3 resultados para multivariate allometry
em AMS Tesi di Laurea - Alm@DL - Università di Bologna
Resumo:
The Large Hadron Collider, located at the CERN laboratories in Geneva, is the largest particle accelerator in the world. One of the main research fields at LHC is the study of the Higgs boson, the latest particle discovered at the ATLAS and CMS experiments. Due to the small production cross section for the Higgs boson, only a substantial statistics can offer the chance to study this particle properties. In order to perform these searches it is desirable to avoid the contamination of the signal signature by the number and variety of the background processes produced in pp collisions at LHC. Much account assumes the study of multivariate methods which, compared to the standard cut-based analysis, can enhance the signal selection of a Higgs boson produced in association with a top quark pair through a dileptonic final state (ttH channel). The statistics collected up to 2012 is not sufficient to supply a significant number of ttH events; however, the methods applied in this thesis will provide a powerful tool for the increasing statistics that will be collected during the next LHC data taking.
Resumo:
The spatio-temporal distribution of megistobenthic crustacean assemblages from the Antalya Gulf, located in the Levantine Sea is described. In order to provide a comprehensive overview of the spatio-temporal patterns of the crustacean community, 3 transect including depth of 10, 25, 75, 125 and 200 m, were studied between 2014 and 2015 to investigate their association with a set of environmental parameters in representative months of each season (spring, summer, autumn and winter). For its economic importance in Levantine waters, a focus analysis of deep-water rose shrimp Parapenaeus longirostris (Lucas, 1846) was done, to investigate the length frequency composition of the population of the Antalya Gulf. A total of 58 crustacean species were encountered in the study area, of these species identified, 18 species were recognized as alien species in the Mediterranean Sea. Throughout the year the most frequent species of the study were the hermit crab Pagurus prideaux (Leach, 1815) and Parapenaeus longirostris (Lucas, 1846) followed by the Indo-Pacific swimming crab Charybdis longicollis (Leene, 1938) and by the invasive shrimp Marsupenaeus japonicus (Spence Bate, 1888). Few species contributing to a high amount to the total biomass were found throughout the year. These species were Charybdis longicollis and Parapenaeus longirostris. Stations of the study area showed similar values of diversity indices of benthic crustacean community among the three transect. The highest values of faunistic indices were detected in autumn and winter (October and February), and also varied along the depth gradient, with the highest values found between 25 and 75 meters. The multivariate analyses conducted on the abundance data point out major differences between depths and between seasons. Therefore, according to cluster analysis and ordination over abundance and biomass, three main crustacean assemblages were detected: the first corresponding to shallow bottoms (10, 25 meters), the second corresponding to intermediate waters (75 meters) and the last to deeper waters (125, 200 meters). Depth was the main factor governing the distribution of megistobenthic crustacean in the area. Besides the depth, the structure of the sediment is the most important factor in determining the crustacean assemblage. Therefore, all factors governing the crustacean distribution were found to be related to the bottom depth. The population of Parapenaeus longirostris in the Antalya Gulf showed significant differences in depth. It was found that females dominated the population of the study area (65.11%), and were significantly larger than males for each cohort identified. The size-weight relationships revealed a slight negative allometry in growth, a bit more pronounced in females than in males.
Resumo:
Il quark top è una delle particelle fondamentali del Modello Standard, ed è osservato a LHC nelle collisioni a più elevata energia. In particolare, la coppia top-antitop (tt̄) è prodotta tramite interazione forte da eventi gluone-gluone (gg) oppure collisioni di quark e antiquark (qq̄). I diversi meccanismi di produzione portano ad avere coppie con proprietà diverse: un esempio è lo stato di spin di tt̄, che vicino alla soglia di produzione è maggiormente correlato nel caso di un evento gg. Uno studio che voglia misurare l’entità di tali correlazioni risulta quindi essere significativamente facilitato da un metodo di discriminazione delle coppie risultanti sulla base del loro canale di produzione. Il lavoro qui presentato ha quindi lo scopo di ottenere uno strumento per effettuare tale differenziazione, attraverso l’uso di tecniche di analisi multivariata. Tali metodi sono spesso applicati per separare un segnale da un fondo che ostacola l’analisi, in questo caso rispettivamente gli eventi gg e qq̄. Si dice che si ha a che fare con un problema di classificazione. Si è quindi studiata la prestazione di diversi algoritmi di analisi, prendendo in esame le distribuzioni di numerose variabili associate al processo di produzione di coppie tt̄. Si è poi selezionato il migliore in base all’efficienza di riconoscimento degli eventi di segnale e alla reiezione degli eventi di fondo. Per questo elaborato l’algoritmo più performante è il Boosted Decision Trees, che permette di ottenere da un campione con purezza iniziale 0.81 una purezza finale di 0.92, al costo di un’efficienza ridotta a 0.74.