A Symmetric Free Energy Based Multi-Component Lattice Boltzmann Method

We present a lattice Boltzmann algorithm based on an underlying free energy that allows the simulation of the dynamics of a multicomponent system with an arbitrary number of components. The thermodynamic properties, such as the chemical potential of each component and the pressure of the overall system, are incorporated in the model. We derived a symmetrical convection diffusion equation for each component as well as the Navier Stokes equation and continuity equation for the overall system. The algorithm was verified through simulations of binary and ternary systems. The equilibrium concentrations of components of binary and ternary systems simulated with our algorithm agree well with theoretical expectations.Comment: 7 pager, 4 figure

Corrections to di-Higgs boson production with light stops and modified Higgs couplings

The Higgs pair production in gluon fusion is a sensitive probe of beyond-Standard Model (BSM) phenomena and its detection is a major goal for the LHC and higher energy hadron collider experiments. In this work we reanalyze the possible modifications of the Higgs pair production cross section within low energy supersymmetry models. We show that the supersymmetric contributions to the Higgs pair production cross section are strongly correlated with the ones of the single Higgs production in the gluon fusion channel. Motivated by the analysis of ATLAS and CMS Higgs production data, we show that the scalar superpartners' contributions may lead to significant modification of the di-Higgs production rate and invariant mass distribution with respect to the SM predictions. We also analyze the combined effects on the di-Higgs production rate of a modification of the Higgs trilinear and top-quark Yukawa couplings in the presence of light stops. In particular, we show that due to the destructive interference of the triangle and box amplitude contributions to the di-Higgs production cross section, even a small modification of the top-quark Yukawa coupling can lead to a significant increase of the di-Higgs production rate.Comment: 33 pages, 13 figures v2: minor improvements, PRD versio

Probing the Electroweak Phase Transition at the LHC

We study the correlation between the value of the triple Higgs coupling and the nature of the electroweak phase transition. We use an effective potential approach, including higher order, non-renormalizable terms coming from integrating out new physics. We show that if only the dimension six operators are considered, large positive deviations of the triple Higgs coupling from its Standard Model (SM) value are predicted in the regions of parameter space consistent with a strong first order electroweak phase transition (SFOEPT). We also show that at higher orders sizable and negative deviations of the triple Higgs coupling may be obtained, and the sign of the corrections tends to be correlated with the order of the phase transition. We also consider a singlet extension of the SM, which allows us to establish the connection with the effective field theory (EFT) approach and analyze the limits of its validity. Furthermore, we study how to probe the triple Higgs coupling from the double Higgs production at the LHC. We show that selective cuts in the invariant mass of the two Higgs bosons should be used, to maximize the sensitivity for values of the triple Higgs coupling significantly different from the Standard Model one.Comment: 43 pages, 4 figure

Are complex systems hard to evolve?

Evolutionary complexity is here measured by the number of trials/evaluations needed for evolving a logical gate in a non-linear medium. Behavioural complexity of the gates evolved is characterised in terms of cellular automata behaviour. We speculate that hierarchies of behavioural and evolutionary complexities are isomorphic up to some degree, subject to substrate specificity of evolution and the spectrum of evolution parameters

Impact of a non-uniform charge distribution on virus assembly

Many spherical viruses encapsulate their genome in protein shells with icosahedral symmetry. This process is spontaneous and driven by electrostatic interactions between positive domains on the virus coat proteins and the negative genome. We model the effect of the icosahedral charge distribution from the protein shell instead of uniform using a mean-field theory. We find that the non-uniform charge distribution strongly affects the optimal genome length, and that it can explain the experimentally observed phenomenon of overcharging of virus and virus-like particles

Role of inertia in two-dimensional deformation and breakup of a droplet

We investigate by Lattice Boltzmann methods the effect of inertia on the deformation and break-up of a two-dimensional fluid droplet surrounded by fluid of equal viscosity (in a confined geometry) whose shear rate is increased very slowly. We give evidence that in two dimensions inertia is {\em necessary} for break-up, so that at zero Reynolds number the droplet deforms indefinitely without breaking. We identify two different routes to breakup via two-lobed and three-lobed structures respectively, and give evidence for a sharp transition between these routes as parameters are varied.Comment: 4 pages, 4 figure

Exploring the assortativity-clustering space of a network's degree sequence

Nowadays there is a multitude of measures designed to capture different aspects of network structure. To be able to say if the structure of certain network is expected or not, one needs a reference model (null model). One frequently used null model is the ensemble of graphs with the same set of degrees as the original network. In this paper we argue that this ensemble can be more than just a null model -- it also carries information about the original network and factors that affect its evolution. By mapping out this ensemble in the space of some low-level network structure -- in our case those measured by the assortativity and clustering coefficients -- one can for example study how close to the valid region of the parameter space the observed networks are. Such analysis suggests which quantities are actively optimized during the evolution of the network. We use four very different biological networks to exemplify our method. Among other things, we find that high clustering might be a force in the evolution of protein interaction networks. We also find that all four networks are conspicuously robust to both random errors and targeted attacks