Avancerad sökning
Visar resultat 1 - 5 av 21 uppsatser som matchar ovanstående sökkriterier.
1. Analysis of Atmospheric Muon Bundles with IceCube
Master-uppsats, Uppsala universitet/HögenergifysikSammanfattning : This work is a preliminary study of the background of a search for dark, long-lived particles in the IceCube detector. The high flux of atmospheric muons in IceCube is considered background to the detector's primary science goal, which is to detect astrophysical neutrinos through the emission of Cherenkov radiation. LÄS MER
2. Determining backgrounds with misidentified leptons in the ATLAS Higgs boson analysis
Master-uppsats, KTH/FysikSammanfattning : This thesis presents an analysis of misidentified leptons in the Higgs boson decaychannel H → W W ∗ → lνlν. Misidentified leptons, resulting from jets misidentifiedas leptons, mimic the signal of a Higgs boson decay, resulting in a backgroundcontribution to the signal. LÄS MER
3. Low-dimensional Magnetism in Novel 2D Honeycomb Materials
Master-uppsats, KTH/Tillämpad fysikSammanfattning : A Kitaev quantum spin liquid is a phase of matter predicted to host excitations that can be used to preform fault-tolerant quantum computation. Though the theoretical prediction of such a state is on firm footing, its realisation in real materials has proven to be elusive. LÄS MER
4. Measuring the vertical muon intensity with the ALTO prototype at Linnaeus University
Kandidat-uppsats, Linnéuniversitetet/Institutionen för fysik och elektroteknik (IFE)Sammanfattning : ALTO is a project, currently in the research and development phase, with the goal of constructing a Very High Energy (VHE) gamma-ray observatory in the southern hemisphere. It will detect the particle content reaching the ground from the interactions of either VHE gamma rays or cosmic rays in the atmosphere known as extensive air showers. LÄS MER
5. Study of pattern recognition of particle tracks with neural networks
Master-uppsats, Uppsala universitet/HögenergifysikSammanfattning : In this project we study the use of neural networks as a tool for particle track pattern recognition with the possibility of its implementation in the Trigger system at the ATLAS experiment [1]. By using a method named Hough transform we created a Convolutional Neural Network (CNN) that is able to train on the transformed images of muons merged with minimum bias. LÄS MER