35,052 research outputs found
Discussion on Event Horizon and Quantum Ergosphere of Evaporating Black Holes in a Tunnelling Framework
In this paper, with the Parikh-Wilczek tunnelling framework the positions of
the event horizon of the Vaidya black hole and the Vaidya-Bonner black hole are
calculated respectively. We find that the event horizon and the apparent
horizon of these two black holes correspond respectively to the two turning
points of the Hawking radiation tunnelling barrier. That is, the quantum
ergosphere coincides with the tunnelling barrier. Our calculation also implies
that the Hawking radiation comes from the apparent horizon.Comment: 8 page
Indirect exchange of magnetic impurities in zigzag graphene ribbon
We use quantum Monte Carlo method to study the indirect coupling between two
magnetic impurities on the zigzag edge of graphene ribbon, with respect to the
chemical potential . We find that the spin-spin correlation between two
adatoms located on the nearest sites in the zigzag edge are drastically
suppressed around the zero-energy. As we switch the system away from
half-filling, the antiferromagnetic correlation is first enhanced and then
decreased. If the two adatoms are adsorbed on the sites belonging to the same
sublattice, we find similar behavior of spin-spin correlation except for a
crossover from ferromagnetic to antiferromagentic correlation in the vicinity
of zero-energy. We also calculated the weight of different components of
d-electron wave function and local magnet moment for various values of
parameters, and all the results are consistent with those of spin-spin
correlation between two magnetic impurities.Comment: 3 pages, 4 figures, conference proceedin
Smart Content Recognition from Images Using a Mixture of Convolutional Neural Networks
With rapid development of the Internet, web contents become huge. Most of the
websites are publicly available, and anyone can access the contents from
anywhere such as workplace, home and even schools. Nevertheless, not all the
web contents are appropriate for all users, especially children. An example of
these contents is pornography images which should be restricted to certain age
group. Besides, these images are not safe for work (NSFW) in which employees
should not be seen accessing such contents during work. Recently, convolutional
neural networks have been successfully applied to many computer vision
problems. Inspired by these successes, we propose a mixture of convolutional
neural networks for adult content recognition. Unlike other works, our method
is formulated on a weighted sum of multiple deep neural network models. The
weights of each CNN models are expressed as a linear regression problem learned
using Ordinary Least Squares (OLS). Experimental results demonstrate that the
proposed model outperforms both single CNN model and the average sum of CNN
models in adult content recognition.Comment: To be published in LNEE, Code: github.com/mundher/NSF
Parametric Instability of Supersonic Shear Layers Induced by Periodic Mach Waves
It is suggested that parametric instability can be induced in a confined supersonic shear layer by the use of a periodic Mach wave system generated by a wavy wall. The existence of such an instability solution is demonstrated computationally by solving the Floquet system of equations. The solution is constructed by means of a Fourier-Chebyshev expansion. Numerical convergence is assured by using a very large number of Fourier and Chebyshev basis functions. The computed growth rate of the induced flow instability is found to vary linearly with the amplitude of the mach waves when the amplitude is not excessively large. This ensures that the instability is, indeed, tied to the presence of the Mach waves. It is proposed that enhanced mixing of supersonic shear layers may be achieved by the use of such a periodic Mach wave system through the inducement of parametric instabilities in the flow. © 1991 American Institute of Physics
Pervasive allele-specific regulation on RNA decay in hybrid mice
Cellular RNA abundance is determined by both RNA transcription and decay. Therefore, change in RNA abundance, which can drive phenotypic diversity between different species, could arise from genetic variants affecting either process. However, previous studies in the evolution of RNA expression have been largely focused on transcription. Here, to globally investigate the effects of cis-regulatory divergence on RNA decay in mammals for the first time, we quantified allele-specific differences in RNA decay rates (ASD) in an F1 hybrid mouse. Out of 8,815 genes with sufficient data, we identified 621 genes exhibiting significant cis-divergence. Systematic analysis of these genes revealed that the genetic variants affecting microRNA binding and RNA secondary structures contribute to the observed divergences. Finally, we demonstrated that although the divergences in RNA abundance were predominantly determined by allelic differences in RNA transcription, most genes with significant ASD did not exhibit significant difference in RNA abundance. For these genes, the apparently compensatory effect between the allelic differences in RNA transcription and ASD suggests that changes in RNA decay could serve as important means to stabilize RNA abundances during mammalian evolution
Ground state fidelity in bond-alternative Ising chains with Dzyaloshinskii-Moriya interactions
A systematic analysis is performed for quantum phase transitions in a
bond-alternative one-dimensional Ising model with a Dzyaloshinskii-Moriya (DM)
interaction by using the fidelity of ground state wave functions based on the
infinite matrix product states algorithm. For an antiferromagnetic phase, the
fidelity per lattice site exhibits a bifurcation, which shows spontaneous
symmetry breaking in the system. A critical DM interaction is inversely
proportional to an alternating exchange coupling strength for a quantum phase
transition. Further, a finite-entanglement scaling of von Neumann entropy with
respect to truncation dimensions gives a central charge c = 0.5 at the critical
point.Comment: 6 pages, 4 figure
Emergence of intrinsic superconductivity below 1.178 K in the topologically non-trivial semimetal state of CaSn3
Topological materials which are also superconducting are of great current
interest, since they may exhibit a non-trivial topologically-mediated
superconducting phase. Although there have been many reports of pressure-tuned
or chemical-doping-induced superconductivity in a variety of topological
materials, there have been few examples of intrinsic, ambient pressure
superconductivity in a topological system having a stoichiometric composition.
Here, we report that the pure intermetallic CaSn3 not only exhibits topological
fermion properties but also has a superconducting phase at 1.178 K under
ambient pressure. The topological fermion properties, including the nearly zero
quasi-particle mass and the non-trivial Berry phase accumulated in cyclotron
motions, were revealed from the de Haas-van Alphen (dHvA) quantum oscillation
studies of this material. Although CaSn3 was previously reported to be
superconducting at 4.2K, our studies show that the superconductivity at 4.2K is
extrinsic and caused by Sn on the degraded surface, whereas its intrinsic bulk
superconducting transition occurs at 1.178 K. These findings make CaSn3 a
promising candidate for exploring new exotic states arising from the interplay
between non-trivial band topology and superconductivity, e.g. topological
superconductivityComment: 20 pages,4 figure
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