Trigger Algorithms and Monte Carlo Event Generation for Dijet Searches in ATLAS and Beyond

Abstract

So far, the Standard Model (SM) has been very successful in describing non-gravitational interactions of fundamental particles. However, many of its theoretical and experimental shortcomings remain unresolved. In collider searches, Beyond the Standard Model (BSM) signatures are expected to manifest themselves as localised excesses of events in the invariant mass lineshape of their decay products. Alternatively, they may become apparent as deviations in the observed shape of angular distributions. In order to discern BSM phenomena, the expected SM background has to predicted with very high accuracy. This is achieved by use of Monte Carlo (MC) techniques.

The ATLAS dijet Trigger Level Analysis (TLA) searches for processes indicative of new physics in final states comprising two jets. Due to the large SM multijet background and the limited bandwidth available to inclusive single-jet triggers, the low mass regime of this search signature is not well constrained by previous experiments. To alleviate the bandwidth limitation, a 20 GeV minimum threshold for the jet transverse momentum has been implemented to reduce the average event size, thus allowing to record events at a higher rate and ultimately resulting in an increased search sensitivity.

In the second part of this thesis, kinematic and angular distributions of dijet topologies are studied using the MC event generator PYTHIA 8.219, including topologies with an additional associated jet that have not been considered in previous MC studies. Pure dijet topologies are corrected up to Next-to-Leading Order (NLO) using k-factors derived from the Matrix Element (ME) event generator NLOJET++. Topologies with associated jet production are studied using a reweighting procedure to account for the reduced strong interaction scale associated with the emission of soft jets, as well as under variation of the minimum angular separation between two jets.

Popular Abstract

Particle physics is the human endeavour to describe the most elementary building blocks of matter and understand how they interact with each other. As far as experiments have observed, these so-called fundamental particles are not made up of smaller, primary constituents. All that is currently known about them is tied together in a theoretical framework known as the Standard Model (SM) of particle physics. Despite its unparalleled success in describing what we observe in the world around us, it is an incomplete theory. This is known quite simply from the fact that gravity is not included, but also from astronomical observations hinting at the existence of forms of matter that are not contained within the SM, e.g. dark matter and dark energy. Consequently, physicists are eager to conduct experiments in order to identify and study new phenomena beyond the Sandard Model (BSM), i.e. occurrences that are not predicted by the SM, such as new fundamental particles.

Probing matter at the smallest scales requires one of the largest and arguably most complex machines known to mankind, built in one of the biggest collaborative scientific efforts to date: the CERN Large Hadron Collider (LHC). It is used to collide beams of protons at velocities greater than 99.9% the speed of light in four separate detector caverns, where the outcomes of the collisions are recorded by custom-made detectors. This allows physicists to verify predictions made by the SM, as well as to identify possible deviations, such as BSM phenomena. Due to the high particle velocities achieved in the LHC ring, collisions occur so frequently that not all of them can be recorded due to the limited amount of both disk space and recording speed. Thus, a dedicated filter system is needed in order to determine whether an event contains interesting physics signatures and should be recorded, or discarded instead. Such a filter system is called a trigger. The decision is made based upon a limited amount of information that is available during the early reconstruction of the collision. Different analysis teams are looking for different particle signatures, and therefore use distinct trigger configurations tailored to their specific needs. At Lund University, for instance, we study collision events that comprise narrowly collimated clusters of particles known as jets. Since jets consist of the same fundamental particles as protons, every new, previously undiscovered particle that can be produced in proton-proton collisions at the LHC can certainly decay into jets. Accordingly, it is possible to discover new particles by identifying anomalies in jet mass and angular distributions.

One of the primary objectives of this thesis was the implementation of a software-based trigger selection cut placed on the jet momentum in order to discard the abundance of low momentum jets that are not useful for the analysis while reducing the average event size at the same time. Due to the reduced event size, collisions can be recorded at a much higher rate, resulting in a higher statistical significance and ultimately an increased sensitivity of searches for new particles in jet distributions.

Needless to say, it is necessary to predict what is expected according to the SM in order to accurately discern BSM phenomena in a search. Since events containing evidence for BSM physics are generally predicted to occur only rarely, this must be done with very high precision that can only be achieved by means of sophisticated statistical methods. In this thesis, the Monte Carlo (MC) event generator PYTHIA, established and developed at Lund University, was used to model various kinematic and angular distributions for two specific jet event topologies.

• author: Murk, Sebastian
• supervisor: Caterina Doglioni
• organization: Department of Physics; Particle and nuclear physics
• course: FYSM60 20162
• year: 2017
• type: H2 - Master's Degree (Two Years)
• subject: Physics and Astronomy
• language: English
• id: 8902969
• date added to LUP: 2017-02-13 09:36:04
• date last changed: 2017-03-10 06:44:02