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20232025
most citedHybrid Quantum Vision Transformers for Event Classification in High Energy Physics

16 citations · 49 across the 9 of their papers we have counts for

collaborators

9 papers

cs.LG2025★ 3 cited

Prediction of Stocks Index Price using Quantum GANs

Sangram Deshpande, Gopal Ramesh Dahale, Sai Nandan Morapakula +1

This paper investigates the application of Quantum Generative Adversarial Networks (QGANs) for stock price prediction. Financial markets are inherently complex, marked by high vola…

physics.comp-ph2025

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…

quant-ph2024

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…

quant-ph2024★ 2 cited

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…

quant-ph2024★ 15 cited

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…

quant-ph2024★ 16 cited

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…

quant-ph2023

Quantum Simulations for Carbon Capture on Metal-Organic Frameworks

Gopal Ramesh Dahale

Direct air capture of Carbon Dioxide is a technical solution that does not rely on natural processes to capture CO2 from the atmosphere. In DAC, the filter material is designed to…

quant-ph2023★ 5 cited

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…

quant-ph2023★ 8 cited

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…