A neutral two-flavor LOFF color superconductor
In this Letter we construct analytically a LOFF color superconducting state that is both color and charge neutral using the weak coupling approximation. We demonstrate that this state is free from chromomagnetic instabilities. Its relevance to the realistic quark matter at moderately high baryon density is discussed.

title: Gauge field fluctuations and first-order phase transition in color superconductivity.
abstract: We study the gauge field fluctuations in dense quark matter and determine the temperature of the induced first-order phase transition to the color-superconducting phase in weak coupling. We find that the local approximation of the coupling between the gauge potential and the order parameter, employed in the Ginzburg-Landau theory, has to be modified by restoring the full momentum dependence of the polarization function of gluons in the superconducting phase.

title: Fermion Field on a Random Lattice
abstract: On etudie les modes zeros d'une action fermion sur un reseau aleatoire. On calcule les valeurs propres basses de l'action et on discute leur distribution

title: Linearized analysis of the Dvali–Gabadadze–Porrati brane model
abstract: We solve the Einstein equations in the Dvali–Gabadadze–Porrati model with a static, spherically symmetric matter distribution on the physical brane and obtain an exact expression for the gravitational field outside the source to the first order in the gravitational coupling. Although, this expression when confined on the physical brane reproduces the correct 4− D Newtonian potential for distances r s ⪡ r ⪡ λ , where λ is a characteristic length scale of the model, it does not coincide with the standard linearized form of the 4− D Schwarzschild metric. The solution reproduces the 5− D Schwarzschild metric in the linearized approximation for r ⪢ λ .

title: Bosonization of lattice fermions.
abstract: For any purely fermionic system on a lattice in arbitrary space dimension we prove that there is a different but well-defined system on the same lattice, consisting of both [ital bona] [ital fide] fermions and bosons with an interaction depending on a parameter [lambda], which characterizes a same-site repulsion between particles. The energy spectrum and the scattering matrix of the former are identical to those in the finite energy sector of the latter, in the limit [lambda][r arrow][infinity] (i.e., hard-core repulsion). This general theorem is applied to a resonance-boson model in a lattice fermion system, whose solution may have relevance to high-[ital T][sub [ital c]] superconductivity.

title: String tensions of SU(3) gauge theory on a random lattice
abstract: The SU(3) gauge theory on a random lattice is studied using the Monte Carlo method. The string tensions are measured. A scaling window around g 0 −2 = 1.4 is detected and the scale parameter is estimated.

title: Fermions in a global monopole background
abstract: We study the scattering of fermions in a “global monopole” background metric. This is the four-dimensional analogue of the scattering on a cone in three dimensions. The scattering amplitude is exactly obtained. We then study massless fermion-dyon systems in such a background metric. The density of the S -wave fermion condensate is found to be given by a constant times the flat space value of Callan and Rubakov.

title: Measurement of the cross section of high transverse momentum $\it{Z\rightarrow b\bar{b}}$ production in proton--proton collisions at $\sqrt{s}=8 TeV$ with the ATLAS Detector

title: Various topics in field theory

title: A neural network clustering algorithm for the ATLAS silicon pixel detector
abstract: A novel technique to identify and split clusters created by multiple charged particles in the ATLAS pixel detector using a set of artificial neural networks is presented. Such merged clusters are a common feature of tracks originating from highly energetic objects, such as jets. Neural networks are trained using Monte Carlo samples produced with a detailed detector simulation. This technique replaces the former clustering approach based on a connected component analysis and charge interpolation. The performance of the neural network splitting technique is quantified using data from proton-proton collisions at the LHC collected by the ATLAS detector in 2011 and from Monte Carlo simulations. This technique reduces the number of clusters shared between tracks in highly energetic jets by up to a factor of three. It also provides more precise position and error estimates of the clusters in both the transverse and longitudinal impact parameter resolution.