Hybrid Quantum Cycle Generative Adversarial Network for Small Molecule Generation

Hybrid Quantum Cycle Generative Adversarial Network for Small Molecule Generation

The drug design process currently requires considerable time and resources to develop each new compound that enters the market. This work develops an application of hybrid quantum generative models based on the integration of parameterized quantum circuits into known molecular generative adversarial...

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Bibliographic Details
Main Authors: Matvei Anoshin, Asel Sagingalieva, Christopher Mansell, Dmitry Zhiganov, Vishal Shete, Markus Pflitsch, Alexey Melnikov
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Transactions on Quantum Engineering
Subjects:
Drug design
hybrid quantum neural network (HQNN)
quantum generative adversarial network (GAN)
quantum machine learning (QML)
variational quantum circuit (VQC)
Online Access:https://ieeexplore.ieee.org/document/10556803/
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