An SDP-based framework computes optimal quantum cloning maps via Choi isomorphism, certifies optimality with duality, and extracts Kraus operators for universal, phase-covariant, asymmetric, and entanglement cloning including higher-order cases.
Cambridge University Press, Cambridge (2017)
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FlexLAM trains variable-length latent actions with nested dropout to match or exceed fixed-capacity LAMs at every token budget under scarce-label supervision without new architectures or losses.
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Semidefinite Programming for Optimal Quantum Cloning: A Computational Framework
An SDP-based framework computes optimal quantum cloning maps via Choi isomorphism, certifies optimality with duality, and extracts Kraus operators for universal, phase-covariant, asymmetric, and entanglement cloning including higher-order cases.
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FlexLAM: Resolving the Bottleneck Trade-off in Latent Action Learning
FlexLAM trains variable-length latent actions with nested dropout to match or exceed fixed-capacity LAMs at every token budget under scarce-label supervision without new architectures or losses.