查看更多>>摘要：Locally repairable codes(LRCs),which can recover any symbol of a codeword by reading only a small number of other symbols,have been widely used in real-world distributed storage systems,such as Microsoft Azure Storage and Ceph Storage Cluster.Since binary linear LRCs can significantly reduce coding and decoding complexity,constructions of binary LRCs are of particular interest.The aim of this paper is to construct dimensional optimal binary LRCs with disjoint local repair groups.We introduce a method to connect intersection subspaces with binary LRCs and construct dimensional optimal binary linear LRCs with locality 2b(b≥3)and minimum distance d≥6 by employing intersection subspaces deduced from the direct sum.This method will sufficiently increase the number of possible repair groups of dimensional optimal LRCs,thus efficiently expanding the range of the construction parameters while keeping the largest code rates compared with all known binary linear LRCs with minimum distance d ≥ 6 and locality 2b.
查看更多>>摘要：The von Neumann bottleneck is a critical limitation in synaptic devices.Therefore,ar-tificial synaptic devices resembling biological neuromorphic synapses have been developed to overcome the von Neumann bottleneck.However,synaptic devices require voltages,which results in considerable energy consumption.Here,photonic synaptic devices with the vertical structure of indium tin oxide(ITO)/SnO2/Al2O3/CsBi3I10/Au are fabricated,which can work in the self-powered mode owing to the photovoltaic effect endowed by a vertical multilayer structure.Several fundamental synaptic functions,such as excitatory postsynaptic current,paired-pulse facilitation,short-term plasticity(STP),long-term plastic-ity(LTP),pulse-frequency-dependent plasticity,transition of STP to LTP,and the learning experience are emulated.Moreover,Morse-coded external light information is decoded by self-powered photonic synap-tic devices.The results indicate that self-powered photonic synaptic devices based on lead-free perovskites exhibit great potential for efficient neuromorphic computing and optical wireless communication.
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