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20242026
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quant-ph2026

Physics inspired quantum algorithm for QCD splitting functions

Gabriel Rouxinol, Yacine Haddad, Cenk Tüysüz +2

We introduce a modular quantum circuit primitive to model entanglement dynamics in QCD parton splitting and use it as a composable building block for data-driven, physics-consisten…

quant-ph2025

Learning Reduced Representations for Quantum Classifiers

Patrick Odagiu, Vasilis Belis, Lennart Schulze +6

Data sets that are specified by a large number of features are currently outside the area of applicability for quantum machine learning algorithms. An immediate solution to this im…

quant-ph2025

Operational Framework for a Quantum Database

Carla Rieger, Michele Grossi, Gian Giacomo Guerreschi +2

Databases are an essential component of modern computing infrastructures and allow efficient manipulation of inherently structured data. The structure depends on the type and relat…

quant-ph2024

Guided Quantum Compression for High Dimensional Data Classification

Vasilis Belis, Patrick Odagiu, Michele Grossi +3

Quantum machine learning provides a fundamentally different approach to analyzing data. However, many interesting datasets are too complex for currently available quantum computers…

quant-ph2024

A Study on Quantum Graph Neural Networks Applied to Molecular Physics

Simone Piperno, Andrea Ceschini, Su Yeon Chang +3

This paper introduces a novel architecture for Quantum Graph Neural Networks, which is significantly different from previous approaches found in the literature. The proposed approa…

quant-ph2024

Latent Style-based Quantum GAN for high-quality Image Generation

Su Yeon Chang, Supanut Thanasilp, Bertrand Le Saux +2

Quantum generative modeling is among the promising candidates for achieving a practical advantage in data analysis. Nevertheless, one key challenge is to generate large-size images…