909 resultados para LHC, CMS, Grid computing, distributed analysis, top physics, Higgs physics


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Data-intensive Grid applications require huge data transfers between grid computing nodes. These computing nodes, where computing jobs are executed, are usually geographically separated. A grid network that employs optical wavelength division multiplexing (WDM) technology and optical switches to interconnect computing resources with dynamically provisioned multi-gigabit rate bandwidth lightpath is called a Lambda Grid network. A computing task may be executed on any one of several computing nodes which possesses the necessary resources. In order to reflect the reality in job scheduling, allocation of network resources for data transfer should be taken into consideration. However, few scheduling methods consider the communication contention on Lambda Grids. In this paper, we investigate the joint scheduling problem while considering both optical network and computing resources in a Lambda Grid network. The objective of our work is to maximize the total number of jobs that can be scheduled in a Lambda Grid network. An adaptive routing algorithm is proposed and implemented for accomplishing the communication tasks for every job submitted in the network. Four heuristics (FIFO, ESTF, LJF, RS) are implemented for job scheduling of the computational tasks. Simulation results prove the feasibility and efficiency of the proposed solution.

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Data-intensive Grid applications require huge data transfers between grid computing nodes. These computing nodes, where computing jobs are executed, are usually geographically separated. A grid network that employs optical wavelength division multiplexing (WDM) technology and optical switches to interconnect computing resources with dynamically provisioned multi-gigabit rate bandwidth lightpath is called a Lambda Grid network. A computing task may be executed on any one of several computing nodes which possesses the necessary resources. In order to reflect the reality in job scheduling, allocation of network resources for data transfer should be taken into consideration. However, few scheduling methods consider the communication contention on Lambda Grids. In this paper, we investigate the joint scheduling problem while considering both optical network and computing resources in a Lambda Grid network. The objective of our work is to maximize the total number of jobs that can be scheduled in a Lambda Grid network. An adaptive routing algorithm is proposed and implemented for accomplishing the communication tasks for every job submitted in the network. Four heuristics (FIFO, ESTF, LJF, RS) are implemented for job scheduling of the computational tasks. Simulation results prove the feasibility and efficiency of the proposed solution.

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In SUSY models with heavy squarks and gaugino mass unification, the gaugino pair production reaction pp -> (W) over tilde (+/-)(1)(Z) over tilde (2) dominates gluino pair production for m (g) over tilde less than or similar to 1 TeV at LHC with root s = 14 TeV (LHC14). For this mass range, the two-body decays (W) over tilde (1) -> W (Z) over tilde (1) and (Z) over tilde (2) -> h (Z) over tilde (1) are expected to dominate the chargino and neutralino branching fractions. By searching for lb (b) over tilde + is not an element of(T) events from (W) over tilde (+/-)(1)Z(2) production, we show that LHC14 with 100 fb(-1) of integrated luminosity becomes sensitive to chargino masses in the range m((W) over tilde1) similar to 450-550 GeV corresponding to m (g) over tilde similar to 1.5-2 TeV in models with gaugino mass unification. For 10(3) fb(-1), LHC14 is sensitive to the Wh channel for m((W) over tilde1) similar to 300-800 GeV, corresponding to m (g) over tilde similar to 1-2.8 TeV, which is comparable to the reach for gluino pair production followed by cascade decays. The Wh + is not an element of(T) search channel opens up a new complementary avenue for SUSY searches at LHC, and serves to point to SUSYas the origin of any new physics discovered via multijet and multilepton + is not an element of(T) channels.

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La sezione d'urto di produzione per coppie tt-barra viene misurata utilizzando dati raccolti dall'esperimento CMS in collisioni protone-protone ad LHC, con energia nel sistema del centro di massa radice di s = 8 TeV. Il campione raccolto corrisponde ad una luminosità integrata di 19.5 fb^-1. La misura viene effettuata su eventi che contano un numero di jet pari o superiore a 6, almeno due dei quali identificati come prodotto dell'adronizzazione di quark bottom. Il valore di sezione d'urto ottenuto è (260 pm 10 (stat)) pb, in accordo con le previsioni teoriche del Modello Standard.

