3 papers
quant-ph2026
Large Language Models Can Help Mitigate Barren Plateaus in Quantum Neural Networks
Jun Zhuang, Chaowen Guan
In the era of noisy intermediate-scale quantum (NISQ) computing, Quantum Neural Networks (QNNs) have emerged as a promising approach for various applications, yet their training is…
quant-ph2025
Enhancing the Trainability of Variational Quantum Circuits with Regularization Strategies
Jun Zhuang, Jack Cunningham, Chaowen Guan
In the era of noisy intermediate-scale quantum (NISQ), variational quantum circuits (VQCs) have been widely applied in various domains, demonstrating the potential advantages of qu…
quant-ph2025
Investigating and Mitigating Barren Plateaus in Variational Quantum Circuits: A Survey
Jack Cunningham, Jun Zhuang
In recent years, variational quantum circuits (VQCs) have been widely explored to advance quantum circuits against classic models on various domains, such as quantum chemistry and…