Numerical simulations show deep reinforcement learning generates squeezed cat states with 98% success rate on a measurement-based quantum processor, outperforming prior proposals.
Fault-tolerant measurement-based quantum computing with continuous-variable cluster states
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Machine learning for efficient generation of universal hybrid quantum computing resources
Numerical simulations show deep reinforcement learning generates squeezed cat states with 98% success rate on a measurement-based quantum processor, outperforming prior proposals.