Reservoir Computing via Quantum Recurrent Neural Networks

Understand

Recent developments in quantum computing and machine learning have propelled the interdisciplinary study of quantum machine learning.

• Sequential modeling is an important task with high scientific and commercial value.
• Existing VQC or QNN-based methods require significant computational resources to perform the gradient-based optimization of a larger number of quantum circuit parameters.
• The major drawback is that such quantum gradient calculation requires a large amount of circuit evaluation, posing challenges in current near-term quantum hardware and simulation software.