474 research outputs found
An Investigation of the Late Pleistocene Paleochannel Systems in the Continental Shelf, South of Chesapeake Bay Mouth
New universal gates for topological quantum computation with Fibonacci- 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 (TSC) thin films. Based on the coset
construction, strongly correlated Majorana fermion edge modes on the 7-layers
of TSC are factorized into the composite of the Fibonacci -anyon
and -anyon modes in the tricritical Ising model. Furthermore, the
deconfinement of and via the interacting potential gives
the braiding of either or . Topological phase gates are
assembled by the braidings. With these topological phase gates, we find a set
of fully topological universal gates for the 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
- …