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