Effective inter-band coupling in MgB2 due to anharmonic phonons

We investigate the origin of the inter-band coupling in MgB2 by focusing on its unusual phononic features, namely, the strong anharmonicity of the phonons and the presence of both linear and quadratic electron-phonon interactions of the Su-Schrieffer-Heeger (SSH) type. The bare electronic Hamiltonian has two bands with intra- and inter-band hopping, which lead to two decoupled hybridized bands. The phonon Hamiltonian including the anharmonic terms is diagonalized approximately by a squeezing transformation, which causes the softening of the phonon frequency. The linear SSH coupling amplitude is reduced, consistently with the estimates from first-principle calculations. Additionally, the quadratic coupling generates an effective phonon-induced interaction between the hybridized bands, which is non-vanishing even in the limit of vanishing inter-bare-band hopping amplitude.Comment: 11 page

A model Hamiltonian for MgB2 which takes into account its unusual phononic features

Taking as a starting point the results of LDA calculations, which show that in MgB2 the phonons have a strong quartic anharmonicity and that the bond-stretching electron-phonon interaction (EPI) has both a linear and a large quadratic component, we propose a model Hamiltonian which succesfully matches a number of experimental evidences. We relate the single critical temperature for both superconducting gaps to a phonon-induced inter-band coupling whose amplitude increases with temperature. We also obtain phonon frequencies and linewidths depending on the band filling, as well as band energies and hybridization amplitudes depending on the phonon number.Comment: 19 pages, no figures, accepted on The European Physical Journal

Generalizations of the Familywise Error Rate

Consider the problem of simultaneously testing null hypotheses H_1,...,H_s. The usual approach to dealing with the multiplicity problem is to restrict attention to procedures that control the familywise error rate (FWER), the probability of even one false rejection. In many applications, particularly if s is large, one might be willing to tolerate more than one false rejection provided the number of such cases is controlled, thereby increasing the ability of the procedure to detect false null hypotheses. This suggests replacing control of the FWER by controlling the probability of k or more false rejections, which we call the k-FWER. We derive both single-step and stepdown procedures that control the k-FWER, without making any assumptions concerning the dependence structure of the p-values of the individual tests. In particular, we derive a stepdown procedure that is quite simple to apply, and prove that it cannot be improved without violation of control of the k-FWER. We also consider the false discovery proportion (FDP) defined by the number of false rejections divided by the total number of rejections (defined to be 0 if there are no rejections). The false discovery rate proposed by Benjamini and Hochberg [J. Roy. Statist. Soc. Ser. B 57 (1995) 289-300] controls E(FDP). Here, we construct methods such that, for any \gamma and \alpha, P{FDP>\gamma}\le\alpha. Two stepdown methods are proposed. The first holds under mild conditions on the dependence structure of p-values, while the second is more conservative but holds without any dependence assumptions.Comment: Published at http://dx.doi.org/10.1214/009053605000000084 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Role of the particle's stepping cycle in an asymmetric exclusion process: A model of mRNA translation

Messenger RNA translation is often studied by means of statistical-mechanical models based on the Asymmetric Simple Exclusion Process (ASEP), which considers hopping particles (the ribosomes) on a lattice (the polynucleotide chain). In this work we extend this class of models and consider the two fundamental steps of the ribosome's biochemical cycle following a coarse-grained perspective. In order to achieve a better understanding of the underlying biological processes and compare the theoretical predictions with experimental results, we provide a description lying between the minimal ASEP-like models and the more detailed models, which are analytically hard to treat. We use a mean-field approach to study the dynamics of particles associated with an internal stepping cycle. In this framework it is possible to characterize analytically different phases of the system (high density, low density or maximal current phase). Crucially, we show that the transitions between these different phases occur at different parameter values than the equivalent transitions in a standard ASEP, indicating the importance of including the two fundamental steps of the ribosome's biochemical cycle into the model.Comment: 9 pages, 9 figure

The effect of stellar migration on Galactic chemical evolution: a heuristic approach

In the last years, stellar migration in galactic discs has been the subject of several investigations. However, its impact on the chemical evolution of the Milky Way still needs to be fully quantified. In this paper, we aim at imposing some constraints on the significance of this phenomenon by considering its influence on the chemical evolution of the Milky Way thin disc. We do not investigate the physical mechanisms underlying the migration of stars. Rather, we introduce a simple, heuristic treatment of stellar migration in a detailed chemical evolution model for the thin disc of the Milky Way, which already includes radial gas flows and reproduces several observational constraints for the solar vicinity and the whole Galactic disc. When stellar migration is implemented according to the results of chemo-dynamical simulations by Minchev et. al. (2013) and finite stellar velocities of 1 km s$^{-1}$ are taken into account, the high-metallicity tail of the metallicity distribution function of long-lived thin-disc stars is well reproduced. By exploring the velocity space, we find that the migrating stars must travel with velocities in the range 0.5 -2 km s$^{-1}$ to properly reproduce the high-metallicity tail of the metallicity distribution. We confirm previous findings by other authors that the observed spread in the age-metallicity relation of solar neighbourhood stars can be explained by the presence of stars which originated at different Galactocentric distances, and we conclude that the chemical properties of stars currently observed in the solar vicinity do suggest that stellar migration is present to some extent.Comment: Accepted for publication by Ap

Panel performance: Modelling variation in sensory profiling data by multiway analysis

Sensory profiling data is essentially three-way data where samples, attributes and assessors are the three dimensions of information. It is common practice to average over the assessors and focus the analysis on the relations between samples and sensory descriptors. However, since assessor reliability can not be controlled in advance, posthoc analysis on assessors is needed to assess performance of the individual and at the panel level. For this purpose, multiway analysis is a very efficient data method as it provides information on samples, attributes and assessors, simultaneously [1]. PARAllel FACtor (PARAFAC) analysis is one of the most used multiway methods in sensory analysis [2][3]. It is based on two basic assumptions: 1) there exist latent variables behind the identified sensory descriptors describing the variation among the products; 2) assessors have different sensitivities to these common latent variables. However, assessors may perceive the factors differently, so the assumption of “common latent variables” becomes questionable. This may happen when the panel is not well trained and/or the samples present subtle differences difficult to detect. In this work a more flexible approach to the analysis of sensory data is presented. Specifically, the work proposes to use PARAFAC2 modelling [4] as it allows each assessor to have an individual idiosyncratic perceptive model. The data was obtained from a descriptive sensory analysis of organic milk samples. Results show that PARAFAC2 is very useful to highlight disagreement in the panel on specific attributes and to detect outlying assessors. In addition, by using PARAFAC2 an improvement in the description of samples is also achieved. On the other hand, PARAFAC has to be preferred to PARAFAC2 when a good panel agreement is observed, since it provides more stable solutions and no further gain in information is obtained from PARAFAC2. Finally, the work proposes an index to measure the performance of each assessor based on individual sensitivity and reproducibility