3,019 research outputs found

    Gravitational perturbations of the Higgs field

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    We study the possible effects of classical gravitational backgrounds on the Higgs field through the modifications induced in the one-loop effective potential and the vacuum expectation value of the energy-momentum tensor. We concentrate our study on the Higgs self-interaction contribution in a perturbed FRW metric. For weak and slowly varying gravitational fields, a complete set of mode solutions for the Klein-Gordon equation is obtained to leading order in the adiabatic approximation. Dimensional regularization has been used in the integral evaluation and a detailed study of the integration of nonrational functions in this formalism has been presented. As expected, the regularized effective potential contains the same divergences as in flat spacetime, which can be renormalized without the need of additional counterterms. We find that, in contrast with other regularization methods, even though metric perturbations affect the mode solutions, they do not contribute to the leading adiabatic order of the potential. We also obtain explicit expressions of the complete energy-momentum tensor for general nonminimal coupling in terms of the perturbed modes. The corresponding leading adiabatic contributions are also obtained.Comment: 15 pages. Version accepted for publication in PRD. Error corrected in the angular integration in Appendix B. Conclusions changed. New section include

    Dark matter distribution in the Draco dwarf from velocity moments

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    We study the distribution of dark matter in the Draco dwarf spheroidal galaxy by modelling the moments of the line-of-sight velocity distribution of stars obtained from new velocity data of Wilkinson et al. The luminosity distribution is approximated by a Sersic profile fitted to the data by Odenkirchen et al. We assume that the dark matter density profile is given by a formula with an inner cusp and an outer exponential cut-off, as recently proposed by Kazantzidis et al. as a result of simulations of tidal stripping of dwarfs by the potential of the Milky Way. The dark matter distribution is characterized by the total dark mass and the cut-off radius. The models have arbitrary velocity anisotropy parameter assumed to be constant with radius. We estimate the three parameters by fitting both the line-of-sight velocity dispersion and kurtosis profiles, which allows us to break the degeneracy between the mass distribution and velocity anisotropy. The results of the fitting procedure turn out to be very different depending on the stellar sample considered, that is on our choice of stars with discrepant velocities to be discarded as interlopers. For our most reliable sample, the model parameters remain weakly constrained, but the robust result is the preference for weakly tangential stellar orbits and high mass-to-light ratios. The best-fitting total mass is then 7 10^7 M_sun, much lower than recent estimates, while the mass-to-light ratio is M/L_V = 300 and almost constant with radius. If the binary fraction in the stellar population of Draco turns out to be significant, the kurtosis of the global velocity distribution will be smaller and the orbits inferred will be more tangential, while the resulting mass estimate lower.Comment: 11 pages, 8 figures, accepted for publication in MNRA

    Dark Matter in Draco: new considerations of the expected gamma flux in IACTs

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    A new revision of the gamma flux that we expect to detect in Imaging Atmospheric Cherenkov Telescopes (IACTs) from SUSY dark matter annihilation in the Draco dSph is presented using the dark matter density profiles compatible with the latest observations. This revision takes also into account the important effect of the Point Spread Function (PSF) of the Cherenkov telescope. We show that this effect is crucial in the way we will observe and interpret a possible signal profile in the telescope. Given these new considerations, some light can be shed on the recent signal excess reported by the CACTUS experiment.Comment: 7 pages, 5 figures, to appear in the Proceedings of the workshop "The dark side of the Universe", Madrid, June 20-24, 200

    Coupled equations for KĂ€hler metrics and Yang-Mills connections

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    We study equations on a principal bundle over a compact complex manifold coupling a connection on the bundle with a Kahler structure on the base. These equations generalize the conditions of constant scalar curvature for a Kahler metric and Hermite-Yang-Mills for a connection. We provide a moment map interpretation of the equations and study obstructions for the existence of solutions, generalizing the Futaki invariant, the Mabuchi K-energy and geodesic stability. We finish by giving some examples of solutions.Comment: 61 pages; v2: introduction partially rewritten; minor corrections and improvements in presentation, especially in Section 4; added references; v3: To appear in Geom. Topol. Minor corrections and improvements, following comments by referee

