1,105 research outputs found
Assisted Entanglement Distillation
Motivated by the problem of designing quantum repeaters, we study
entanglement distillation between two parties, Alice and Bob, starting from a
mixed state and with the help of "repeater" stations. To treat the case of a
single repeater, we extend the notion of entanglement of assistance to
arbitrary mixed tripartite states and exhibit a protocol, based on a random
coding strategy, for extracting pure entanglement. The rates achievable by this
protocol formally resemble those achievable if the repeater station could merge
its state to one of Alice and Bob even when such merging is impossible. This
rate is provably better than the hashing bound for sufficiently pure tripartite
states. We also compare our assisted distillation protocol to a hierarchical
strategy consisting of entanglement distillation followed by entanglement
swapping. We demonstrate by the use of a simple example that our random
measurement strategy outperforms hierarchical distillation strategies when the
individual helper stations' states fail to individually factorize into portions
associated specifically with Alice and Bob. Finally, we use these results to
find achievable rates for the more general scenario, where many spatially
separated repeaters help two recipients distill entanglement.Comment: 25 pages, 4 figure
Plan, Attend, Generate: Character-level Neural Machine Translation with Planning in the Decoder
We investigate the integration of a planning mechanism into an
encoder-decoder architecture with an explicit alignment for character-level
machine translation. We develop a model that plans ahead when it computes
alignments between the source and target sequences, constructing a matrix of
proposed future alignments and a commitment vector that governs whether to
follow or recompute the plan. This mechanism is inspired by the strategic
attentive reader and writer (STRAW) model. Our proposed model is end-to-end
trainable with fully differentiable operations. We show that it outperforms a
strong baseline on three character-level decoder neural machine translation on
WMT'15 corpus. Our analysis demonstrates that our model can compute
qualitatively intuitive alignments and achieves superior performance with fewer
parameters.Comment: Accepted to Rep4NLP 2017 Workshop at ACL 2017 Conferenc
Provincial Battles, National Prize? Elections in a Federal State
This book is about the general election of 2015 in Canada that returned the Liberal Party to power after a nine-year absence
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https://digitalmaine.com/alien_docs/1436/thumbnail.jp
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