Efficient Ansatz

Efficient ansatz design is crucial for the success of variational quantum algorithms (VQAs), which aim to leverage noisy intermediate-scale quantum (NISQ) devices for practical applications. Current research focuses on developing hardware-efficient ansatz architectures, such as those exploiting symmetries or employing native-pulse control, and on mitigating training challenges like barren plateaus through innovative cost functions and evolutionary optimization strategies. These advancements improve the accuracy, scalability, and noise resilience of VQAs, paving the way for their wider adoption in fields like quantum chemistry and machine learning.