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Real space Renormalization Group analysis of a non-mean field spin-glass

Michele Castellana 1, 2 Europhysics Letters 95, 4 (2011) 47014 A real space Renormalization Group approach is presented for a non-mean field spin-glass. This approach has been conceived in the effort to develop an alternative method to the Renormalization Group approaches based on the replica method. Indeed, non-perturbative effects in the latter are quite generally out of control,

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Randomizing genome-scale metabolic networks

Areejit Samal 1, 2, Olivier C. Martin 2, 3 PLoS ONE 6 (2011) e22295 Networks coming from protein-protein interactions, transcriptional regulation, signaling, or metabolism may appear to have ‘unusual’ properties. To quantify this, it is appropriate to randomize the network and test the hypothesis that the network is not statistically different from expected in a motivated ensemble. However, when dealing with

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Quantum Monte Carlo calculation of the zero-temperature phase diagram of the two-component fermionic hard-core gas in two dimensions

N. D. Drummond 1, 2, N. R. Cooper 1, R. J. Needs 1, G. V. Shlyapnikov 3, 4 Physical Review B 83 (2011) 195429 Motivated by potential realizations in cold-atom or cold-molecule systems, we have performed quantum Monte Carlo simulations of two-component gases of fermions in two dimensions with hard-core interactions. We have determined the gross features of the zero-temperature phase diagram, by investigating the

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Phenotypic robustness can increase phenotypic variability after non-genetic perturbations in gene regulatory circuits

Carlos Espinosa-Soto 1, 2, Olivier C. Martin 3, 4, Andreas Wagner 1, 2, 5 Journal of Evolutionary Biology 24 (2011) 1284-1297 Non-genetic perturbations, such as environmental change or developmental noise, can induce novel phenotypes. If an induced phenotype confers a fitness advantage, selection may promote its genetic stabilization. Non-genetic perturbations can thus initiate evolutionary innovation. Genetic variation that is not usually phenotypically visible may play

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Phase transitions in the distribution of the Andreev conductance of superconductor-metal junctions with many transverse modes

Kedar Damle 1, Satya N. Majumdar 2, Vikram Tripathi 1, Pierpaolo Vivo 2 Physical Review Letters 107 (2011) 177206 We compute analytically the full distribution of Andreev conductance $G_{\mathrm{NS}}$ of a metal-superconductor interface with a large number $N_c$ of transverse modes, using a random matrix approach. The probability distribution $\mathcal{P}(G_{\mathrm{NS}},N_c)$ in the limit of large $N_c$ displays a Gaussian behavior near the average

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Phase transition in the detection of modules in sparse networks

Aurelien Decelle 1, Florent Krzakala 2, Cristopher Moore 3, 4, Lenka Zdeborová 5 Physical Review Letters 107 (2011) 065701 We present an asymptotically exact analysis of the problem of detecting communities in sparse random networks. Our results are also applicable to detection of functional modules, partitions, and colorings in noisy planted models. Using a cavity method analysis, we unveil a phase transition from a

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