Quantum classical hybrid neural networks for continuous variable prediction

2022/12/08 by Prateek Jain, Jain, Prateek, Alberto García-García +1
Computer Science · #Computational Finance (q-fin.CP) #Computational Physics and Python Applications #FOS: Economics and business #FOS: Physical sciences #Neural Networks and Reservoir Computing #Quantum Computing Algorithms and Architecture #Quantum Physics (quant-ph)

paper · pdf · doi:10.48550/arxiv.2212.04209

openalex publication_date 2022/12/08 · openalex created_date 2022/12/26 · openalex updated_date 2026/07/28

Abstract

Within this decade, quantum computers are predicted to outperform conventional computers in terms of processing power and have a disruptive effect on a variety of business sectors. It is predicted that the financial sector would be one of the first to benefit from quantum computing both in the short and long terms. In this research work we use Hybrid Quantum Neural networks to present a quantum machine learning approach for Continuous variable prediction.

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