AI RESEARCH
Adversarial Effects on Expressibility and Trainability in Distributed Variational Quantum Algorithms
arXiv CS.LG
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ArXi:2605.03629v1 Announce Type: cross Distributed quantum algorithms offer a promising pathway to scale variational quantum algorithms beyond the constraints of noisy intermediate-scale quantum hardware. However, existing approaches implicitly assume a trusted entanglement-sharing layer across quantum processors. We show that this assumption