5 papers · 1 filter
Practical framework for simulating permutation-equivariant quantum circuits
Su Yeon Chang, Martin Larocca, M. Cerezo
Understanding which subclasses of quantum circuits are efficiently classically simulable is fundamental to delineating the boundary between classical and quantum computation. In th…
Leveraging Symmetry Merging in Pauli Propagation
Yanting Teng, Su Yeon Chang, Manuel S. Rudolph +1
We introduce a symmetry-adapted framework for simulating quantum dynamics based on Pauli propagation. When a quantum circuit possesses a symmetry, many Pauli strings evolve redunda…
A Primer on Quantum Machine Learning
Su Yeon Chang, M. Cerezo
Quantum machine learning (QML) is a computational paradigm that seeks to apply quantum-mechanical resources to solve learning problems. As such, the goal of this framework is to le…
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…
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…