Soft QCD from ATLAS and CMS

Measurements of hadron production in pp collisions by the ATLAS and CMS experiments are presented, including charged particle transverse momentum, pseudorapidity and event-by-event multiplicity distributions at sqrt(s) = 0.9, 2.36 and 7 TeV, for NSD and inelastic events. Diffraction is studied with either diffraction enriched or suppressed data samples. Total inelastic cross-section as well as gap cross-section measurements are shown. Measured spectra of identified strange hadrons, reconstructed based on their decay topology, are also discussed. Comparisons to several QCD Monte Carlo models and tunes are exhibited. Results on two-particle angular correlations over a broad range of pseudorapidity and azimuthal angle in pp collisions are presented. Underlying event activity are studied with different hard probes: tracks, trackjets, calorimeter clusters, or in Drell-Yan events.Comment: Presented at the 2011 Hadron Collider Physics symposium (HCP-2011), Paris, France, November 14-18 2011, 4 pages, 4 figure

Méthodes qualitatives pour la construction et l'analyse des réseaux moléculaires SBGN

Two fundamental tasks of Systems Biology are the construction of molecular networks from experimental data, and their analysis with a view to discovering their emergent properties. With the increase of available experimental data, these two tasks can no longer be realized by hand. Based on this observation, numerous bioinformatics methods aiming at the automation of these two task have been developped.In parallel, standards aiming at defining and organizing terms of systems biology, or representing networks and mathematical models, have been developped. Among these standards, the Standard Biology Graphical Notation is composed of three languages that allow the representation of molecular networks. The two main SBGN languages are SBGN-PD for the representation of reaction networks, and SBGN-AF for the representation of influence graphs. The SBGN notation not only standardizes the representation of networks, but also gives the concepts of systems biology that are most often used to express knowledge of the field.Our work takes its root in this general background. We have developped a number of methods to construct molecular networks and analyze their dynamics. All the methods that we propose are based on qualitative formalisms, such as logics or automata networks. These formalisms have solid theoretical bases and can be used by numerous pieces of software. All our methods also rely on the biological concepts given by the SBGN standard, and can therefore be blended in the same theoretical framework.First, we introduce two sets of predicates that allow to translate any SBGN-PD or SBGN-AF network into a set of ground atoms. Then, we show how these sets of predicates can be used to reason on networks, by proposing a transformation method of SBGN-PD signaling networks into SBGN-AF influence graphs.Second, we present a first-order logic based method to construct signaling networks from experimental results. This method formalizes and automatizes biologists' reasoning using explicit reasoning rules.On the contrary to existing methods, it allows to take into account numerous types of experimental results while reconstructing precise molecular mecanisms.Third, we show a new method to compute the finite traces and attractor points of Boolean networks that model SBGN-AF networks and that are parameterized using general principles.Finally, we introduce two new qualitative semantics for the computation of the dynamics of SBGN-PD reaction networks. These semantics are expressed using automata networks. The first semantics extends the classical Boolean semantics by taking into account inhibitions. As to the second one, it relies on the concept of story which introduces a new point of view on reaction networks. Indeed, it allows to model different physical states of the same molecular entity using a unique variable.All the methods that we have developped show how qualitative formalisms can be used to reason on the relations represented by molecular networks in order to discorver new knowledge in systems biology.La construction des réseaux moléculaires à partir de résultats expérimentaux, ainsi que leur analyse en vue d'en exhiber des propriétés émergentes, sont deux tâches fondamentales de la biologie des systèmes. Avec l'augmentation du nombre de données expérimentales, elles ne peuvent plus être réalisées manuellement. Partant de ce constat, un certain nombre de méthodes bioinformatiques visant à les automatiser ont été développées.En parallèle du développement des méthodes, un certain nombre de standards ont vu le jour. Parmi ceux-ci, la Standard Biology Graphical Notation (SBGN) se compose de trois langages permettant la représentation des réseaux moléculaires.Les deux langages SBGN les plus couramment utilisés sont SBGN-PD pour la représentation des réseaux de réactions, et SBGN-AF pour celle des graphes d'influences. La notation SBGN, en plus de standardiser la représentation des réseaux, donne l'ensemble des concepts de la biologie des systèmes qui sont le plus souvent utilisés pour exprimer les connaissances du domaine.C'est dans ce cadre général que se placent l'ensemble de nos travaux. Nous avons développé un ensemble de méthodes pour la construction des réseaux moléculaires et l'analyse de leur dynamique. L'ensemble des méthodes que nous proposons reposent sur des formalismes qualitatifs, tels que la logique ou les réseaux d'automates. Ces formalismes on non seulement des bases théoriques solides, mais peuvent aussi être utilisés par de nombreux logiciels.L'ensemble de nos méthodes reposent également sur les concepts biologiques fournis par le standard SBGN, et peuvent ainsi être intégrées dans un même cadre théorique.Nous introduisons d'abord deux ensembles de prédicats qui permettent de traduire n'importe quel réseau SBGN-PD ou SBGN-AF sous la forme d'atomes instanciés. Nous montrons ensuite comment ces deux ensembles peuvent être utilisés pour raisonner automatiquement sur des réseaux moléculaires, en proposant une méthode de transformation automatique des réseaux de signalisation SBGN-PD en graphes d'influences SBGN-AF.Nous présentons ensuite une méthode de construction des réseaux de signalisation à partir de résultats expérimentaux, basée sur la logique du premier ordre. Cette méthode formalise et automatise le raisonnement réalisé par les biologistes à l'aide de règles de raisonnement explicites. Contrairement aux méthodes développées jusqu'à maintenant, celle que nous présentons prend en compte un grand nombre de types d'expériences, tout en permettant la reconstruction de mécanismes moléculaires précis.Puis nous montrons une nouvelle méthode pour le calcul des traces finies et des points attracteurs de réseaux Booléens modélisant des réseaux SBGN-AF et paramétrés à l'aide de principes généraux. Notre méthode repose sur l'utilisation de programmes logiques normaux du premier ordre, qui formalisent ces principes généraux.Enfin, nous proposons deux nouvelles sémantiques qualitatives pour le calcul de la dynamique des réseaux de réactions SBGN-PD, exprimées à l'aide de réseaux d'automates. La première de ces sémantiques étend la sémantique Booléenne des réseaux de réactions en prenant en compte les inhibitions. Quant à la deuxième, elle introduit le concept d'histoire (story) qui offre un nouveau point de vue sur les réseaux de réactions, en permettant de modéliser différents états physiques d'une même entité moléculaire par une seule variable.L'ensemble des méthodes que nous avons développées montrent comment les formalismes qualitatifs, et en particulier la logique, peuvent être utilisés pour raisonner à partir des relations représentées par les réseaux moléculaires, afin de découvrir de nouvelles connaissances en biologie des systèmes

