16 citations · 49 across the 9 of their papers we have counts for
7 papers · 1 filter
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…
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…
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…
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…
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…