4,344 research outputs found
Quantum confinement effects on the ordering of the lowest-lying excited states in conjugated chains
The symmetrized density matrix renormalization group approach is applied
within the extended Hubbard-Peierls model (with parameters U/t, V/t, and bond
alternation \delta) to study the ordering of the lowest one-photon
(1^{1}B^{-}_u) and two-photon (2^{1}A^{+}_g) states in one- dimensional
conjugated systems with chain lengths, N, up to N=80 sites. Three different
types of crossovers are studied, as a function of U/t, \delta, and N. The
U-crossover emphasizes the larger ionic character of the 2A_g state compared to
the lowest triplet excitation. The \delta crossover shows strong dependence on
both N and U/t. The N-crossover illustrates the more localized nature of the
2A_g excitation relative to the 1B_u excitation at intermediate correlation
strengths.Comment: Latex file; figures available upon request. Submitted to PR
SURGE: Continuous Detection of Bursty Regions Over a Stream of Spatial Objects
With the proliferation of mobile devices and location-based services,
continuous generation of massive volume of streaming spatial objects (i.e.,
geo-tagged data) opens up new opportunities to address real-world problems by
analyzing them. In this paper, we present a novel continuous bursty region
detection problem that aims to continuously detect a bursty region of a given
size in a specified geographical area from a stream of spatial objects.
Specifically, a bursty region shows maximum spike in the number of spatial
objects in a given time window. The problem is useful in addressing several
real-world challenges such as surge pricing problem in online transportation
and disease outbreak detection. To solve the problem, we propose an exact
solution and two approximate solutions, and the approximation ratio is
in terms of the burst score, where is a parameter
to control the burst score. We further extend these solutions to support
detection of top- bursty regions. Extensive experiments with real-world data
are conducted to demonstrate the efficiency and effectiveness of our solutions
Discovering Organizational Correlations from Twitter
Organizational relationships are usually very complex in real life. It is
difficult or impossible to directly measure such correlations among different
organizations, because important information is usually not publicly available
(e.g., the correlations of terrorist organizations). Nowadays, an increasing
amount of organizational information can be posted online by individuals and
spread instantly through Twitter. Such information can be crucial for detecting
organizational correlations. In this paper, we study the problem of discovering
correlations among organizations from Twitter. Mining organizational
correlations is a very challenging task due to the following reasons: a) Data
in Twitter occurs as large volumes of mixed information. The most relevant
information about organizations is often buried. Thus, the organizational
correlations can be scattered in multiple places, represented by different
forms; b) Making use of information from Twitter collectively and judiciously
is difficult because of the multiple representations of organizational
correlations that are extracted. In order to address these issues, we propose
multi-CG (multiple Correlation Graphs based model), an unsupervised framework
that can learn a consensus of correlations among organizations based on
multiple representations extracted from Twitter, which is more accurate and
robust than correlations based on a single representation. Empirical study
shows that the consensus graph extracted from Twitter can capture the
organizational correlations effectively.Comment: 11 pages, 4 figure
Fast synchrotron X-ray tomographic quantification of dendrite evolution during the solidification of Mg-Sn alloys
The evolution of dendritic microstructures during the solidification of a Mg-15 wt%Sn alloy was investigated in situ via fast synchrotron X-ray microtomography. To enable these in situ observations a novel encapsulation method was developed and integrated into a fast, pink beam, imaging beamline at Diamond Light Source. The dendritic growth was quantified with time using: solid volume fraction, tip velocity, interface specific surface area, and surface curvature. The influence of cooling rate upon these quantities and primary phase nucleation was investigated. The primary dendrites grew with an 18-branch, 6-fold symmetry structure, accompanied by coarsening. The coarsening process was assessed by the specific surface area and was compared with the existing models. These results provide the first quantification of dendritic growth during the solidification of Mg alloys, confirming existing analytic models and providing experimental data to inform and validate more complex numeric models
Scale-Adaptive Group Optimization for Social Activity Planning
Studies have shown that each person is more inclined to enjoy a group
activity when 1) she is interested in the activity, and 2) many friends with
the same interest join it as well. Nevertheless, even with the interest and
social tightness information available in online social networks, nowadays many
social group activities still need to be coordinated manually. In this paper,
therefore, we first formulate a new problem, named Participant Selection for
Group Activity (PSGA), to decide the group size and select proper participants
so that the sum of personal interests and social tightness of the participants
in the group is maximized, while the activity cost is also carefully examined.
To solve the problem, we design a new randomized algorithm, named Budget-Aware
Randomized Group Selection (BARGS), to optimally allocate the computation
budgets for effective selection of the group size and participants, and we
prove that BARGS can acquire the solution with a guaranteed performance bound.
The proposed algorithm was implemented in Facebook, and experimental results
demonstrate that social groups generated by the proposed algorithm
significantly outperform the baseline solutions.Comment: 20 pages. arXiv admin note: substantial text overlap with
arXiv:1305.150
Dielectrophoresis model for the colossal electroresistance of phase-separated manganites
We propose a dielectrophoresis model for phase-separated manganites. Without
increase of the fraction of metallic phase, an insulator-metal transition
occurs when a uniform electric field applied across the system exceeds a
threshold value. Driven by the dielectrophoretic force, the metallic clusters
reconfigure themselves into stripes along the direction of electric field,
leading to the filamentous percolation. This process, which is time-dependent,
irreversible and anisotropic, is a probable origin of the colossal
electroresistance in manganites.Comment: 4 pages, 5 figure
Low-Lying Electronic Excitations and Nonlinear Optic Properties of Polymers via Symmetrized Density Matrix Renormalization Group Method
A symmetrized Density Matrix Renormalization Group procedure together with
the correction vector approach is shown to be highly accurate for obtaining
dynamic linear and third order polarizabilities of one-dimensional Hubbard and
models. The model is seen to show characteristically different
third harmonic generation response in the CDW and SDW phases. This can be
rationalized from the excitation spectrum of the systems.Comment: 4 pages Latex; 3 eps figures available upon request; Proceedings of
ICSM '96, to appear in Synth. Metals, 199
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