Quantifying entanglement for unknown quantum states via artificial neural networks.

Quantum entanglement acts as a crucial part in quantum computation and quantum information, hence quantifying unknown entanglement is an important task. Due to the fact that the amount of entanglement cannot be achieved directly by measuring any physical observables, it remains an open problem to quantify entanglement experimentally. In this work, we provide an effective way to quantify entanglement for the unknown quantum states via artificial neural networks.

Optical scheme for simulating post-quantum nonlocality distillation.

An optical scheme for simulating nonlocality distillation is proposed in post-quantum regime. The nonlocal boxes are simulated by measurements on appropriately pre- and post-selected polarization entangled photon pairs, i.e.

Optical simulation of a Popescu-Rohrlich Box.

It is well known that the fair-sampling loophole in Bell test opened by the selection of the state to be measured can lead to post-quantum correlations. In this paper, we make the selection of the results after measurement, which opens the fair- sampling loophole too, and thus can lead to post-quantum correlations. This kind of result-selection loophole can be realized by pre- and post-selection processes within the "two-state vector formalism", and a physical simulation of Popescu-Rohrlich (PR) box is designed in linear optical system.