arXiv (OAI Expanded)
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DreamQAS: Learning a Decision-Useful World Model for VQE-Efficient Quantum Architecture Search
Reinforcement-learning-based quantum architecture search (RL-QAS) repeatedly invokes a variational quantum eigensolver (VQE) after each gate addition even though circuit transitions and action legality are known. DreamQAS preserves these exact dynamics and learns only expensive post-VQE feedback thr
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