8 research outputs found

    Entanglement breaking channels and entanglement sudden death

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    The occurrence of entanglement sudden death in the evolution of a bipartite system depends on both the initial state and the channel responsible for the evolution. An extreme case is that of entanglement braking channels, which are channels that acting on only one of the subsystems drives them to full disentanglement regardless of the initial state. In general, one can find certain combinations of initial states and channels acting on one or both subsystems that can result in entanglement sudden death or not. Neither the channel nor the initial state, but their combination, is responsible for this effect, but their combination. In this work we show that, in all cases, when entanglement sudden death occurs, the evolution can be mapped to that of an effective entanglement breaking channel on a modified initial state. Our results allow to anticipate which states will suffer entanglement sudden death or not for a given evolution. An experiment with polarization entangled photons demonstrates the utility of this result in a variety of cases

    Resilience of hybrid optical angular momentum qubits to turbulence

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    Recent schemes to encode quantum information into the total angular momentum of light, defining rotation-invariant hybrid qubits composed of the polarization and orbital angular momentum degrees of freedom, present interesting applications for quantum information technology. However, there remains the question as to how detrimental effects such as random spatial perturbations affect these encodings. Here, we demonstrate that alignment-free quantum communication through a turbulent channel based on hybrid qubits can be achieved with unit transmission fidelity. In our experiment, alignment-free qubits are produced with q-plates and sent through a homemade turbulence chamber. The decoding procedure, also realized with q-plates, relies on both degrees of freedom and renders an intrinsic error-filtering mechanism that maps errors into losses
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