Magnetic moments of the spin-32{3\over 2} doubly heavy baryons

In this work, we investigate the chiral corrections to the magnetic moments of the spin-$3\over 2$ doubly charmed baryons systematically up to next-to-next-to-leading order with the heavy baryon chiral perturbation theory. The numerical results are given up to next-to-leading order: $\mu_{\Xi^{*++}_{cc}}=1.72\mu_{N}$, $\mu_{\Xi^{*+}_{cc}}=-0.09\mu_{N}$, $\mu_{\Omega^{*+}_{cc}}=0.99\mu_{N}$. As a by-product, we have also calculated the magnetic moments of the spin-$3\over 2$ doubly bottom baryons and charmed bottom baryons: $\mu_{\Xi^{*0}_{bb}}=0.63\mu_{N}$, $\mu_{\Xi^{*-}_{bb}}=-0.79\mu_{N}$, $\mu_{\Omega^{*-}_{bb}}=0.12\mu_{N}$, $\mu_{\Xi^{*+}_{bc}}=1.12\mu_{N}$, $\mu_{\Xi^{*0}_{bc}}=-0.40\mu_{N}$, $\mu_{\Omega^{*0}_{bc}}=0.56\mu_{N}$.Comment: 10 pages,2 figures. arXiv admin note: text overlap with arXiv:1707.02765. Replace the published versio

Radiative decays of the doubly charmed baryons in chiral perturbation theory

We have systematically investigated the spin-$\frac{3}{2}$ to spin-$\frac{1}{2}$ doubly charmed baryon transition magnetic moments to the next-to-next-to-leading order in the heavy baryon chiral perturbation theory (HBChPT). Numerical results of transition magnetic moments and decay widths are presented to the next-to-leading order: $\mu_{\Xi_{cc}^{*++}\rightarrow\Xi_{cc}^{++}}=-2.35\mu_{N}$, $\mu_{\Xi_{cc}^{*+}\rightarrow\Xi_{cc}^{+}}=1.55\mu_{N}$, $\mu_{\Omega_{cc}^{*+}\rightarrow\Omega_{cc}^{+}}=1.54\mu_{N}$, $\Gamma_{\Xi_{cc}^{*++}\rightarrow\Xi_{cc}^{++}}=22.0$ keV, $\Gamma_{\Xi_{cc}^{*+}\rightarrow\Xi_{cc}^{+}}=9.57$ keV, $\Gamma_{\Omega_{cc}^{*+}\rightarrow\Omega_{cc}^{+}}=9.45$ keV.Comment: arXiv admin note: text overlap with arXiv:1707.02765, arXiv:1706.0645

End-to-End Quantum-like Language Models with Application to Question Answering

Language Modeling (LM) is a fundamental research topic ina range of areas. Recently, inspired by quantum theory, a novel Quantum Language Model (QLM) has been proposed for Information Retrieval (IR). In this paper, we aim to broaden the theoretical and practical basis of QLM. We develop a Neural Network based Quantum-like Language Model (NNQLM) and apply it to Question Answering. Specifically, based on word embeddings, we design a new density matrix, which represents a sentence (e.g., a question or an answer) and encodes a mixture of semantic subspaces. Such a density matrix, together with a joint representation of the question and the answer, can be integrated into neural network architectures (e.g., 2-dimensional convolutional neural networks). Experiments on the TREC-QA and WIKIQA datasets have verified the effectiveness of our proposed models

Distributed Power-Line Outage Detection Based on Wide Area Measurement System

In modern power grids, the fast and reliable detection of power-line outages is an important functionality, which prevents cascading failures and facilitates an accurate state estimation to monitor the real-time conditions of the grids. However, most of the existing approaches for outage detection suffer from two drawbacks, namely: (i) high computational complexity; and (ii) relying on a centralized means of implementation. The high computational complexity limits the practical usage of outage detection only for the case of single-line or double-line outages. Meanwhile, the centralized means of implementation raises security and privacy issues. Considering these drawbacks, the present paper proposes a distributed framework, which carries out in-network information processing and only shares estimates on boundaries with the neighboring control areas. This novel framework relies on a convex-relaxed formulation of the line outage detection problem and leverages the alternating direction method of multipliers (ADMM) for its distributed solution. The proposed framework invokes a low computational complexity, requiring only linear and simple matrix-vector operations. We also extend this framework to incorporate the sparse property of the measurement matrix and employ the LSQRalgorithm to enable a warm start, which further accelerates the algorithm. Analysis and simulation tests validate the correctness and effectiveness of the proposed approaches