18,080 research outputs found
Critical behavior of a stochastic anisotropic Bak-Sneppen model
In this paper we present our study on the critical behavior of a stochastic
anisotropic Bak-Sneppen (saBS) model, in which a parameter is
introduced to describe the interaction strength among nearest species. We
estimate the threshold fitness and the critical exponent by
numerically integrating a master equation for the distribution of avalanche
spatial sizes. Other critical exponents are then evaluated from previously
known scaling relations. The numerical results are in good agreement with the
counterparts yielded by the Monte Carlo simulations. Our results indicate that
all saBS models with nonzero interaction strength exhibit self-organized
criticality, and fall into the same universality class, by sharing the
universal critical exponents.Comment: 9 pages, 7 figures. arXiv admin note: text overlap with
arXiv:cond-mat/9803068 by other author
Exploiting Device-to-Device Communications to Enhance Spatial Reuse for Popular Content Downloading in Directional mmWave Small Cells
With the explosive growth of mobile demand, small cells in millimeter wave
(mmWave) bands underlying the macrocell networks have attracted intense
interest from both academia and industry. MmWave communications in the 60 GHz
band are able to utilize the huge unlicensed bandwidth to provide multiple Gbps
transmission rates. In this case, device-to-device (D2D) communications in
mmWave bands should be fully exploited due to no interference with the
macrocell networks and higher achievable transmission rates. In addition, due
to less interference by directional transmission, multiple links including D2D
links can be scheduled for concurrent transmissions (spatial reuse). With the
popularity of content-based mobile applications, popular content downloading in
the small cells needs to be optimized to improve network performance and
enhance user experience. In this paper, we develop an efficient scheduling
scheme for popular content downloading in mmWave small cells, termed PCDS
(popular content downloading scheduling), where both D2D communications in
close proximity and concurrent transmissions are exploited to improve
transmission efficiency. In PCDS, a transmission path selection algorithm is
designed to establish multi-hop transmission paths for users, aiming at better
utilization of D2D communications and concurrent transmissions. After
transmission path selection, a concurrent transmission scheduling algorithm is
designed to maximize the spatial reuse gain. Through extensive simulations
under various traffic patterns, we demonstrate PCDS achieves near-optimal
performance in terms of delay and throughput, and also superior performance
compared with other existing protocols, especially under heavy load.Comment: 12 pages, to appear in IEEE Transactions on Vehicular Technolog
Community detection by label propagation with compression of flow
The label propagation algorithm (LPA) has been proved to be a fast and
effective method for detecting communities in large complex networks. However,
its performance is subject to the non-stable and trivial solutions of the
problem. In this paper, we propose a modified label propagation algorithm LPAf
to efficiently detect community structures in networks. Instead of the majority
voting rule of the basic LPA, LPAf updates the label of a node by considering
the compression of a description of random walks on a network. A multi-step
greedy agglomerative strategy is employed to enable LPAf to escape the local
optimum. Furthermore, an incomplete update condition is also adopted to speed
up the convergence. Experimental results on both synthetic and real-world
networks confirm the effectiveness of our algorithm
High-field quantum spin liquid transitions and angle-field phase diagram of Kitaev magnet -RuCl
The pursuit of quantum spin liquid (QSL) in the Kitaev honeycomb magnets has
drawn intensive attention recently. In particular, -RuCl has been
widely recognized as a promising candidate for the Kitaev QSL. Although the
compound exhibits an antiferromagnetic order under zero field, it is believed
to be endowed with fractionalized excitations, and can be driven to the QSL
phase by magnetic fields. Here, based on a realistic ---
model for -RuCl [1], we exploit the exponential tensor
renormalization group approach to explore the phase diagram of the compound
under magnetic fields. We calculate the thermodynamic quantities, including the
specific heat, Gr\"uneisen parameter, magnetic torque, and the magnetotropic
susceptibility, etc, under a magnetic field with a tilting angle to
the -axis perpendicular to the honeycomb plane. We find an extended QSL in
the angle-field phase diagram determined with thermodynamic responses. The
gapless nature of such field-induced QSL is identified from the specific heat
and entropy data computed down to very low temperatures. The present study
provides guidance for future high-field experiments for the QSL in
-RuCl and other candidate Kitaev magnets.Comment: 10 pages, 6 figures (including Appendices
Community Detection in Dynamic Networks via Adaptive Label Propagation
An adaptive label propagation algorithm (ALPA) is proposed to detect and
monitor communities in dynamic networks. Unlike the traditional methods by
re-computing the whole community decomposition after each modification of the
network, ALPA takes into account the information of historical communities and
updates its solution according to the network modifications via a local label
propagation process, which generally affects only a small portion of the
network. This makes it respond to network changes at low computational cost.
The effectiveness of ALPA has been tested on both synthetic and real-world
networks, which shows that it can successfully identify and track dynamic
communities. Moreover, ALPA could detect communities with high quality and
accuracy compared to other methods. Therefore, being low-complexity and
parameter-free, ALPA is a scalable and promising solution for some real-world
applications of community detection in dynamic networks.Comment: 16 pages, 11 figure
The effects of overtaking strategy in the Nagel-Schreckenberg model
Based on the Nagel-Schreckenberg (NS) model with periodic boundary
conditions, we proposed the NSOS model by adding the overtaking strategy (OS).
In our model, overtaking vehicles are randomly selected with probability at
each time step, and the successful overtaking is determined by their
velocities. We observed that (i) traffic jams still occur in the NSOS model;
(ii) OS increases the traffic flow in the regime where the densities exceed the
maximum flow density. We also studied the phase transition (from free flow
phase to jammed phase) of the NSOS model by analyzing the overtaking success
rate, order parameter, relaxation time and correlation function, respectively.
It was shown that the NSOS model differs from the NS model mainly in the jammed
regime, and the influence of OS on the transition density is dominated by the
braking probability Comment: 9 pages, 20 figures, to be published in The European Physical Journal
B (EPJB
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