Coulomb Screening of 2D Massive Dirac Fermions

A model of 2D massive Dirac fermions, interacting with a instantaneous $1/r$ Coulomb interaction, is presented to mimic the physics of gapped graphene. The static polarization function is calculated explicitly to analyze screening effect at the finite temperature and density. Results are compared with the massless case . We also show that various other works can be reproduced within our model in a straightforward and unified manner

Finite-temperature Screening and the Specific Heat of Doped Graphene Sheets

At low energies, electrons in doped graphene sheets are described by a massless Dirac fermion Hamiltonian. In this work we present a semi-analytical expression for the dynamical density-density linear-response function of noninteracting massless Dirac fermions (the so-called "Lindhard" function) at finite temperature. This result is crucial to describe finite-temperature screening of interacting massless Dirac fermions within the Random Phase Approximation. In particular, we use it to make quantitative predictions for the specific heat and the compressibility of doped graphene sheets. We find that, at low temperatures, the specific heat has the usual normal-Fermi-liquid linear-in-temperature behavior, with a slope that is solely controlled by the renormalized quasiparticle velocity.Comment: 9 pages, 5 figures, Submitted to J. Phys.

Effect of disorder on the ground-state properties of graphene

We calculate the ground-state energy of Dirac electrons in graphene in the presence of disorder. We take randomly distributed charged impurities at a fixed distance from the graphene sheet and surface fluctuations (ripples) as the main scattering mechanisms. Mode-coupling approach to scattering rate and random-phase approximation for ground-state energy incorporating the many-body interactions and the disorder effects yields good agreement with experimental inverse compressibility.Comment: Extended introduction and discussion. To appear in Phys. Rev.

Plasmons in layered structures including graphene

We investigate the optical properties of layered structures with graphene at the interface for arbitrary linear polarization at finite temperature including full retardation by working in the Weyl gauge. As a special case, we obtain the full response and the related dielectric function of a layered structure with two interfaces. We apply our results to discuss the longitudinal plasmon spectrum of several single and double layer devices such as systems with finite and zero electronic densities. We further show that a nonhomogeneous dielectric background can shift the relative weight of the in-phase and out-of-phase mode and discuss how the plasmonic mode of the upper layer can be tuned into an acoustic mode with specific sound velocity.Comment: 18 pages, 6 figure

Assisted reproductive outcomes in women with different polycystic ovary syndrome phenotypes: The predictive value of anti-Müllerian hormone

This cross-sectional study aimed to evaluate IVF/intracytoplasmic sperm injection (ICSI) outcomes in different polycystic ovary syndrome (PCOS) phenotypes (A, B, C and D) compared with a control group and the predictive values of serum anti-Müllerian hormone (AMH) in PCOS phenotypes for main outcomes. This study evaluated 386 PCOS women and 350 patients with male factor infertility. Women with phenotypes A and C had significantly higher concentrations of AMH than those with phenotype B (P < 0.001). Clinical pregnancy rate (CPR) in the phenotype D group (53.3) was higher than other groups (32.5, 26.4 and 36.8, respectively, in phenotypes A, B and C), but not to a significant level. Multivariable regression analysis, after adjusting for women's age and body mass index, revealed that PCOS phenotypes A and B were associated with a decreased CPR compared with the control group (odds ratio OR: 0.46, confidence interval CI: 0.26-0.8, P = 0.007 and OR: 0.34, CI: 0.18-0.62, P = 0.001, respectively). It seems a combination of hyperandrogenism and chronic anovulation is associated with a negative impact on the CPR in these patients. These results demonstrated that AMH concentration is related to PCO morphology but not predictive for CPR and live birth rate. © 2016 Reproductive Healthcare Ltd. Published by Elsevier Ltd. All rights reserved

Graphene plasmonics

Two rich and vibrant fields of investigation, graphene physics and plasmonics, strongly overlap. Not only does graphene possess intrinsic plasmons that are tunable and adjustable, but a combination of graphene with noble-metal nanostructures promises a variety of exciting applications for conventional plasmonics. The versatility of graphene means that graphene-based plasmonics may enable the manufacture of novel optical devices working in different frequency ranges, from terahertz to the visible, with extremely high speed, low driving voltage, low power consumption and compact sizes. Here we review the field emerging at the intersection of graphene physics and plasmonics.Comment: Review article; 12 pages, 6 figures, 99 references (final version available only at publisher's web site

Critical Behavior and Universality Classes for an Algorithmic Phase Transition in Sparse Reconstruction

Recovery of an N-dimensional, K-sparse solution x from an M-dimensional vector of measurements y for multivariate linear regression can be accomplished by minimizing a suitably penalized least-mean-square cost ||y-Hx||22+λV(x). Here H is a known matrix and V(x) is an algorithm-dependent sparsity-inducing penalty. For ‘random’ H, in the limit λ→ 0 and M, N, K→ ∞, keeping ρ= K/ N and α= M/ N fixed, exact recovery is possible for α past a critical value α c = α(ρ). Assuming x has iid entries, the critical curve exhibits some universality, in that its shape does not depend on the distribution of x. However, the algorithmic phase transition occurring at α= α c and associated universality classes remain ill-understood from a statistical physics perspective, i.e. in terms of scaling exponents near the critical curve. In this article, we analyze the mean-field equations for two algorithms, Basis Pursuit (V(x) = | | x| | 1 ) and Elastic Net (V(x)=||x||1+g2||x||22) and show that they belong to different universality classes in the sense of scaling exponents, with mean squared error (MSE) of the recovered vector scaling as λ43 and λ respectively, for small λ on the critical line. In the presence of additive noise, we find that, when α&gt; α c , MSE is minimized at a non-zero value for λ, whereas at α= α c , MSE always increases with λ. © 2019, Springer Science+Business Media, LLC, part of Springer Nature

Mean Field Analysis of Sparse Reconstruction with Correlated Variables

Sparse reconstruction algorithms aim to retrieve high-dimensional sparse signals from a limited number of measurements. A common example is LASSO or Basis Pursuit where sparsity is enforced using an ℓ -penalty together with a cost function ||y - Hx|| . For random design matrices H, a sharp phase transition boundary separates the 'good' parameter region where error-free recovery of a sufficiently sparse signal is possible and a 'bad' regime where the recovery fails. However, theoretical analysis of phase transition boundary of the correlated variables case lags behind that of uncorrelated variables. Here we use replica trick from statistical physics to show that when an N-dimensional signal x is K-sparse and H is M × N dimensional with the covariance E[H H ] = 1/M C D , with all D = 1, the perfect recovery occurs at M ∼ φ (D)K log(N/M) in the very sparse limit, where φ (D) ≥ 1, indicating need for more observations for the same degree of sparsity. 1 2 ia jb ij ab aa K K

Crisis Management: Monetary Policy Compatible with the Oil Economy

The purpose of this research is to explain monetary policy consistent with the country's economic conditions. Hence, in this paper, we tried to evaluate the two states of the central bank's reaction to the dynamic general equilibrium model adapted to the characteristics of the Oil-rich countries economy. In the first instance, the policy maker, with regard to the level of production, diverts inflation from target inflation and exchange rate policy. In the latter case, the basis for deciding the production deviation from potential production, the deviation of future inflation from target inflation and exchange rate, and in both cases, the use of policy experiences is also considered as a variable for policy