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Due to physical orientations and birefringence effects, practical quantum information protocols utilizing optical polarization need to handle misalignment between preparation and measurement reference frames. For any such capable system, an important question is how many resources -- e.g., measured single photons -- are needed to reliably achieve alignment precision sufficient for the desired quantum protocol. Here we study the performance of a polarization-frame alignment scheme used in prior laboratory and field quantum key distribution (QKD) experiments by performing Monte Carlo numerical simulations. The scheme utilizes, to the extent possible, the same single-photon-level signals and measurements as for the QKD protocol being supported. Even with detector noise and imperfect sources, our analysis shows that only a small fraction of resources from the overall signal -- a few hundred photon detections, in total -- are required for good performance, restoring the state to better than 99% of its original quality.
We propose a method for reconfiguring a relay node for polarization encoded quantum key distribution (QKD) networks. The relay can be switched between trusted and untrusted modes to adapt to different network conditions, relay distances, and security
The primary resource for quantum computation is Hilbert-space dimension. Whereas Hilbert space itself is an abstract construction, the number of dimensions available to a system is a physical quantity that requires physical resources. Avoiding a dema
We propose and experimentally demonstrate a plug-and-play, practical, and enabling method allowing to synchronize the building blocks of a quantum network in an all-optical way. Our scheme relies on mature and reliable classical telecommunication and
In this work we consider practical implementations of Kitaevs algorithm for quantum phase estimation. We analyze the use of phase shifts that simplify the estimation of successive bits in the estimation of unknown phase $varphi$. By using increasingl
Application of the adiabatic model of quantum computation requires efficient encoding of the solution to computational problems into the lowest eigenstate of a Hamiltonian that supports universal adiabatic quantum computation. Experimental systems ar