Integer Quantum Hall Effect in Trilayer Graphene

The Integer Quantum Hall Effect (IQHE) is a distinctive phase of two-dimensional electronic systems subjected to a perpendicular magnetic field. Thus far, the IQHE has been observed in semiconductor heterostructures and in mono- and bi-layer graphene. Here we report on the IQHE in a new system: trilayer graphene. Experimental data are compared with self-consistent Hartree calculations of the Landau levels for the gated trilayer. The plateau structure in the Hall resistivity determines the stacking order (ABA versus ABC). We find that the IQHE in ABC trilayer graphene is similar to that in the monolayer, except for the absence of a plateau at filling factor v=2. At very low filling factor, the Hall resistance vanishes due to the presence of mixed electron and hole carriers induced by disorder.Comment: 5 pages, 4 figure

Cosmological inference including massive neutrinos from the matter power spectrum: biases induced by uncertainties in the covariance matrix

Data analysis from upcoming large galaxy redshift surveys, such as Euclid and DESI will significantly improve constraints on cosmological parameters. To optimally extract the information from these galaxy surveys, it is important to control with a high level of confidence the uncertainty and bias arising from the estimation of the covariance that affects the inference of cosmological parameters. In this work, we are addressing two different but closely related issues: (i) the sampling noise present in a covariance matrix estimated from a finite set of simulations and (ii) the impact on cosmological constraints of the non-Gaussian contribution to the covariance matrix of the power spectrum. We focus on the parameter estimation obtained from fitting the matter power spectrum in real space, using the DEMNUni N-body simulations. Regarding the first issue, we adopt two different approaches to reduce the sampling noise in the precision matrix that propagates in the parameter space: on the one hand using an alternative estimator of the covariance matrix based on a non-linear shrinkage, NERCOME; and on the other hand employing a method of fast generation of approximate mock catalogs, COVMOS. We find that NERCOME can significantly reduce the noise induced on the posterior distribution of parameters, but at the cost of a systematic overestimation of the error bars on the cosmological parameters. We show that using a COVMOS covariance matrix estimated from a large number of realisations (10~000) results in unbiased cosmological constraints. Regarding the second issue, we quantify the impact on cosmological constraints of the non-Gaussian part of the power spectrum covariance purely coming from non-linear clustering. We find that when this term is neglected, both the errors and central values of the estimated parameters are affected for a scale cut \kmax > 0.2\ \invMpc.Comment: 21 pages, 2 appendices, 20 figures. Submitted to A&

Identification of thiosulfate- and sulfur -reducing bacteria unable to reduce sulfate in ricefield soils

Eighteen strains of anaerobic thiosulfate-reducing bacteria unable to use sulfate as electron acceptor (TSRnSR) were isolated from four ricefield soils originating from France and the Philippines, using peptides as energy sources, H2 as electron donor, thiosulfate as electron acceptors, and four enrichment methods to vary the selection pressure. They were strict proteolytic asaccharolytic anaerobes producing H2S when grown on thiosulfate + H2. They exhibited the same RFLP profile (11 restriction enzymes tested). Partial sequencing of the 16S rDNA showed that they belonged to the genus Clostridium and were phylogenetically related to C. subterminale. DNA-DNA hybridization of a representative strain with the closest C. subterminale strain (DSM 6970T) yielded a value of 68.9%. Previous counts of TSRnSR in ricefield soils, their identification as Clostridium strains, and the known ubiquity of this genus in such soils indicate that TSRnSR may play a significant role in S cycling in some wetland soils. (Résumé d'auteur

A Survey on Approximation Mechanism Design without Money for Facility Games

In a facility game one or more facilities are placed in a metric space to serve a set of selfish agents whose addresses are their private information. In a classical facility game, each agent wants to be as close to a facility as possible, and the cost of an agent can be defined as the distance between her location and the closest facility. In an obnoxious facility game, each agent wants to be far away from all facilities, and her utility is the distance from her location to the facility set. The objective of each agent is to minimize her cost or maximize her utility. An agent may lie if, by doing so, more benefit can be obtained. We are interested in social choice mechanisms that do not utilize payments. The game designer aims at a mechanism that is strategy-proof, in the sense that any agent cannot benefit by misreporting her address, or, even better, group strategy-proof, in the sense that any coalition of agents cannot all benefit by lying. Meanwhile, it is desirable to have the mechanism to be approximately optimal with respect to a chosen objective function. Several models for such approximation mechanism design without money for facility games have been proposed. In this paper we briefly review these models and related results for both deterministic and randomized mechanisms, and meanwhile we present a general framework for approximation mechanism design without money for facility games

Stochastic bias of colour-selected BAO tracers by joint clustering-weak lensing analysis

The baryon acoustic oscillation (BAO) feature in the two-point correlation function of galaxies supplies a standard ruler to probe the expansion history of the Universe. We study here several galaxy selection schemes, aiming at building an emission-line galaxy (ELG) sample in the redshift range $0.6<z<1.7$, that would be suitable for future BAO studies, providing a highly biased galaxy sample. We analyse the angular galaxy clustering of galaxy selections at the redshifts 0.5, 0.7, 0.8, 1 and 1.2 and we combine this analysis with a halo occupation distribution (HOD) model to derive the properties of the haloes these galaxies inhabit, in particular the galaxy bias on large scales. We also perform a weak lensing analysis (aperture statistics) to extract the galaxy bias and the cross-correlation coefficient and compare to the HOD prediction. We apply this analysis on a data set composed of the photometry of the deep co-addition on Sloan Digital Sky Survey (SDSS) Stripe 82 (225 deg$^2$), of Canda-France-Hawai Telescope/Stripe 82 deep \emph{i}-band weak lensing survey and of the {\it Wide-Field Infrared Survey Explorer}infrared photometric band W1. The analysis on the SDSS-III/constant mass galaxies selection at $z=0.5$ is in agreement with previous studies on the tracer, moreover we measure its cross-correlation coefficient $r=1.16\pm0.35$. For the higher redshift bins, we confirm the trends that the brightest galaxy populations selected are strongly biased ($b>1.5$), but we are limited by current data sets depth to derive precise values of the galaxy bias. A survey using such tracers of the mass field will guarantee a high significance detection of the BAO.Comment: 17 pages, 15 figures, submitted to MNRA

LP-based Covering Games with Low Price of Anarchy

We present a new class of vertex cover and set cover games. The price of anarchy bounds match the best known constant factor approximation guarantees for the centralized optimization problems for linear and also for submodular costs -- in contrast to all previously studied covering games, where the price of anarchy cannot be bounded by a constant (e.g. [6, 7, 11, 5, 2]). In particular, we describe a vertex cover game with a price of anarchy of 2. The rules of the games capture the structure of the linear programming relaxations of the underlying optimization problems, and our bounds are established by analyzing these relaxations. Furthermore, for linear costs we exhibit linear time best response dynamics that converge to these almost optimal Nash equilibria. These dynamics mimic the classical greedy approximation algorithm of Bar-Yehuda and Even [3]