Collins and Sivers asymmetries in muonproduction of pions and kaons off transversely polarised protons

Measurements of the Collins and Sivers asymmetries for charged pions and charged and neutral kaons produced in semi-inclusive deep-inelastic scattering of high energy muons off transversely polarised protons are presented. The results were obtained using all the available COMPASS proton data, which were taken in the years 2007 and 2010. The Collins asymmetries exhibit in the valence region a non-zero signal for pions and there are hints of non-zero signal also for kaons. The Sivers asymmetries are found to be positive for positive pions and kaons and compatible with zero otherwise. © 2015

Untergrundstudien zur Messung der Strangeness-Vektorformfaktoren des Protons durch paritätsverletzende Elektronenstreuung unter Rückwärtswinkeln

Im Rahmen des A4-Experiments werden die Beiträge des Strange-Quarks zu den elektromagnetischen Formfaktoren des Protons gemessen. Solche Seequarkeffekte bei Niederenergieobservablen sind für das Verständnis der Hadronenstruktur wichtig, denn sie stellen eine direkte Manifestation der QCD-Freiheitsgrade im nichtperturbativen Bereich dar.rnrnLinearkombinationen der Strangeness-Vektorformfaktoren des Protons $G_E^s$ und $G_M^s$ sind experimentell über die Messung der paritätsverletzenden Asymmetrie im Wirkungsquerschnitt der elastischen Streuung longitudinal polarisierter Elektronen an unpolarisierten Nukleonen zugänglich. Vor dieser Arbeit hatte die A4-Kollaboration zwei solche Messungen unter Vorwärtsstreuwinkeln bei den Viererimpulsübertägen $Q^2$ von jeweils 0.23 und 0.10 (GeV/c)$^2$ veröffentlicht. Um die Separation von $G_E^s$ und $G_M^s$ beim höheren $Q^2$-Wert zu erhalten, wurde eine Messung unter Rückwärtswinkeln mit der Strahlenergie von 315 MeV durchgeführt.rnrnIm A4-Experiment werden die an einem Flüssigwasserstoff-Target gestreuten Elektronen eines longitudinal polarisierten Strahls mit einem Cherenkov-Kalorimeter einzeln gezählt. Durch die kalorimetrische Energiemessung erfolgt die Trennung der elastischen von den inelastischen Ereignissen. Bei Rückwärtswinkeln wurde dieses Apparat mit einem Szintillator als Elektronentagger erweitert, um den $\gamma$-Untergrund aus dem $\pi^0$-Zerfall zu unterdrücken.rn rnUm die Auswertung dieser Messung zu ermöglichen, wurden im Rahmen dieser Arbeit die gemessenen Energiespektren anhand von ausführlichen Simulationen der Streuprozesse und des Antwortverhaltens der Detektoren untersucht, und eine Methode zur Behandlung des restlichen Untergrunds aus der $\gamma$-Konversionrnvor dem Szintillator entwickelt. Die Simulationergebnisse sind auf dem 5%-Niveau mit den Messungen verträglich, und es wurde bewiesen, dass die Methode der Untergrundbehandlung anwendbar ist.rnrnDie Asymmetriemessung bei Rückwärtswinkeln, die man nach Anwendung der hier erarbeiteten Untergrundbehandlung erhält, wurde für die Separation von $G_E^s$ und $G_M^s$ bei $Q^2$=0.22 (GeV/c)^2 mit der Vorwärtswinkelmessung beim selbenrn$Q^2$ kombiniert. Es ergeben sich die Werte:rnrn$G_M^s$= -0.14 ± 0.11_{exp} ± 0.11_{theo} undrn$G_E^s$= 0.050 ± 0.038_{exp} ± 0.019_{theo}, rnrnwobei die systematische Unsicherheit wegen der Untergrundbehandlung im experimentellen Fehler enthalten ist. Am Ende der Arbeit werden die aus diesen Resultaten folgenden Rückschlüsse auf den Einfluss der Strangeness auf die statischen elektromagnetischen Eigenschaften des Protons diskutiert.rnWithin the A4 experiment the contributions of the strange quark to the electromagnetic form factors of the proton are measured. These see-quark effects in low energy observables are very important for the understanding of hadron structure, because they are a direct manifestation of QCD degrees of freedom in the non-perturbative regime.rnrnLinear combinations of the strangeness vector form factors of the proton ($G_E^s$ and $G_M^s$) are accessible experimentally by measuring the parity violating asymmetry in the cross section of the elastic scattering of longitudinal polarised electrons off unpolarised nucleons. Two such measurements were published by the A4 collaboration before this work. Both of them were forward angle measurements at the $Q^2$ values of 0.23 andrn0.10 (GeV/c)$^2$, respectively. A measurement at backward angle with a beam energy of 315 MeV was performed for separating $G_E^s$ and $G_M^s$ at the higher of these $Q^2$ values.rnrnIn the A4 experiment a longitudinally polarised electron beam scatters on a liquid hydrogen target. Single scattered electrons are counted with a Cherenkov calorimeter. The separation of elastic from inelastic events is achieved by means of calorimetric energy measurement. For the backward angle measurement a plastic scintillator was installed as electron tagger for suppressing the $\gamma$ background coming from the decay of $\pi^0$ mesons.rnrnIn order to make the data analysis possible the energy spectra needed to be studied thoroughly. This was done in this work using detailed simulations of both the scattering processes suffered by beam electrons and of the response of the detectors. A method for handling the remaining background due to $\gamma$ conversion before the scintillator has been also developed. The simulationrnresults agree with the measured spectra at the 5% level and the strategy for handling the background was shown to be feasible.rnrnThe asymmetry value obtained by handling the background as proposed in this work was combined with the previous A4 forward angle measurement at the same $Q^2$ for separating $G_E^s$ and $G_M^s$ at $Q^2$=0.22~(GeV/c)$^2$. The results arernrn$G_M^s$= -0.14 ± 0.11_{exp} ± 0.11_{theo} andrn$G_E^s$= 0.050 ± 0.038_{exp} ± 0.019_{theo}, rnrnwhere the systematic uncertainty due to the background correction is contained in the experimental error. Conclusions about the influence of strangeness on the static electromagnetic properties of the proton are drawn from these results and are presented at the end of the work.r

