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

Adversarial Generation of Natural Language

Generative Adversarial Networks (GANs) have gathered a lot of attention from the computer vision community, yielding impressive results for image generation. Advances in the adversarial generation of natural language from noise however are not commensurate with the progress made in generating images, and still lag far behind likelihood based methods. In this paper, we take a step towards generating natural language with a GAN objective alone. We introduce a simple baseline that addresses the discrete output space problem without relying on gradient estimators and show that it is able to achieve state-of-the-art results on a Chinese poem generation dataset. We present quantitative results on generating sentences from context-free and probabilistic context-free grammars, and qualitative language modeling results. A conditional version is also described that can generate sequences conditioned on sentence characteristics.Comment: 11 pages, 3 figures, 5 table

The relationship between smolt and postsmolt growth for Atlantic salmon (Salmo salar) in the Gulf of St. Lawrence

The interaction of ocean climate and growth conditions during the postsmolt phase is emerging as the primary hypothesis to explain patterns of adult recruitment for individual stocks and stock complexes of Atlantic salmon (Salmo salar). Friedland et al. (1993) first reported that contrast in sea surface temperature (SST) conditions during spring appeared to be related to recruitment of the European stock complex. This hypothesis was further supported by the relationship between cohort specific patterns of recruitment for two index stocks and regional scale SST (Friedland et al., 1998). One of the index stocks, the North Esk of Scotland, was shown to have a pattern of postsmolt growth that was positively correlated with survival, indicating that growth during the postsmolt year controls survival and recruitment (Friedland et al., 2000). A similar scenario is emerging for the North American stock complex where contrast in ocean conditions during spring in the postsmolt migration corridors was associated with the recruitment pattern of the stock complex (Friedland et al., 2003a, 2003b). The accumulation of additional data on the postsmolt growth response of both stock complexes will contribute to a better understanding of the recruitment process in Atlantic salmon