Search for CP Violating Signature of Intergalactic Magnetic Helicity in the Gamma Ray Sky

The existence of a cosmological magnetic field could be revealed by the effects of non-trivial helicity on large scales. We evaluate a CP odd statistic, $Q$, using gamma ray data obtained from Fermi satellite observations at high galactic latitudes to search for such a signature. Observed values of $Q$ are found to be non-zero; the probability of a similar signal in Monte Carlo simulations is $\sim 0.2\%$. Contamination from the Milky Way does not seem to be responsible for the signal since it is present even for data at very high galactic latitudes. Assuming that the signal is indeed due to a helical cosmological magnetic field, our results indicate left-handed magnetic helicity and field strength $\sim 10^{-14}~{\rm G}$ on $\sim 10~{\rm Mpc}$ scales.Comment: 5 pages. Matches published MNRAS Lett. version. For analysis tools see http://sites.physics.wustl.edu/magneticfields/wiki/index.php/Search_for_CP_violation_in_the_gamma-ray_sk

Standard random walks and trapping on the Koch network with scale-free behavior and small-world effect

A vast variety of real-life networks display the ubiquitous presence of scale-free phenomenon and small-world effect, both of which play a significant role in the dynamical processes running on networks. Although various dynamical processes have been investigated in scale-free small-world networks, analytical research about random walks on such networks is much less. In this paper, we will study analytically the scaling of the mean first-passage time (MFPT) for random walks on scale-free small-world networks. To this end, we first map the classical Koch fractal to a network, called Koch network. According to this proposed mapping, we present an iterative algorithm for generating the Koch network, based on which we derive closed-form expressions for the relevant topological features, such as degree distribution, clustering coefficient, average path length, and degree correlations. The obtained solutions show that the Koch network exhibits scale-free behavior and small-world effect. Then, we investigate the standard random walks and trapping issue on the Koch network. Through the recurrence relations derived from the structure of the Koch network, we obtain the exact scaling for the MFPT. We show that in the infinite network order limit, the MFPT grows linearly with the number of all nodes in the network. The obtained analytical results are corroborated by direct extensive numerical calculations. In addition, we also determine the scaling efficiency exponents characterizing random walks on the Koch network.Comment: 12 pages, 8 figures. Definitive version published in Physical Review

Research and Design of VR Based Unmanned Aerial Vehicle Model and Database

In response to the application of drones in real life, drones are more susceptible to interference and influence from various external factors such as weather, site, airspace, etc. during flight operations or related tasks. Not only can they not guarantee the completion of expected goals or tasks, but they are also prone to problems such as falling, collision, or accidental injury caused by the unstable state of drones. The drone flight simulation, virtual training, and drone database system developed based on VR technology has improved the safety, diversity, and instability of drones in practical applications, and reduced the interference of external adverse factors on drone flight. A comprehensive drone model database system has been established. This provides effective guarantees for the application and implementation of drones in various fields

The origin of secondary heavy rare earth element enrichment in carbonatites: Constraints from the evolution of the Huanglongpu district, China

publisher: Elsevier articletitle: The origin of secondary heavy rare earth element enrichment in carbonatites: Constraints from the evolution of the Huanglongpu district, China journaltitle: Lithos articlelink: http://dx.doi.org/10.1016/j.lithos.2018.02.027 content_type: article copyright: © 2018 The Authors. Published by Elsevier B.V.Copyright: © 2018 Published by Elsevier B.V. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. The file attached is the Published/publisher’s pdf version of the articl