학술논문

CaloQVAE : Simulating high-energy particle-calorimeter interactions using hybrid quantum-classical generative models
Document Type
Working Paper
Source
Subject
High Energy Physics - Experiment
Computer Science - Machine Learning
Quantum Physics
81P68, 68T07, 81V99
Language
Abstract
The Large Hadron Collider's high luminosity era presents major computational challenges in the analysis of collision events. Large amounts of Monte Carlo (MC) simulation will be required to constrain the statistical uncertainties of the simulated datasets below these of the experimental data. Modelling of high-energy particles propagating through the calorimeter section of the detector is the most computationally intensive MC simulation task. We introduce a technique combining recent advancements in generative models and quantum annealing for fast and efficient simulation of high-energy particle-calorimeter interactions.
Comment: 6 pages, 3 figures