Adaptive Directional Gradients for Parameterised Quantum Circuits

arXiv·low signal

Training parameterised quantum circuits on quantum hardware is bottlenecked by the measurement cost of gradient estimation, which scales poorly. This paper proposes adaptive directional gradients to cut that measurement overhead during training. It is a quantum-ML training advance with little direct relevance to today's classical AI-agent builders, noted here for completeness.