6 papers · 1 filter
Quantum Simulation of the Real-time Dynamics in the multi-flavor Gross-Neveu Model at the utility scale using Superconducting Quantum Computers
Talal Ahmed Chowdhury, Seokwon Choi, Kyoungchul Kong +1
We present a scalable quantum simulation framework for real-time dynamics of the multi-flavor Gross-Neveu model in 1+1 dimensions. Using superconducting quantum processors at utili…
Quantum Diffusion Model for Quark and Gluon Jet Generation
Mariia Baidachna, Rey Guadarrama, Gopal Ramesh Dahale +6
Diffusion models have demonstrated remarkable success in image generation, but they are computationally intensive and time-consuming to train. In this paper, we introduce a novel d…
Lie-Equivariant Quantum Graph Neural Networks
Jogi Suda Neto, Roy T. Forestano, Sergei Gleyzer +3
Discovering new phenomena at the Large Hadron Collider (LHC) involves the identification of rare signals over conventional backgrounds. Thus binary classification tasks are ubiquit…
Quantum Attention for Vision Transformers in High Energy Physics
Alessandro Tesi, Gopal Ramesh Dahale, Sergei Gleyzer +4
We present a novel hybrid quantum-classical vision transformer architecture incorporating quantum orthogonal neural networks (QONNs) to enhance performance and computational effici…
A Comparison Between Invariant and Equivariant Classical and Quantum Graph Neural Networks
Roy T. Forestano, Marçal Comajoan Cara, Gopal Ramesh Dahale +8
Machine learning algorithms are heavily relied on to understand the vast amounts of data from high-energy particle collisions at the CERN Large Hadron Collider (LHC). The data from…
Quantum Vision Transformers for Quark-Gluon Classification
Marçal Comajoan Cara, Gopal Ramesh Dahale, Zhongtian Dong +8
We introduce a hybrid quantum-classical vision transformer architecture, notable for its integration of variational quantum circuits within both the attention mechanism and the mul…