Bridgeness: A Local Index on Edge Significance in Maintaining Global Connectivity

Edges in a network can be divided into two kinds according to their different roles: some enhance the locality like the ones inside a cluster while others contribute to the global connectivity like the ones connecting two clusters. A recent study by Onnela et al uncovered the weak ties effects in mobile communication. In this article, we provide complementary results on document networks, that is, the edges connecting less similar nodes in content are more significant in maintaining the global connectivity. We propose an index named bridgeness to quantify the edge significance in maintaining connectivity, which only depends on local information of network topology. We compare the bridgeness with content similarity and some other structural indices according to an edge percolation process. Experimental results on document networks show that the bridgeness outperforms content similarity in characterizing the edge significance. Furthermore, extensive numerical results on disparate networks indicate that the bridgeness is also better than some well-known indices on edge significance, including the Jaccard coefficient, degree product and betweenness centrality.Comment: 10 pages, 4 figures, 1 tabl

Dissociation energy of the hydrogen molecule at 10−9^{-9} accuracy

The ionization energy of ortho-H$_2$ has been determined to be $E^\mathrm{o}_\mathrm{I}(\mathrm{H}_2)/(hc)=124\,357.238\,062(25)$ cm$^{-1}$ from measurements of the GK(1,1)--X(0,1) interval by Doppler-free two-photon spectroscopy using a narrow band 179-nm laser source and the ionization energy of the GK(1,1) state by continuous-wave near-infrared laser spectroscopy. $E^\mathrm{o}_\mathrm{I}$(H$_2$) was used to derive the dissociation energy of H$_2$, $D^{N=1}_{0}$(H$_2$), at $35\,999.582\,894(25)$ cm$^{-1}$ with a precision that is more than one order of magnitude better than all previous results. The new result challenges calculations of this quantity and represents a benchmark value for future relativistic and QED calculations of molecular energies.Comment: 6 pages, 5 figure

Impact of Gobi desert dust on aerosol chemistry of Xi'an, inland China during spring 2009: differences in composition and size distribution between the urban ground surface and the mountain atmosphere

Composition and size distribution of atmospheric aerosols from Xi'an city (~400 m, altitude) in inland China during the spring of 2009 including a massive dust event on 24 April were measured and compared with a parallel measurement at the summit (2060 m, altitude) of Mt. Hua, an alpine site nearby Xi'an. EC (elemental carbon), OC (organic carbon) and major ions in the city were 2–22 times higher than those on the mountaintop during the whole sampling period. Compared to that in the non-dust period a sharp increase in OC was observed at both sites during the dust period, which was mainly caused by an input of biogenic organics from the Gobi desert. However, adsorption/heterogeneous reaction of gaseous organics with dust was another important source of OC in the urban, contributing 22% of OC in the dust event. In contrast to the mountain atmosphere where fine particles were less acidic when dust was present, the urban fine particles became more acidic in the dust event than in the non-dust event, mainly due to enhanced heterogeneous formation of nitrate and diluted NH<sub>3</sub>. Cl<sup>−</sup> and NO<sub>3</sub><sup>−</sup> in the urban air during the dust event significantly shifted toward coarse particles. Such redistributions were further pronounced on the mountaintop when dust was present, resulting in both ions almost entirely staying in coarse particles. On the contrary, no significant spatial difference in size distribution of SO<sub>4</sub><sup>2−</sup> was found between the urban ground surface and the mountain atmosphere, which dominated in the fine mode (<2.1 μm) during the nonevent and comparably distributed in the fine (<2.1 μm) and coarse (>2.1 μm) modes during the dust event

