arXiv cs.AI
· Papers
DreamQAS: Learning a Decision-Useful World Model for VQE-Efficient Quantum Architecture Search
arXiv:2607.29491v1 Announce Type: cross Abstract: Reinforcement-learning-based quantum architecture search (RL-QAS) repeatedly optimizes a variational quantum eigensolver (VQE) after extending a circuit, although circuit construction and action legality are deterministic and known. We introduce DreamQAS, a model-based