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Results of a search for supersymmetry via direct production of third-generation squarks are reported, using 20.3  fb −1 of proton-proton collision data at √s =8  TeV recorded by the ATLAS experiment at the LHC in 2012. Two different analysis strategies based on monojetlike and c -tagged event selections are carried out to optimize the sensitivity for direct top squark-pair production in the decay channel to a charm quark and the lightest neutralino (t 1 →c+χ ˜ 0 1 ) across the top squark–neutralino mass parameter space. No excess above the Standard Model background expectation is observed. The results are interpreted in the context of direct pair production of top squarks and presented in terms of exclusion limits in the m ˜t 1, m ˜ X0 1 ) parameter space. A top squark of mass up to about 240 GeV is excluded at 95% confidence level for arbitrary neutralino masses, within the kinematic boundaries. Top squark masses up to 270 GeV are excluded for a neutralino mass of 200 GeV. In a scenario where the top squark and the lightest neutralino are nearly degenerate in mass, top squark masses up to 260 GeV are excluded. The results from the monojetlike analysis are also interpreted in terms of compressed scenarios for top squark-pair production in the decay channel t ˜ 1 →b+ff ′ +χ ˜ 0 1 and sbottom pair production with b ˜ 1 →b+χ ˜ 0 1 , leading to a similar exclusion for nearly mass-degenerate third-generation squarks and the lightest neutralino. The results in this paper significantly extend previous results at colliders.

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Complexity has always been one of the most important issues in distributed computing. From the first clusters to grid and now cloud computing, dealing correctly and efficiently with system complexity is the key to taking technology a step further. In this sense, global behavior modeling is an innovative methodology aimed at understanding the grid behavior. The main objective of this methodology is to synthesize the grid's vast, heterogeneous nature into a simple but powerful behavior model, represented in the form of a single, abstract entity, with a global state. Global behavior modeling has proved to be very useful in effectively managing grid complexity but, in many cases, deeper knowledge is needed. It generates a descriptive model that could be greatly improved if extended not only to explain behavior, but also to predict it. In this paper we present a prediction methodology whose objective is to define the techniques needed to create global behavior prediction models for grid systems. This global behavior prediction can benefit grid management, specially in areas such as fault tolerance or job scheduling. The paper presents experimental results obtained in real scenarios in order to validate this approach.

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Systems biology is based on computational modelling and simulation of large networks of interacting components. Models may be intended to capture processes, mechanisms, components and interactions at different levels of fidelity. Input data are often large and geographically disperse, and may require the computation to be moved to the data, not vice versa. In addition, complex system-level problems require collaboration across institutions and disciplines. Grid computing can offer robust, scaleable solutions for distributed data, compute and expertise. We illustrate some of the range of computational and data requirements in systems biology with three case studies: one requiring large computation but small data (orthologue mapping in comparative genomics), a second involving complex terabyte data (the Visible Cell project) and a third that is both computationally and data-intensive (simulations at multiple temporal and spatial scales). Authentication, authorisation and audit systems are currently not well scalable and may present bottlenecks for distributed collaboration particularly where outcomes may be commercialised. Challenges remain in providing lightweight standards to facilitate the penetration of robust, scalable grid-type computing into diverse user communities to meet the evolving demands of systems biology.

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Wireless Mesh Networks (WMNs), based on commodity hardware, present a promising technology for a wide range of applications due to their self-configuring and self-healing capabilities, as well as their low equipment and deployment costs. One of the key challenges that WMN technology faces is the limited capacity and scalability due to co-channel interference, which is typical for multi-hop wireless networks. A simple and relatively low-cost approach to address this problem is the use of multiple wireless network interfaces (radios) per node. Operating the radios on distinct orthogonal channels permits effective use of the frequency spectrum, thereby, reducing interference and contention. In this paper, we evaluate the performance of the multi-radio Ad-hoc On-demand Distance Vector (AODV) routing protocol with a specific focus on hybrid WMNs. Our simulation results show that under high mobility and traffic load conditions, multi-radio AODV offers superior performance as compared to its single-radio counterpart. We believe that multi-radio AODV is a promising candidate for WMNs, which need to service a large number of mobile clients with low latency and high bandwidth requirements.

