43,550 research outputs found
Cosmological Simulation for Fuzzy Dark Matter Model
Fuzzy Dark Matter (FDM), motivated by string theory, has recently become a
hot candidate for dark matter. The rest mass of FDM is believed to be eV and the corresponding de-Broglie wave length is kpc.
Therefore, the quantum effect of FDM plays an important role in structure
formation. In order to study the cosmological structure formation in FDM model,
several simulation techniques have been introduced. We review the current
status and challenges in the cosmological simulation for the FDM model in this
paper.Comment: 10 pages, 2 tables, published on Front. Astron. Space Sci. under the
topic: Dark Matter - Where is it? What is it
False Data Injection Attacks on Phasor Measurements That Bypass Low-rank Decomposition
This paper studies the vulnerability of phasor measurement units (PMUs) to
false data injection (FDI) attacks. Prior work demonstrated that unobservable
FDI attacks that can bypass traditional bad data detectors based on measurement
residuals can be identified by detector based on low-rank decomposition (LD).
In this work, a class of more sophisticated FDI attacks that captures the
temporal correlation of PMU data is introduced. Such attacks are designed with
a convex optimization problem and can always bypass the LD detector. The
vulnerability of this attack model is illustrated on both the IEEE 24-bus RTS
and the IEEE 118-bus systems.Comment: 6 pages, 4 figures, submitted to 2017 IEEE International Conference
on Smart Grid Communications (SmartGridComm
Emergence of Blind Areas in Information Spreading
Recently, contagion-based (disease, information, etc.) spreading on social
networks has been extensively studied. In this paper, other than traditional
full interaction, we propose a partial interaction based spreading model,
considering that the informed individuals would transmit information to only a
certain fraction of their neighbors due to the transmission ability in
real-world social networks. Simulation results on three representative networks
(BA, ER, WS) indicate that the spreading efficiency is highly correlated with
the network heterogeneity. In addition, a special phenomenon, namely
\emph{Information Blind Areas} where the network is separated by several
information-unreachable clusters, will emerge from the spreading process.
Furthermore, we also find that the size distribution of such information blind
areas obeys power-law-like distribution, which has very similar exponent with
that of site percolation. Detailed analyses show that the critical value is
decreasing along with the network heterogeneity for the spreading process,
which is complete the contrary to that of random selection. Moreover, the
critical value in the latter process is also larger that of the former for the
same network. Those findings might shed some lights in in-depth understanding
the effect of network properties on information spreading
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