PAS-QFL: Personalized Ansatz Selection for Quantum Federated Learning under Client Data Heterogeneity

arXiv:2608.14995v1 Announce Type: new Abstract: Quantum federated learning (QFL) lets multiple quantum clients collaboratively train quantum neural networks (QNNs) without sharing private local data. However, existing QFL methods commonly assume that all clients use the same ansatz, overlooking how