Step-like features on caloric effects of graphenes

We considered a graphene nano-ribbon with a longitudinal electric field (along $x$ direction) and a transversal magnetic field (along $z$ direction), and then observe (i) the electrocaloric effect ruled by an applied magnetic field and (ii) the magnetocaloric effect ruled by an applied electric field. We focused our attention to the limit of low temperatures, and then observed interesting step-like features. For each filled Landau level $n$, created by the applied magnetic field, both caloric effects increase proportionally to $n+1/2$; and this step measures either important graphene properties (like Fermi velocity) or quantum fundamental quantities (like Planck constant and magnetic flux quantum)

Phase diagram of a 2D Ising model within a nonextensive approach

In this work we report Monte Carlo simulations of a 2D Ising model, in which the statistics of the Metropolis algorithm is replaced by the nonextensive one. We compute the magnetization and show that phase transitions are present for $q\neq 1$. A $q -$ phase diagram (critical temperature vs. the entropic parameter $q$) is built and exhibits some interesting features, such as phases which are governed by the value of the entropic index $q$. It is shown that such phases favors some energy levels of magnetization states. It is also showed that the contribution of the Tsallis cutoff is essential to the existence of phase transitions

First-order classical Lagrangians for the nonminimal Standard-Model Extension

In this paper, we derive the general leading-order classical Lagrangian covering all fermion operators of the nonminimal Standard-Model Extension (SME). Such a Lagrangian is considered to be the point-particle analog of the effective field theory description of Lorentz violation that is provided by the SME. First of all, a suitable Ansatz is made for the Lagrangian of the spin-degenerate operators $\hat{a}$, $\hat{c}$, $\hat{e}$, and $\hat{f}$ at leading order in Lorentz violation. The latter is shown to satisfy the set of five nonlinear equations that govern the map from the field theory to the classical description. After doing so, the second step is to propose results for the spin-nondegenerate operators $\hat{b}$, $\hat{d}$, $\hat{H}$, and $\hat{g}$. Although these are more involved than the Lagrangians for the spin-degenerate ones, an analytical proof of their validity is viable, nevertheless. The final step is to combine both findings to produce a generic Lagrangian for the complete set of Lorentz-violating operators that is consistent with the known minimal and nonminimal Lagrangians found in the literature so far. The outcome reveals the leading-order structure of the classical SME analog. It can be of use for both phenomenological studies of classical bodies in gravitational fields and conceptual work on explicit Lorentz violation in gravity. Furthermore, there may be a possible connection to Finsler geometry.Comment: 23 page

Crystallization of a quasi-two-dimensional granular fluid

We experimentally investigate the crystallization of a uniformly heated quasi-2D granular fluid as a function of filling fraction. Our experimental results for the Lindemann melting criterion, the radial distribution function, the bond order parameter and the statistics of topological changes at the particle level are the same as those found in simulations of equilibrium hard disks. This direct mapping suggests that the study of equilibrium systems can be effectively applied to study non-equilibrium steady states like those found in our driven and dissipative granular system.Comment: 4 pages, 4 figures, submitted to Phys. Rev. Let

Simulation-based Estimation of Mean and Standard Deviation for Meta-analysis via Approximate Bayesian Computation (ABC)

Background: When conducting a meta-analysis of a continuous outcome, estimated means and standard deviations from the selected studies are required in order to obtain an overall estimate of the mean effect and its confidence interval. If these quantities are not directly reported in the publications, they need to must be estimated from other reported summary statistics, such as the median, the minimum, the maximum, and quartiles. Methods: We propose a simulation-based estimation approach using the Approximate Bayesian Computation (ABC) technique for estimating mean and standard deviation based on various sets of summary statistics found in published studies. We conduct a simulation study to compare the proposed ABC method with the existing methods of Hozo et al. (2005), Bland (2015), and Wan et al. (2014). Results: In the estimation of the standard deviation, our ABC method performs best in skewed or heavy-tailed distributions. The average relative error (ARE) approaches zero as sample size increases. In the normal distribution, our ABC performs well. However, the Wan et al. method is best since it is based on the normal distribution assumption. When the distribution is skewed or heavy-tailed, the ARE of Wan et al. moves away from zero even as sample size increases. In the estimation of the mean, our ABC method is best since the AREs converge to zero. Conclusion: ABC is a flexible method for estimating the study-specific mean and standard deviation for meta-analysis, especially with underlying skewed or heavy-tailed distributions. The ABC method can be applied using other reported summary statistics such as the posterior mean and 95% credible interval when Bayesian analysis has been employed