Localizing gravity on thick branes: a solution for massive KK modes of the Schroedinger equation

We generate scalar thick brane configurations in a 5D Riemannian space time which describes gravity coupled to a self-interacting scalar field. We also show that 4D gravity can be localized on a thick brane which does not necessarily respect Z_2-symmetry, generalizing several previous models based on the Randall-Sundrum system and avoiding the restriction to orbifold geometries as well as the introduction of the branes in the action by hand. We begin by obtaining a smooth brane configuration that preserves 4D Poincar'e invariance and violates reflection symmetry along the fifth dimension. The extra dimension can have either compact or extended topology, depending on the values of the parameters of the solution. In the non-compact case, our field configuration represents a thick brane with positive energy density centered at y=c_2, whereas in the compact case we get pairs of thick branes. We recast as well the wave equations of the transverse traceless modes of the linear fluctuations of the classical solution into a Schroedinger's equation form with a volcano potential of finite bottom. We solve Schroedinger equation for the massless zero mode m^2=0 and obtain a single bound wave function which represents a stable 4D graviton and is free of tachyonic modes with m^2<0. We also get a continuum spectrum of Kaluza-Klein (KK) states with m^2>0 that are suppressed at y=c_2 and turn asymptotically into plane waves. We found a particular case in which the Schroedinger equation can be solved for all m^2>0, giving us the opportunity of studying analytically the massive modes of the spectrum of KK excitations, a rare fact when considering thick brane configurations.Comment: 8 pages in latex. We corrected signs in the field equations, the expressions for the scalar field and the self-interacting potential. Due to the fact that no changes are introduced in the warp factor, the physics of the system remains the sam

Robustness of bipartite Gaussian entangled beams propagating in lossy channels

Subtle quantum properties offer exciting new prospects in optical communications. Quantum entanglement enables the secure exchange of cryptographic keys and the distribution of quantum information by teleportation. Entangled bright beams of light attract increasing interest for such tasks, since they enable the employment of well-established classical communications techniques. However, quantum resources are fragile and undergo decoherence by interaction with the environment. The unavoidable losses in the communication channel can lead to a complete destruction of useful quantum properties -- the so-called "entanglement sudden death". We investigate the precise conditions under which this phenomenon takes place for the simplest case of two light beams and demonstrate how to produce states which are robust against losses. Our study sheds new light on the intriguing properties of quantum entanglement and how they may be tamed for future applications.Comment: To be published - Nature Photonic

Mass gap for gravity localized on Weyl thick branes

We study the properties of a previously found family of thick brane configurations in a pure geometric Weyl integrable 5D space time, a non-Riemannian generalization of Kaluza-Klein (KK) theory involving a geometric scalar field. Thus the 5D theory describes gravity coupled to a self-interacting scalar field which gives rise to the structure of the thick branes. Analyzing the graviton spectrum for this class of models, we find that a particularly interesting situation arises for a special case in which the 4D graviton is separated from the KK gravitons by a mass gap. The corresponding effective Schroedinger equation has a modified Poeschl-Teller potential and can be solved exactly. Apart from the massless 4D graviton, it contains one massive KK bound state, and the continuum spectrum of delocalized KK modes. We discuss the mass hierarchy problem, and explicitly compute the corrections to Newton's law in the thin brane limit.Comment: 6 pages in Revtex, no figures, journal version, significately revised and extende

Disentanglement in Bipartite Continuous-Variable Systems

Entanglement in bipartite continuous-variable systems is investigated in the presence of partial losses, such as those introduced by a realistic quantum communication channel, e.g. by propagation in an optical fiber. We find that entanglement can vanish completely for partial losses, in a situa- tion reminiscent of so-called entanglement sudden death. Even states with extreme squeezing may become separable after propagation in lossy channels. Having in mind the potential applications of such entangled light beams to optical communications, we investigate the conditions under which entanglement can survive for all partial losses. Different loss scenarios are examined and we derive criteria to test the robustness of entangled states. These criteria are necessary and sufficient for Gaussian states. Our study provides a framework to investigate the robustness of continuous-variable entanglement in more complex multipartite systems.Comment: Phys. Rev. A (in press

Analytical results for a Bessel function times Legendre polynomials class integrals

When treating problems of vector diffraction in electromagnetic theory, the evaluation of the integral involving Bessel and associated Legendre functions is necessary. Here we present the analytical result for this integral that will make unnecessary numerical quadrature techniques or localized approximations. The solution is presented using the properties of the Bessel and associated Legendre functions.Comment: 4 page

The era of big data: Genome-scale modelling meets machine learning

With omics data being generated at an unprecedented rate, genome-scale modelling has become pivotal in its organisation and analysis. However, machine learning methods have been gaining ground in cases where knowledge is insufficient to represent the mechanisms underlying such data or as a means for data curation prior to attempting mechanistic modelling. We discuss the latest advances in genome-scale modelling and the development of optimisation algorithms for network and error reduction, intracellular constraining and applications to strain design. We further review applications of supervised and unsupervised machine learning methods to omics datasets from microbial and mammalian cell systems and present efforts to harness the potential of both modelling approaches through hybrid modelling