Anja Butter, Tilman Plehn, Ramon Winterhalder

Submission summary

As Contributors: Tilman Plehn · Ramon Winterhalder
Arxiv Link: https://arxiv.org/abs/1912.08824v2
Date submitted: 2020-01-31
Submitted by: Winterhalder, Ramon
Submitted to: SciPost Physics
Discipline: Physics
Subject area: High-Energy Physics - Phenomenology
Approach: Computational

Abstract

Subtracting and adding event samples are common problems in LHC simulations. We show how generative adversarial networks can produce new event samples with a phase space distribution corresponding to added or subtracted input samples. We illustrate some general features using toy samples and then show explicit examples of background and non-local collinear subtraction events in terms of unweighted 4-vector events. This event sample manipulation reflects the excellent interpolation properties of neural networks.

Current status:
Editor-in-charge assigned


Submission & Refereeing History

Submission 1912.08824v2 on 31 January 2020

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