arXiv subjects

Jun Meng

Publications and source records attributed to Jun Meng.

46 records · Page 3Linked to original sources

arXiv2018

Resilience of spatial networks with inter-links behaving as an external field

Many real systems such as, roads, shipping routes, and infrastructure systems can be modeled based on spatially embedded networks. The inter-links between two distant spatial networks, such as those formed by transcontinental airline flights, play a crucial role in optimizing communication and transportation over such long distances. Still, little is known about how inter-links affect the resilience of such systems. Here, we develop a framework to study the resilience of interlinked spatially embedded networks based on percolation theory. We find that the inter-links can be regarded as an external field near the percolation phase transition, analogous to a magnetic field in a ferromagnetic-paramagnetic spin system. By defining the analogous critical exponents $δ$ and $γ$, we find that their values for various inter-links structures follow Widom's scaling relations. Furthermore, we study the optimal robustness of our model and compare it with the analysis of real-world networks. The framework presented here not only facilitates the understanding of phase transitions with external fields in complex networks but also provides insight into optimizing real-world infrastructure networks and a magnetic field in a management.

physics.soc-ph↗

arXiv2018

Forecasting the magnitude and onset of El Nino based on climate network

El Nino is probably the most influential climate phenomenon on interannual time scales. It affects the global climate system and is associated with natural disasters and serious consequences in many aspects of human life. However, the forecasting of the onset and in particular the magnitude of El Nino are still not accurate, at least more than half a year in advance. Here, we introduce a new forecasting index based on network links representing the similarity of low frequency temporal temperature anomaly variations between different sites in the El Nino 3.4 region. We find that significant upward trends and peaks in this index forecast with high accuracy both the onset and magnitude of El Nino approximately 1 year ahead. The forecasting procedure we developed improves in particular the prediction of the magnitude of El Nino and is validated based on several, up to more than a century long, datasets.

physics.geo-ph↗

arXiv2017

Abrupt transitions in collaborative social networks

Despite the wide use of networks as a versatile tool for exploring complex social systems, little is known about how to detect and forecast abrupt changes in social systems. In this report, we develop an early warning approach based on network properties to detect such changes. By analysing three collaborative social networks---one co-stardom, one patent and one scientific collaborative network, we discover that abrupt transitions inherent in these networks can serve as a good early warning signal, indicating, respectively, the dissolution of the Soviet Union, the emergence of the "soft matter" research field, and the merging of two scientific communities. We then develop a clique growth model that explains the universal properties of these real networks and find that they belong to a new universality class, described by the Gumbel distribution.

physics.soc-ph↗

arXiv2017

Statistical properties of random clique networks

In this paper, a random clique network model to mimic the large clustering coefficient and the modular structure that exist in many real complex networks, such as social networks, artificial networks, and protein interaction networks, is introduced by combining the random selection rule of the Erdös and Rényi (ER) model and the concept of cliques. We find that random clique networks having a small average degree differ from the ER network in that they have a large clustering coefficient and a power law clustering spectrum, while networks having a high average degree have similar properties as the ER model. In addition, we find that the relation between the clustering coefficient and the average degree shows a non-monotonic behavior and that the degree distributions can be fit by multiple Poisson curves; we explain the origin of such novel behaviors and degree distributions.

physics.soc-ph↗

arXiv2016

Percolation framework to describe El Niño conditions

Complex networks have been used intensively to investigate the flow and dynamics of many natural systems including the climate system. Here, we develop a percolation based measure, the order parameter, to study and quantify climate networks. We find that abrupt transitions of the order parameter usually occur $\sim$1 year before El Niño ~ events, suggesting that they can be used as early warning precursors of El Niño. Using this method we analyze several reanalysis datasets and show the potential for good forecasting of El Niño. The percolation based order parameter exhibits discontinuous features, indicating possible relation to the first order phase transition mechanism.

