New universal gates for topological quantum computation with Fibonacci-ε\boldsymbol{\varepsilon} composite Majorana edge modes on topological superconductor multilayers

We propose a new design of universal topological quantum computer device through a hybrid of the 1-, 2- and 7-layers of chiral topological superconductor ($\chi$TSC) thin films. Based on the $SO(7)_1/(G_2)_1$ coset construction, strongly correlated Majorana fermion edge modes on the 7-layers of $\chi$TSC are factorized into the composite of the Fibonacci $\tau$-anyon and $\varepsilon$-anyon modes in the tricritical Ising model. Furthermore, the deconfinement of $\tau$ and $\varepsilon$ via the interacting potential gives the braiding of either $\tau$ or $\varepsilon$. Topological phase gates are assembled by the braidings. With these topological phase gates, we find a set of fully topological universal gates for the $(\tau,\varepsilon)$ composite Majorana-Ising-type quantum computation. Because the Hilbert space still possesses a tensor product structure of quibts and is characterized by the fermion parities, encoding quantum information in this machine is more efficient and substantial than that with Fibonacci anyons. The computation results is easier to be read out by electric signals, so are the initial data inputted.Comment: 6 pages, 3 figues, revised versio

TGSum: Build Tweet Guided Multi-Document Summarization Dataset

The development of summarization research has been significantly hampered by the costly acquisition of reference summaries. This paper proposes an effective way to automatically collect large scales of news-related multi-document summaries with reference to social media's reactions. We utilize two types of social labels in tweets, i.e., hashtags and hyper-links. Hashtags are used to cluster documents into different topic sets. Also, a tweet with a hyper-link often highlights certain key points of the corresponding document. We synthesize a linked document cluster to form a reference summary which can cover most key points. To this aim, we adopt the ROUGE metrics to measure the coverage ratio, and develop an Integer Linear Programming solution to discover the sentence set reaching the upper bound of ROUGE. Since we allow summary sentences to be selected from both documents and high-quality tweets, the generated reference summaries could be abstractive. Both informativeness and readability of the collected summaries are verified by manual judgment. In addition, we train a Support Vector Regression summarizer on DUC generic multi-document summarization benchmarks. With the collected data as extra training resource, the performance of the summarizer improves a lot on all the test sets. We release this dataset for further research.Comment: 7 pages, 1 figure in AAAI 201

Disorder and metal-insulator transitions in Weyl semimetals

The Weyl semimetal (WSM) is a newly proposed quantum state of matter. It has Weyl nodes in bulk excitations and Fermi arcs surface states. We study the effects of disorder and localization in WSMs and find three exotic phase transitions. (I) Two Weyl nodes near the Brillouin zone boundary can be annihilated pairwise by disorder scattering, resulting in the opening of a topologically nontrivial gap and a transition from a WSM to a three-dimensional (3D) quantum anomalous Hall state. (II) When the two Weyl nodes are well separated in momentum space, the emergent bulk extended states can give rise to a direct transition from a WSM to a 3D diffusive anomalous Hall metal. (III) Two Weyl nodes can emerge near the zone center when an insulating gap closes with increasing disorder, enabling a direct transition from a normal band insulator to a WSM. We determine the phase diagram by numerically computing the localization length and the Hall conductivity, and propose that the exotic phase transitions can be realized on a photonic lattice.Comment: 7 pages with appendix, 6 figure

Flutter Influence Mode Analysis of High Speed Wing Model

AbstractIn flutter wind tunnel test, the matching degree between scaled model and prototype would directly affect the reliability of test results. It is difficult to achieve completely dynamic similarity because of some material or technological constrains, and only lower order modes including mode shape and frequency are accurately simulated to construct a compromised model. Theoretical support would be necessary to answer the question which modes must be simulated to guarantee data validity of wind tunnel flutter test. An analytical study of a sweepback winghas been undertaken to estimate the flutter influence mode needed for accurate flutter prediction by analyzing generalized aerodynamic stiffness coefficient, unsteady aerodynamic force and flutter results. The results show that the aerodynamic stiffness coefficient with expression of mode shape could be taken as a quick criterion for mode selection in flutter model design and analysis

Forcing the Whole Video as Background: An Adversarial Learning Strategy for Weakly Temporal Action Localization

With video-level labels, weakly supervised temporal action localization (WTAL) applies a localization-by-classification paradigm to detect and classify the action in untrimmed videos. Due to the characteristic of classification, class-specific background snippets are inevitably mis-activated to improve the discriminability of the classifier in WTAL. To alleviate the disturbance of background, existing methods try to enlarge the discrepancy between action and background through modeling background snippets with pseudo-snippet-level annotations, which largely rely on artificial hypotheticals. Distinct from the previous works, we present an adversarial learning strategy to break the limitation of mining pseudo background snippets. Concretely, the background classification loss forces the whole video to be regarded as the background by a background gradient reinforcement strategy, confusing the recognition model. Reversely, the foreground(action) loss guides the model to focus on action snippets under such conditions. As a result, competition between the two classification losses drives the model to boost its ability for action modeling. Simultaneously, a novel temporal enhancement network is designed to facilitate the model to construct temporal relation of affinity snippets based on the proposed strategy, for further improving the performance of action localization. Finally, extensive experiments conducted on THUMOS14 and ActivityNet1.2 demonstrate the effectiveness of the proposed method.Comment: 9 pages, 5 figures, conferenc

A distributed hybrid index for processing continuous range queries over moving objects

Central to many location-based services is the problem of processing concurrent continuous range queries over a large scale of moving objects. Most relevant works to this problem mainly investigate the centralized search algorithms based on a single server for handling range queries. However, due to the limited resources of a single server, these algorithms hardly can deal with an ocean of objects and extensive concurrent queries. Moreover, these approaches usually suppose either objects or queries are static but seldom consider the scenario that objects and queries are both moving simultaneously, restricting the practicability of these approaches. To resolve the above issues, we propose a distributed hybrid index (DHI) that consists of a global grid index and extensive local VR-tree indexes. DHI is apt to be deployed on a cluster of servers, and owns a good scalability to maintain numerous moving objects and concurrent range queries. Based on DHI, we further design a distributed incremental search approach, which organizes multiple servers with a publish/subscribe mechanism to calculate and monitor the results for continuous range queries in a distributed pattern. Finally, we conduct extensive experiments to fully evaluate the performance of our paper.Peer ReviewedPostprint (author's final draft