Numerical simulations show deep reinforcement learning generates squeezed cat states with 98% success rate on a measurement-based quantum processor, outperforming prior proposals.
Robust preparation of wigner-negative states with optimized snap-displacement sequences
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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.