List of previous students

Nicola Orlando
Faten Hariri
Emma Kuwertz
Spyridon Argyropoulo
Sabrina Sacerdoti
Simone Amoroso
Jesper Roy Christiansen
Nathan Hartland
Christian Roehr
Benjamin Watt
Philip Ilten
Nishita Desai
Sercan Sen
Miroslav Myska
Sudha Ahuja
Holger Schulz
Avi Gershan
Aleksander Kusina
Magdalena Slawinska
Flavia Dias
Kenneth Wraight
Irais Bautista Guzman
Sparsh Navin
Paolo Francavilla
Riccardo Di Sipio
Seyi Latunde-Dada
Devdatta Majumder
Martijn Gosselink
Christopher Bignamini
Marek Schönherr
Michal Deak
Noam Hod
Florian Bechtel
Jonathan Ferland
Manuel Bähr
Alexander Flossdorf
Piergiulio Lenzi

Riccardo Di Sipio is a PhD student from the University of Bologna working along with the Atlas experiment, on a three-month MCnet studentship in the Userlink team at UCL.

The goal of my PhD thesis is the measurement of top-antitop pairs production cross-section in the semileptonic decay channel with the Atlas detector. Events in which top-quark pairs are produced will be extremely important at the LHC, as they will provide a special environment to study physics within the Standard Model and beyond, such as its supersymmetric extension, and to calibrate the detector using leptons, particle jets and evaluation of missing transverse energy.

One of the backgrounds to those events is represented by QCD jets, which can mimic ttbar events by the reconstruction of a jet as a lepton and by "fake ETmiss" generated by dead materials, or other inefficiencies. Although estimates suggest this effects to be quite low, it can be helpful to have a MC sample before the first physics run, in order to compute efficiencies and then make a comparison with real data.

At present, no general full-simulation sample has been generated for QCD events in the ATLAS experiment with cuts suitable for top quark studies, mainly due to the huge number of events that need to be simulated.

I generated a number of QCD multijet samples using Pythia, Herwig and Sherpa, applying appropriate cuts on parton pT and then filtering the final states in order to choose events with at least four high-pT jets. Using three different programs it is possible to estimate the systematic error given by different generation models.

I've something similar for the ttbar samples, comparing leading-order generators such as Pythia, Pythia 8 and Sherpa, to more accurate next-to-leading order programs, i.e. Mc@NLO and Powheg-hvq.

Comparison is carried out using Rivet, a tool developed and maintained by MCnet. Rivet provides a generator-independent framework for comparison of event generator predictions. A number of kinematical and event shape variables have been studied, aiming to find the more useful ones to separate the ttbar signal from the QCD multijet background, with the possibility of relaxing the requirement of an isolated lepton.