Variational Quantum Circuits for Deep Reinforcement Learning

Understand

The state-of-the-art machine learning approaches are based on classical von Neumann computing architectures and have been widely used in many industrial and academic domains.

• With the recent development of quantum computing, researchers and tech-giants have attempted new quantum circuits for machine learning tasks.
• However, the existing quantum computing platforms are hard to simulate classical deep learning models or problems because of the intractability of deep quantum circuits.
• Thus, it is necessary to design feasible quantum algorithms for quantum machine learning for noisy intermediate scale quantum (NISQ) devices.