14,556 research outputs found
Black hole remnant in asymptotic Anti-de Sitter space
It is known that a solution of remnant were suggested for black hole ground
state after surface gravity is corrected by loop quantum effect. On the other
hand, a Schwarzschild black hole in asymptotic Anti-de Sitter space would
tunnel into the thermal soliton solution known as the Hawking-Page phase
transition. In this letter, we investigate the low temperature phase of
three-dimensional BTZ black hole and four-dimensional AdS Schwarzschild black
hole. We find that the thermal soliton is energetically favored than the
remnant solution at low temperature in three dimensions, while Planck-size
remnant is still possible in four dimensions. Though the BTZ remnant seems
energetically disfavored, we argue that it is still possible to be found in the
overcooled phase if strings were present and its implication is discussed.Comment: 13 pages, 5 figures, submitted versio
Holographic study on the jet quenching parameter in anisotropic systems
We first calculate the jet quenching parameter of an anisotropic plasma with
a U(1) chemical potential via the AdS/CFT duality. The effects of charge,
anisotropy parameter and quark motion direction on the jet quenching parameter
are investigated. We then discuss the situation of anisotropic black brane in
the IR region. We study both the jet quenching parameters along the
longitudinal direction and transverse plane
Investigating Linguistic Pattern Ordering in Hierarchical Natural Language Generation
Natural language generation (NLG) is a critical component in spoken dialogue
system, which can be divided into two phases: (1) sentence planning: deciding
the overall sentence structure, (2) surface realization: determining specific
word forms and flattening the sentence structure into a string. With the rise
of deep learning, most modern NLG models are based on a sequence-to-sequence
(seq2seq) model, which basically contains an encoder-decoder structure; these
NLG models generate sentences from scratch by jointly optimizing sentence
planning and surface realization. However, such simple encoder-decoder
architecture usually fail to generate complex and long sentences, because the
decoder has difficulty learning all grammar and diction knowledge well. This
paper introduces an NLG model with a hierarchical attentional decoder, where
the hierarchy focuses on leveraging linguistic knowledge in a specific order.
The experiments show that the proposed method significantly outperforms the
traditional seq2seq model with a smaller model size, and the design of the
hierarchical attentional decoder can be applied to various NLG systems.
Furthermore, different generation strategies based on linguistic patterns are
investigated and analyzed in order to guide future NLG research work.Comment: accepted by the 7th IEEE Workshop on Spoken Language Technology (SLT
2018). arXiv admin note: text overlap with arXiv:1808.0274
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