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K. Sneppen
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Signaling pathways and networks determine the ability to communicate in systems ranging from living cells to human society. We investigate how the network structure constrains communication in social-, man-made and biological networks. We find that human networks of governance and collaboration are predictable on teat-a-teat level, reflecting well defined pathways, but globally inefficient. In contrast, the Internet tends to have better overall communication abilities, more alternative pathways, and is therefore more robust. Between these extremes the molecular network of Saccharomyces cerevisea is more similar to the simpler social systems, whereas the pattern of interactions in the more complex Drosophilia melanogaster, resembles the robust Internet.
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We train embodied agents to play Visual Hide and Seek where a prey must navigate in a simulated environment in order to avoid capture from a predator. We place a variety of obstacles in the environment for the prey to hide behind, and we only give the agents partial observations of their environment using an egocentric perspective. Although we train the model to play this game from scratch, experiments and visualizations suggest that the agent learns to predict its own visibility in the environment. Furthermore, we quantitatively analyze how agent weaknesses, such as slower speed, effect the learned policy. Our results suggest that, although agent weaknesses make the learning problem more challenging, they also cause more useful features to be learned. Our project website is available at: http://www.cs.columbia.edu/ ~bchen/visualhideseek/.
We use $sim$83,000 star-forming galaxies at $0.04<z<0.3$ from the Sloan Digital Sky Survey to study the so-called fundamental metallicity relation (FMR) and report on the disappearance of its anti-correlation between metallicity and star formation rate (SFR) when using the new metallicity indicator recently proposed by Dopita et al. In this calibration, metallicity is primarily sensitive to the emission line ratio [NII]$lambda$6584 / [SII]$lambdalambda$6717, 6731 that is insensitive to dilution by pristine infalling gas that may drive the FMR anti-correlation with SFR. Therefore, we conclude that the apparent disappearance of the FMR (using this new metallicity indicator) does not rule out its existence.
In this chapter we discuss how the results developed within the theory of fractals and Self-Organized Criticality (SOC) can be fruitfully exploited as ingredients of adaptive network models. In order to maintain the presentation self-contained, we first review the basic ideas behind fractal theory and SOC. We then briefly review some results in the field of complex networks, and some of the models that have been proposed. Finally, we present a self-organized model recently proposed by Garlaschelli et al. [Nat. Phys. 3, 813 (2007)] that couples the fitness network model defined by Caldarelli et al. [Phys. Rev. Lett. 89, 258702 (2002)] with the evolution model proposed by Bak and Sneppen [Phys. Rev. Lett. 71, 4083 (1993)] as a prototype of SOC. Remarkably, we show that the results obtained for the two models separately change dramatically when they are coupled together. This indicates that self-organized networks may represent an entirely novel class of complex systems, whose properties cannot be straightforwardly understood in terms of what we have learnt so far.
We investigate the connection between the dynamics of synchronization and the modularity on complex networks. Simulating the Kuramotos model in complex networks we determine patterns of meta-stability and calculate the modularity of the partition these patterns provide. The results indicate that the more stable the patterns are, the larger tends to be the modularity of the partition defined by them. This correlation works pretty well in homogeneous networks (all nodes have similar connectivity) but fails when networks contain hubs, mainly because the modularity is never improved where isolated nodes appear, whereas in the synchronization process the characteristic of hubs is to have a large stability when forming its own community.
Gluinos that result in classic large missing transverse momentum signatures at the LHC have been excluded by 2011 searches if they are lighter than around 800 GeV. This adds to the tension between experiment and supersymmetric solutions of the naturalness problem, since the gluino is required to be light if the electroweak scale is to be natural. Here, we examine natural scenarios where supersymmetry is present, but was hidden from 2011 searches due to violation of R-parity and the absence of a large missing transverse momentum signature. Naturalness suggests that third generation states should dominate gluino decays and we argue that this leads to a generic signature in the form of same-sign, flavour-ambivalent leptons, without large missing transverse momentum. As a result, searches in this channel are able to cover a broad range of scenarios with some generality and one should seek gluinos that decay in this way with masses below a TeV. We encourage the LHC experiments to tailor a search for supersymmetry in this form. We consider a specific case that is good at hiding: baryon number violation, and estimate that the most constraining existing search from 2011 data implies a lower bound on the gluino mass of 550 GeV.
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