VR-SGD: A Simple Stochastic Variance Reduction Method for Machine Learning

© 1989-2012 IEEE. In this paper, we propose a simple variant of the original SVRG, called variance reduced stochastic gradient descent (VR-SGD). Unlike the choices of snapshot and starting points in SVRG and its proximal variant, Prox-SVRG, the two vectors of VR-SGD are set to the average and last iterate of the previous epoch, respectively. The settings allow us to use much larger learning rates, and also make our convergence analysis more challenging. We also design two different update rules for smooth and non-smooth objective functions, respectively, which means that VR-SGD can tackle non-smooth and/or non-strongly convex problems directly without any reduction techniques. Moreover, we analyze the convergence properties of VR-SGD for strongly convex problems, which show that VR-SGD attains linear convergence. Different from most algorithms that have no convergence guarantees for non-strongly convex problems, we also provide the convergence guarantees of VR-SGD for this case, and empirically verify that VR-SGD with varying learning rates achieves similar performance to its momentum accelerated variant that has the optimal convergence rate O(1/T2O(1/T2). Finally, we apply VR-SGD to solve various machine learning problems, such as convex and non-convex empirical risk minimization, and leading eigenvalue computation. Experimental results show that VR-SGD converges significantly faster than SVRG and Prox-SVRG, and usually outperforms state-of-the-art accelerated methods, e.g., Katyusha

Smoking-gun signatures of little Higgs models

Little Higgs models predict new gauge bosons, fermions and scalars at the TeV scale that stabilize the Higgs mass against quadratically divergent one-loop radiative corrections. We categorize the many little Higgs models into two classes based on the structure of the extended electroweak gauge group and examine the experimental signatures that identify the little Higgs mechanism in addition to those that identify the particular little Higgs model. We find that by examining the properties of the new heavy fermion(s) at the LHC, one can distinguish the structure of the top quark mass generation mechanism and test the little Higgs mechanism in the top sector. Similarly, by studying the couplings of the new gauge bosons to the light Higgs boson and to the Standard Model fermions, one can confirm the little Higgs mechanism and determine the structure of the extended electroweak gauge group.Comment: 59 pages, 10 figures. v2: refs added, typos fixed, JHEP versio

Continuous extremal optimization for Lennard-Jones Clusters

In this paper, we explore a general-purpose heuristic algorithm for finding high-quality solutions to continuous optimization problems. The method, called continuous extremal optimization(CEO), can be considered as an extension of extremal optimization(EO) and is consisted of two components, one is with responsibility for global searching and the other is with responsibility for local searching. With only one adjustable parameter, the CEO's performance proves competitive with more elaborate stochastic optimization procedures. We demonstrate it on a well known continuous optimization problem: the Lennerd-Jones clusters optimization problem.Comment: 5 pages and 3 figure

Initial determination of the spins of the gluino and squarks at LHC

In principle particle spins can be measured from their production cross sections once their mass is approximately known. The method works in practice because spins are quantized and cross sections depend strongly on spins. It can be used to determine, for example, the spin of the top quark. Direct application of this method to supersymmetric theories will have to overcome the challenge of measuring mass at the LHC, which could require high statistics. In this article, we propose a method of measuring the spins of the colored superpatners by combining rate information for several channels and a set of kinematical variables, without directly measuring their masses. We argue that such a method could lead to an early determination of the spin of gluino and squarks. This method can be applied to the measurement of spin of other new physics particles and more general scenarios.Comment: 23 pages, 8 figures, minor change

PM_{2.5} reductions in Chinese cities from 2013 to 2019 remain significant despite the inflating effects of meteorological conditions

Air pollution is a major environmental issue in China and imposes severe health burdens on Chinese citizens. Consequently, China has deployed a series of control measures to mitigate fine particulate matter (PM_{2.5}). However, the extent to which these measures have been effective is obscured by the existence of confounding meteorological effects. Here, we use a newly developed reduced-form model that can address emission-driven PM_{2.5} trends and control for meteorological effects to examine the level of PM_{2.5} reduction across 367 cities since the introduction of the Air Pollution Prevention and Control Action Plan (the Plan) in 2013. Our findings show that, on average, the national annual mean level of PM_{2.5} decreased by 34% from 2013 to 2019 after the removal of meteorological effects, about 10% less than the reduction level officially observed. Despite this difference, assuming that current control efforts continue through 2035, the long-term air-quality target of 35 μg/m^{3} as determined by the recently updated Plan will be met