16 citations · 74 across the 13 of their papers we have counts for
14 papers
Symmetry-Preserving and Scalable Variational Circuits for the Lattice Gross-Neveu Model
Vivan Bhatt, Zhongtian Dong, Kyoungchul Kong +1
We study variational preparation of ground states and sector-resolved excited states in the -dimensional lattice Gross-Neveu model. We construct fixed circuits preserving ei…
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 generative adversarial networks for gluon initiated jets generation
Rey Guadarrama, Sergei Gleyzer, Mariia Baidachna +6
Quantum computing has the potential to offer significant advantages over classical computing, making it a promising avenue for exploring alternative methods in High Energy Physics…
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…
Analytical Insights on Hadronic Top Quark Polarimetry
Zhongtian Dong, Dorival Gonçalves, Kyoungchul Kong +2
Top quark polarization provides an important tool for studying its production mechanisms, spin correlations, top quark properties, and new physics searches. Unlike lighter quarks,…
Hadronic Top Quark Polarimetry with ParticleNet
Zhongtian Dong, Dorival Gonçalves, Kyoungchul Kong +2
Precision studies for top quark physics are a cornerstone of the Large Hadron Collider program. Polarization, probed through decay kinematics, provides a unique tool to scrutinize…
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…
Hybrid Quantum Vision Transformers for Event Classification in High Energy Physics
Eyup B. Unlu, Marçal Comajoan Cara, Gopal Ramesh Dahale +8
Models based on vision transformer architectures are considered state-of-the-art when it comes to image classification tasks. However, they require extensive computational resource…
is all you need: production of multiple semi-invisible resonances at hadron colliders
Zhongtian Dong, Kyoungchul Kong, Konstantin T. Matchev +1
The stransverse mass variable was originally proposed for the study of hadron collider events in which parent particles are produced and then decay semi-invisibly. H…
Equivariant Quantum Neural Networks: Benchmarking against Classical Neural Networks
Zhongtian Dong, Marçal Comajoan Cara, Gopal Ramesh Dahale +8
This paper presents a comprehensive comparative analysis of the performance of Equivariant Quantum Neural Networks (EQNN) and Quantum Neural Networks (QNN), juxtaposed against thei…
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…
Probing the CP Structure of the Top Quark Yukawa at the Future Muon Collider
Morgan E. Cassidy, Zhongtian Dong, Kyoungchul Kong +3
We study the top-Higgs coupling with a CP violating phase at a future multi-TeV muon collider. We focus on processes that are directly sensitive to the top quark Yukawa couplin…