2,886 research outputs found
Gravitational perturbations of the Higgs field
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
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
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
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
We consider bilayer graphene in the presence of spin orbit coupling, to
assess its behavior as a topological insulator. The first Chern number for
the energy bands of single and bilayer graphene is computed and compared. It is
shown that for a given valley and spin, 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
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
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
<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 âomicsâ data.</p>
- âŠ