Escaping Barren Plateaus With Negative Learning Rates Enables Variational Quantum Algorithms In Quantum Internet Of Things

Escaping Barren Plateaus With Negative Learning Rates Enables Variational Quantum Algorithms In Quantum Internet Of Things

Researchers have developed a new optimisation technique for quantum computing that incorporates negative learning rates, enabling more reliable training of quantum algorithms on resource-limited devices and overcoming a key obstacle to deploying quantum-enhanced intelligence in everyday applications.