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Preface. The evolution of cognitive neuroscience has been spurred by the development of increasingly sophisticated investigative techniques to study human cognition. In Methods in Mind, experts examine the wide variety of tools available to cognitive neuroscientists, paying particular attention to the ways in which different methods can be integrated to strengthen empirical findings and how innovative uses for established techniques can be developed. The book will be a uniquely valuable resource for the researcher seeking to expand his or her repertoire of investigative techniques. Each chapter explores a different approach. These include transcranial magnetic stimulation, cognitive neuropsychiatry, lesion studies in nonhuman primates, computational modeling, psychophysiology, single neurons and primate behavior, grid computing, eye movements, fMRI, electroencephalography, imaging genetics, magnetoencephalography, neuropharmacology, and neuroendocrinology. As mandated, authors focus on convergence and innovation in their fields; chapters highlight such cross-method innovations as the use of the fMRI signal to constrain magnetoencephalography, the use of electroencephalography (EEG) to guide rapid transcranial magnetic stimulation at a specific frequency, and the successful integration of neuroimaging and genetic analysis. Computational approaches depend on increased computing power, and one chapter describes the use of distributed or grid computing to analyze massive datasets in cyberspace. Each chapter author is a leading authority in the technique discussed.

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The evolution of cognitive neuroscience has been spurred by the development of increasingly sophisticated investigative techniques to study human cognition. In Methods in Mind, experts examine the wide variety of tools available to cognitive neuroscientists, paying particular attention to the ways in which different methods can be integrated to strengthen empirical findings and how innovative uses for established techniques can be developed. The book will be a uniquely valuable resource for the researcher seeking to expand his or her repertoire of investigative techniques. Each chapter explores a different approach. These include transcranial magnetic stimulation, cognitive neuropsychiatry, lesion studies in nonhuman primates, computational modeling, psychophysiology, single neurons and primate behavior, grid computing, eye movements, fMRI, electroencephalography, imaging genetics, magnetoencephalography, neuropharmacology, and neuroendocrinology. As mandated, authors focus on convergence and innovation in their fields; chapters highlight such cross-method innovations as the use of the fMRI signal to constrain magnetoencephalography, the use of electroencephalography (EEG) to guide rapid transcranial magnetic stimulation at a specific frequency, and the successful integration of neuroimaging and genetic analysis. Computational approaches depend on increased computing power, and one chapter describes the use of distributed or grid computing to analyze massive datasets in cyberspace. Each chapter author is a leading authority in the technique discussed.

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L'esperimento ATLAS, come gli altri esperimenti che operano al Large Hadron Collider, produce Petabytes di dati ogni anno, che devono poi essere archiviati ed elaborati. Inoltre gli esperimenti si sono proposti di rendere accessibili questi dati in tutto il mondo. In risposta a questi bisogni è stato progettato il Worldwide LHC Computing Grid che combina la potenza di calcolo e le capacità di archiviazione di più di 170 siti sparsi in tutto il mondo. Nella maggior parte dei siti del WLCG sono state sviluppate tecnologie per la gestione dello storage, che si occupano anche della gestione delle richieste da parte degli utenti e del trasferimento dei dati. Questi sistemi registrano le proprie attività in logfiles, ricchi di informazioni utili agli operatori per individuare un problema in caso di malfunzionamento del sistema. In previsione di un maggiore flusso di dati nei prossimi anni si sta lavorando per rendere questi siti ancora più affidabili e uno dei possibili modi per farlo è lo sviluppo di un sistema in grado di analizzare i file di log autonomamente e individuare le anomalie che preannunciano un malfunzionamento. Per arrivare a realizzare questo sistema si deve prima individuare il metodo più adatto per l'analisi dei file di log. In questa tesi viene studiato un approccio al problema che utilizza l'intelligenza artificiale per analizzare i logfiles, più nello specifico viene studiato l'approccio che utilizza dell'algoritmo di clustering K-means.