    Band topology and quantum spin Hall effect in bilayer graphene

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    We consider bilayer graphene in the presence of spin orbit coupling, to assess its behavior as a topological insulator. The first Chern number nn for the energy bands of single and bilayer graphene is computed and compared. It is shown that for a given valley and spin, nn in a bilayer is doubled with respect to the monolayer. This implies that bilayer graphene will have twice as many edge states as single layer graphene, which we confirm with numerical calculations and analytically in the case of an armchair terminated surface. Bilayer graphene is a weak topological insulator, whose surface spectrum is susceptible to gap opening under spin-mixing perturbations. We also assess the stability of the associated topological bulk state of bilayer graphene under various perturbations. Finally, we consider an intermediate situation in which only one of the two layers has spin orbit coupling, and find that although individual valleys have non-trivial Chern numbers, the spectrum as a whole is not gapped, so that the system is not a topological insulator.Comment: 9 pages. 9 figures include

    Gate-controlled conductance through bilayer graphene ribbons

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    We study the conductance of a biased bilayer graphene flake with monolayer nanoribbon contacts. We find that the transmission through the bilayer ribbon strongly depends on the applied bias between the two layers and on the relative position of the monolayer contacts. Besides the opening of an energy gap on the bilayer, the bias allows to tune the electronic density on the bilayer flake, making possible the control of the electronic transmission by an external parameter.Comment: 5 pages, 5 figures include

    Astrophysical implications of the proton-proton cross section updates

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    The p(p,e^+ \nu_e)^2H reaction rate is an essential ingredient for theoretical computations of stellar models. In the past several values of the corresponding S-factor have been made available by different authors. Prompted by a recent evaluation of S(E), we analysed the effect of the adoption of different proton-proton reaction rates on stellar models, focusing, in particular, on the age of mid and old stellar clusters (1-12 Gyr) and on standard solar model predictions. By comparing different widely adopted p(p,e^+ \nu_e)^2H reaction rates, we found a maximum difference in the temperature regimes typical of main sequence hydrogen-burning stars (5x10^6 - 3x10^7 K) of about 3%. Such a variation translates into a change of cluster age determination lower than 1%. A slightly larger effect is observed in the predicted solar neutrino fluxes with a maximum difference, in the worst case, of about 8%. Finally we also notice that the uncertainty evaluation of the present proton-proton rate is at the level of few \permil, thus the p(p,e^+ \nu_e)^2H reaction rate does not constitute anymore a significant uncertainty source in stellar models.Comment: accepte

    A network-based approach for predicting key enzymes explaining metabolite abundance alterations in a disease phenotype

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    <p>Background The study of metabolism has attracted much attention during the last years due to its relevance in various diseases. The advance in metabolomics platforms allows us to detect an increasing number of metabolites in abnormal high/low concentration in a disease phenotype. Finding a mechanistic interpretation for these alterations is important to understand pathophysiological processes, however it is not an easy task. The availability of genome scale metabolic networks and Systems Biology techniques open new avenues to address this question.</p> <p>Results In this article we present a novel mathematical framework to find enzymes whose malfunction explains the accumulation/depletion of a given metabolite in a disease phenotype. Our approach is based on a recently introduced pathway concept termed Carbon Flux Paths (CFPs), which extends classical topological definition by including network stoichiometry. Using CFPs, we determine the Connectivity Curve of an altered metabolite, which allows us to quantify changes in its pathway structure when a certain enzyme is removed. The influence of enzyme removal is then ranked and used to explain the accumulation/depletion of such metabolite. For illustration, we center our study in the accumulation of two metabolites (L-Cystine and Homocysteine) found in high concentration in the brain of patients with mental disorders. Our results were discussed based on literature and found a good agreement with previously reported mechanisms. In addition, we hypothesize a novel role of several enzymes for the accumulation of these metabolites, which opens new strategies to understand the metabolic processes underlying these diseases.</p> <p>Conclusions With personalized medicine on the horizon, metabolomic platforms are providing us with a vast amount of experimental data for a number of complex diseases. Our approach provides a novel apparatus to rationally investigate and understand metabolite alterations under disease phenotypes. This work contributes to the development of Systems Medicine, whose objective is to answer clinical questions based on theoretical methods and high-throughput “omics” data.</p&gt
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