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.
Mostquantumstatesaretooentangledtobeusefulascomputational resources.Physical Review Letters, 102(19), May 2009
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Random states from symplectic and orthogonal unitaries show exponentially large strong state complexity and near-orthogonality, with average-case hardness for learning circuits from these groups.
PINNs combined with Magnus expansion learn scheduling functions and adiabatic gauge potentials that yield higher normalized QFI than Euler-Lagrange baselines in nearest-neighbor, dipolar, and trapped-ion spin models up to six qubits.
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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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On the Complexity of Quantum States and Circuits from the Orthogonal and Symplectic Groups
Random states from symplectic and orthogonal unitaries show exponentially large strong state complexity and near-orthogonality, with average-case hardness for learning circuits from these groups.
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Physics-Informed Neural Networks for Maximizing Quantum Fisher Information in Time-Dependent Many-Body Systems
PINNs combined with Magnus expansion learn scheduling functions and adiabatic gauge potentials that yield higher normalized QFI than Euler-Lagrange baselines in nearest-neighbor, dipolar, and trapped-ion spin models up to six qubits.