Photonic reservoir computing is an emerging topic due to the possibility to realize very fast devices with minimal training effort. We will discuss the reservoir computing performance of memory cells with a focus on the impact of delay lines and the interplay between coupling topology and performance for various benchmark tasks. We will further show that additional delayed input can be beneficial for reservoir computing setups in general, as it provides an easy tuning parameter, which can improve the performance of a reservoir on a range of tasks.
Quantum memories are a key element for the realisation of quantum repeaters, essential for long-distance quantum communication. Especially for satellite-based quantum networks, alkali metal vapours constitute an excellent storage platform, as neither cryogenics, nor strong magnetic fields are required. We have realised a technologically simple, in principle satellite-suited quantum memory in Caesium vapor, based on electromagnetically induced transparency (EIT) on the Cs D1 line. We focus on the simultaneous optimization of end-to-end efficiency and signal-to-noise level in the memory, which will make our system suitable for many different applications. We have achieved light storage at the single-photon level with end-to-end efficiencies up to 12%, which correspond to internal memory efficiencies of up to 30%. Simultaneously we achieve a minimal noise level corresponding to µ_1=0.029 signal photons. Furthermore, we have determined the limiting noise source at this level to be four-wave mixing noise in the Lambda-system and present solutions to minimise this read-out noise.
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