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Quantum metrology exploits entangled states of particles to improve sensing precision beyond the limit achievable with uncorrelated particles. All previous methods required detection noise levels below this standard quantum limit to realize the benefits of the intrinsic sensitivity provided by these states. Remarkably, a recent proposal has shown that, in principle, such low-noise detection is not a necessary requirement. Here, we experimentally demonstrate a widely applicable method for entanglement-enhanced measurements without low-noise detection. Using an intermediate magnification step, we perform squeezed state metrology 8 dB below the standard quantum limit with a detection system that has a noise floor 10 dB above the standard quantum limit. Beyond its conceptual significance, this method eases implementation complexity and is expected to find application in next generation quantum sensors.
I give a scientific perspective, with a personal emphasis, on the seminal 1992 paper, The quantum-state diffusion model applied to open systems, by Gisin and Percival.
We demonstrate an experimental realization of remote state preparation via the quantum teleportation algorithm, using an entangled photon pair in the polarization degree of freedom as the quantum resource. The input state is encoded on the path of on
The conditions are investigated under which a row of increasing dominoes is able to keep tumbling over. The analysis is restricted to the simplest case of frictionless dominoes that only can topple not slide. The model is scale invariant, i.e. domino
Multi-photon quantum interference is the underlying principle for optical quantum information processing protocols. Indistinguishability is the key to quantum interference. Therefore, the success of many protocols in optical quantum information proce
Quantum state tomography is a key process in most quantum experiments. In this work, we employ quantum machine learning for state tomography. Given an unknown quantum state, it can be learned by maximizing the fidelity between the output of a variati