OptorSim - A Grid Simulator for Studying Dynamic Data Replication Strategies

Computational grids process large, computationally intensive problems on small data sets. In contrast, data grids process large computational problems that in turn require evaluating, mining and producing large amounts of data. Replication, creating geographically disparate identical copies of data, is regarded as one of the major optimization techniques for reducing data access costs. In this paper, several replication algorithms are discussed. These algorithms were studied using the Grid simulator: OptorSim. OptorSim provides a modular framework within which optimization strategies can be studied under different Grid configurations. The goal is to explore the stability and transient behaviour of selected optimization techniques. We detail the design and implementation of OptorSim and analyze various replication algorithms based on different Grid workloads

Optorsim: a Grid Simulator for Studying Dinamic Data Replication Strategies

Computational Grids process large, computationally intensive problems on small data sets. In contrast, Data Grids process large computational problems that in turn require evaluating, mining and producing large amounts of data. Replication, creating geographically disparate identical copies of data, is regarded as one of the major optimisation techniques for reducing data access costs. In this paper, several replication algorithms are discussed. These algorithms were studied using the Grid simulator: OptorSim. OptorSim provides a modular framework within which optimisation strategies can be studied under different Grid configurations. The goal is to explore the stability and transient behaviour of selected optimisation techniques. We detail the design and implementation of OptorSim and analyse various replication algorithms based on different Grid workload

Optorsim: A Grid Simulator for Studying Dynamic Data Replication Strategies

Computational grids process large, computationally intensive problems on small data sets. In contrast, data grids process large computational problems that in turn require evaluating, mining and producing large amounts of data. Replication, creating geographically disparate identical copies of data, is regarded as one of the major optimization techniques for reducing data access costs. In this paper, several replication algorithms are discussed. These algorithms were studied using the Grid simulator: OptorSim. OptorSim provides a modular framework within which optimization strategies can be studied under different Grid configurations. The goal is to explore the stability and transient behaviour of selected optimization techniques. We detail the design and implementation of OptorSim and analyze various replication algorithms based on different Grid workloads

Optorsim: a Grid Simulator for Studying Dinamic Data Replication Strategies

Computational Grids process large, computationally intensive problems on small data sets. In contrast, Data Grids process large computational problems that in turn require evaluating, mining and producing large amounts of data. Replication, creating geographically disparate identical copies of data, is regarded as one of the major optimisation techniques for reducing data access costs. In this paper, several replication algorithms are discussed. These algorithms were studied using the Grid simulator: OptorSim. OptorSim provides a modular framework within which optimisation strategies can be studied under different Grid configurations. The goal is to explore the stability and transient behaviour of selected optimisation techniques. We detail the design and implementation of OptorSim and analyse various replication algorithms based on different Grid workload