Density matrix emulation of quantum recurrent neural networks for multivariate time series prediction

Density matrix emulation of quantum recurrent neural networks for multivariate time series prediction

Quantum recurrent neural networks (QRNNs) are robust candidates for modelling and predicting future values in multivariate time series. However, the effective implementation of some QRNN models is limited by the need for mid-circuit measurements. Those increase the requirements for quantum hardware,...

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Bibliographic Details
Main Authors: J D Viqueira, D Faílde, M M Juane, A Gómez, D Mera
Format: Article
Language:English
Published: IOP Publishing 2025-01-01
Series:Machine Learning: Science and Technology
Subjects:
quantum computing
machine learning
time series prediction
Online Access:https://doi.org/10.1088/2632-2153/ad9431
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https://doi.org/10.1088/2632-2153/ad9431

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