physics.ao-ph↗

arXiv2016

Climate network suggests enhanced El Niño global impacts in localized areas

We construct directed and weighted climate networks based on near surface air temperature to investigate the global impacts of El Nino and La Nina. We find that regions which are characterized by higher positive or negative network in weighted links, are exhibiting stronger correlations with the El Nino basin and are warmer or cooler during El Nino or La Nina periods. These stronger in-weighted activities are found to be concentrated in localized areas, as compared to non-El Nino periods, whereas a large fraction of the globe is not influenced by the events. The regions of localized activity vary from one El Nino (La Nina) event to another; still some El Nino (La Nina) events are more similar to each other. We quantify this similarity using network community structure. The results and methodology reported here may be used to improve the understanding and prediction of El Nino or La Nina events and also may be applied in the investigation of other climate variables.

physics.ao-ph↗

arXiv2013

Cosmological constraints on the new holographic dark energy model with action principle

Recently, a New HDE model with action principle was proposed (Li and Miao, arXiv:1210.0966). This model completely solves the causality and circular problems in the original HDE model, and is similar to the original model except a new term that can be interpreted as dark radiation. In this paper, we make further investigations on this model from the aspect of cosmological observations. Numerically, we confirm that the equations of motion force the $L(z=-1)=0$, making the cut-off $aL$ exactly the future event horizon. We also perform detailed analysis on the dynamical properties of the model, divided into the $c<6$ and $c\geq6$ cases ($c$ is a dimensionless parameter which should be decided by the data). From a combination of the present Union2.1+BAO+CMB+$H_0$ data, we find the model yields $χ^2_{\rm min}=548.798$ (in a non-flat Universe), comparable to the results of the original HDE model (549.461) and the concordant $Λ$CDM model (550.354). At 95.4% CL, we get $1.41<c<3.09$ and correspondingly $-2.25<w(z=-1)<-1.39$, implying the Big Rip fate of the Universe at a high confidence level. Besides, for the constraints on dark radiation, we also get a rough estimation $N_{\rm \rm eff}=3.54^{+0.32+0.67}_{\rm -0.45-0.76}$, with the central value slightly larger than the standard value 3.046.

astro-ph.CO↗

arXiv2012

Einstein Equations From Holographic Thermodynamics and Holographic Entropy

We derive the Einstein field equations and black hole entropy from the first law of thermodynamics on a holographic time-like screen. Because of the universality of gravity, the stress tensor on the screen must be independent of the details of matter fields, so it should be a pure geometric quantity. For simplicity, we assume that the stress tensor on the screen depends on surface Ricci curvature and extrinsic curvature linearly. Then we prove that the surface stress tensor is just the Brown-York stress tensor plus terms which do not affect the field equations of gravitation and the entropy of the system. By assuming a generalized "Fine first law of thermodynamics" or the usual universal first law of thermodynamics on the screen, we can derive the matter field equations as well.

hep-th↗

arXiv2012

Replaying neutrino bremsstrahlung with general dispersion relations

It is generally held that neutrinos with superluminal velocity will lose their energy spontaneously by radiating electron-positron pairs, similar to bremsstrahlung process. Recently, this process was closely studied for neutrinos whose energy is roughly proportional to their momentum. Confronted with an increasing amount of superluminal neutrino models, it is urgent to calculate the same process for general dispersion relations. The calculation is performed in this paper, without resorting to any nontrivial frame such as the effective "rest frame".

hep-ph↗

arXiv2011

f(R) Gravity and Maxwell Equations from the Holographic Principle

Extending the holographic program of [1], we derive f(R) gravity and the Maxwell equations from the holographic principle, using time-like holographic screen. We find that to derive the Einstein equations and f(R) gravity in a natural holographic approach, the quasi-static condition is necessary. We also find the surface stress tensor and the surface electric current, surface magnetic current on the holographic screen for f(R) gravity and Maxwell's theory, respectively.

hep-th↗