Towards a logic-based method to infer provenance-aware molecular networks

International audienceProviding techniques to automatically infer molecular networks is particularly important to understand complex relationships between biological objects. We present a logic-based method to infer such networks and show how it allows inferring signalling networks from the design of a knowledge base. Provenance of inferred data has been carefully collected, allowing quality evaluation. More precisely, our method (i) takes into account various kinds of biological experiments and their origin; (ii) mimics the scientist's reasoning within a first-order logic setting; (iii) specifies precisely the kind of interaction between the molecules; (iv) provides the user with the provenance of each interaction; (v) automatically builds and draws the inferred network

Discovery of Calcium, Indium, Tin, and Platinum Isotopes

Currently, twenty-four calcium, thirty-eight indium, thirty-eight tin and thirty-nine platinum isotopes have been observed and the discovery of these isotopes is discussed here. For each isotope a brief synopsis of the first refereed publication, including the production and identification method, is presented.Comment: to be published in At. Data Nuclear Data Tables, This updated paper combines manuscripts: 1004.4934 (Calcium), 1004.5266 (Indium), 1003.5127 (Tin), and 1006.4033 (Platinum

Measurement of masses in the [Formula: see text] system by kinematic endpoints in pp collisions at [Formula: see text].

A simultaneous measurement of the top-quark, W-boson, and neutrino masses is reported for [Formula: see text] events selected in the dilepton final state from a data sample corresponding to an integrated luminosity of 5.0 fb-1 collected by the CMS experiment in pp collisions at [Formula: see text]. The analysis is based on endpoint determinations in kinematic distributions. When the neutrino and W-boson masses are constrained to their world-average values, a top-quark mass value of [Formula: see text] is obtained. When such constraints are not used, the three particle masses are obtained in a simultaneous fit. In this unconstrained mode the study serves as a test of mass determination methods that may be used in beyond standard model physics scenarios where several masses in a decay chain may be unknown and undetected particles lead to underconstrained kinematics

Performance of photon reconstruction and identification with the CMS detector in proton-proton collisions at √s = 8 TeV

A description is provided of the performance of the CMS detector for photon reconstruction and identification in proton-proton collisions at a centre-of-mass energy of 8 TeV at the CERN LHC. Details are given on the reconstruction of photons from energy deposits in the electromagnetic calorimeter (ECAL) and the extraction of photon energy estimates. The reconstruction of electron tracks from photons that convert to electrons in the CMS tracker is also described, as is the optimization of the photon energy reconstruction and its accurate modelling in simulation, in the analysis of the Higgs boson decay into two photons. In the barrel section of the ECAL, an energy resolution of about 1% is achieved for unconverted or late-converting photons from Hγγ decays. Different photon identification methods are discussed and their corresponding selection efficiencies in data are compared with those found in simulated events

Search for physics beyond the standard model in events with τ leptons, jets, and large transverse momentum imbalance in pp collisions at [Formula: see text].

A search for physics beyond the standard model is performed with events having one or more hadronically decaying τ leptons, highly energetic jets, and large transverse momentum imbalance. The data sample corresponds to an integrated luminosity of 4.98 fb-1 of proton-proton collisions at [Formula: see text] collected with the CMS detector at the LHC in 2011. The number of observed events is consistent with predictions for standard model processes. Lower limits on the mass of the gluino in supersymmetric models are determined

Measurement of jet multiplicity distributions in [Formula: see text] production in pp collisions at [Formula: see text].

The normalised differential top quark-antiquark production cross section is measured as a function of the jet multiplicity in proton-proton collisions at a centre-of-mass energy of 7[Formula: see text] at the LHC with the CMS detector. The measurement is performed in both the dilepton and lepton+jets decay channels using data corresponding to an integrated luminosity of 5.0[Formula: see text]. Using a procedure to associate jets to decay products of the top quarks, the differential cross section of the [Formula: see text] production is determined as a function of the additional jet multiplicity in the lepton+jets channel. Furthermore, the fraction of events with no additional jets is measured in the dilepton channel, as a function of the threshold on the jet transverse momentum. The measurements are compared with predictions from perturbative quantum chromodynamics and no significant deviations are observed