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The analysis of the Higgs boson data by the ATLAS and CMS Collaborations appears to exhibit an excess of h -> gamma gamma events above the Standard Model (SM) expectations, whereas no significant excess is observed in h -> ZZ* -> four lepton events, albeit with large statistical uncertainty due to the small data sample. These results (assuming they persist with further data) could be explained by a pair of nearly mass-degenerate scalars, one of which is an SM-like Higgs boson and the other is a scalar with suppressed couplings to W+W- and ZZ. In the two-Higgs-doublet model, the observed gamma gamma and ZZ* -> four lepton data can be reproduced by an approximately degenerate CP-even (h) and CP-odd (A) Higgs boson for values of sin (beta - alpha) near unity and 0: 70 less than or similar to tan beta less than or similar to 1. An enhanced gamma gamma signal can also arise in cases where m(h) similar or equal to m(H), m(H) similar or equal to m(A), or m(h) similar or equal to m(H) similar or equal to m(A). Since the ZZ* -> 4 leptons signal derives primarily from an SM-like Higgs boson whereas the gamma gamma signal receives contributions from two (or more) nearly mass-degenerate states, one would expect a slightly different invariant mass peak in the ZZ* -> four lepton and gamma gamma channels. The phenomenological consequences of such models can be tested with additional Higgs data that will be collected at the LHC in the near future. DOI: 10.1103/PhysRevD.87.055009.

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Comunicação apresentada na CAPSI 2011 - 11ª Conferência da Associação Portuguesa de Sistemas de Informação – A Gestão de Informação na era da Cloud Computing, Lisboa, ISEG/IUL-ISCTE/, 19 a 21 de Outubro de 2011.

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A measurement of spin correlation in tt¯ production is presented using data collected with the ATLAS detector at the Large Hadron Collider in proton-proton collisions at a center-of-mass energy of 8 TeV, corresponding to an integrated luminosity of 20.3 fb−1. The correlation between the top and antitop quark spins is extracted from dilepton tt¯ events by using the difference in azimuthal angle between the two charged leptons in the laboratory frame. In the helicity basis the measured degree of correlation corresponds to Ahelicity=0.38±0.04, in agreement with the Standard Model prediction. A search is performed for pair production of top squarks with masses close to the top quark mass decaying to predominantly right-handed top quarks and a light neutralino, the lightest supersymmetric particle. Top squarks with masses between the top quark mass and 191 GeV are excluded at the 95% confidence level.

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A search is performed for top-quark pairs (tt¯) produced together with a photon (γ) with transverse momentum >20 GeV using a sample of tt¯ candidate events in final states with jets, missing transverse momentum, and one isolated electron or muon. The dataset used corresponds to an integrated luminosity of 4.59 fb−1 of proton--proton collisions at a center-of-mass energy of 7 TeV recorded by the ATLAS detector at the CERN Large Hadron Collider. In total 140 and 222 tt¯γ candidate events are observed in the electron and muon channels, to be compared to the expectation of 79±26 and 120±39 non-tt¯γ background events respectively. The production of tt¯γ events is observed with a significance of 5.3 standard deviations away from the null hypothesis. The tt¯γ production cross section times the branching ratio (BR) of the single-lepton decay channel is measured in a fiducial kinematic region within the ATLAS acceptance. The measured value is σfidtt¯γ=63±8(stat.)+17−13(syst.)±1(lumi.) fb per lepton flavor, in good agreement with the leading-order theoretical calculation normalized to the next-to-leading-order theoretical prediction of 48±10 fb.