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We investigate the optimal distribution of quantum information over multipartite systems in asymmetric settings. We introduce cloning transformations that take $N$ identical replicas of a pure state in any dimension as input, and yield a collection of clones with non-identical fidelities. As an example, if the clones are partitioned into a set of $M_A$ clones with fidelity $F^A$ and another set of $M_B$ clones with fidelity $F^B$, the trade-off between these fidelities is analyzed, and particular cases of optimal $N to M_A+M_B$ cloning machines are exhibited. We also present an optimal $1 to 1+1+1$ cloning machine, which is the first known example of a tripartite fully asymmetric cloner. Finally, it is shown how these cloning machines can be optically realized.
We study machines that take N identical replicas of a pure qudit state as input and output a set of M_A clones of a given fidelity and another set of $M_B$ clones of another fidelity. The trade-off between these two fidelities is investigated, and nu
The future of quantum communication relies on quantum networks composed by observers sharing multipartite quantum states. The certification of multipartite entanglement will be crucial to the usefulness of these networks. In many real situations it i
Quantum no-cloning, the impossibility of perfectly cloning an arbitrary unknown quantum state, is one of the most fundamental limitations due to the laws of quantum mechanics, which underpin the physical security of quantum key distribution. Quantum
We study the dynamical entanglement distribution in a multipartite system. The initial state is a maximally entangled two level atom with a single photon field. Next a sequence of atoms are sent, one at the time, and interact with the field. We show
We introduce a quantum cellular automaton that achieves approximate phase-covariant cloning of qubits. The automaton is optimized for 1-to-2N economical cloning. The use of the automaton for cloning allows us to exploit different foliations for improving the performance with given resources.