AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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An AI-assisted error-mitigation framework for quantum diffusion processes generated by sequential local weak measurements that provides a hybrid classical-quantum approach for approximating non-unitary dynamics and mitigating coherence loss.
The results show that operator-learning surrogates can enable inverse design in quantum systems whose Hilbert spaces are too large for conventional direct optimization and enable inverse design in quantum systems whose Hilbert spaces are too large for conventional direct optimization.
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