Evidence for single top quark production using Bayesian neural networks

PDF Version Also Available for Download.

Description

We present results of a search for single top quark production in p{bar p} collisions using a dataset of approximately 1 fb{sup -1} collected with the D0 detector. This analysis considers the muon+jets and electron+jets final states and makes use of Bayesian neural networks to separate the expected signals from backgrounds. The observed excess is associated with a p-value of 0.081%, assuming the background-only hypothesis, which corresponds to an excess over background of 3.2 standard deviations for a Gaussian density. The p-value computed using the SM signal cross section of 2.9 pb is 1.6%, corresponding to an expected significance of ... continued below

Physical Description

150 pages

Creation Information

Kau, Daekwang August 1, 2007.

Context

This thesis or dissertation is part of the collection entitled: Office of Scientific & Technical Information Technical Reports and was provided by UNT Libraries Government Documents Department to Digital Library, a digital repository hosted by the UNT Libraries. More information about this document can be viewed below.

Who

People and organizations associated with either the creation of this thesis or dissertation or its content.

Author

Publisher

Provided By

UNT Libraries Government Documents Department

Serving as both a federal and a state depository library, the UNT Libraries Government Documents Department maintains millions of items in a variety of formats. The department is a member of the FDLP Content Partnerships Program and an Affiliated Archive of the National Archives.

Contact Us

What

Descriptive information to help identify this thesis or dissertation. Follow the links below to find similar items on the Digital Library.

Description

We present results of a search for single top quark production in p{bar p} collisions using a dataset of approximately 1 fb{sup -1} collected with the D0 detector. This analysis considers the muon+jets and electron+jets final states and makes use of Bayesian neural networks to separate the expected signals from backgrounds. The observed excess is associated with a p-value of 0.081%, assuming the background-only hypothesis, which corresponds to an excess over background of 3.2 standard deviations for a Gaussian density. The p-value computed using the SM signal cross section of 2.9 pb is 1.6%, corresponding to an expected significance of 2.2 standard deviations. Assuming the observed excess is due to single top production, we measure a single top quark production cross section of {sigma}(p{bar p} {yields} tb + X, tqb + X) = 4.4 {+-} 1.5 pb.

Physical Description

150 pages

Language

Identifier

Unique identifying numbers for this document in the Digital Library or other systems.

  • Report No.: FERMILAB-THESIS-2007-58
  • Grant Number: AC02-07CH11359
  • DOI: 10.2172/927940 | External Link
  • Office of Scientific & Technical Information Report Number: 927940
  • Archival Resource Key: ark:/67531/metadc894236

Collections

This document is part of the following collection of related materials.

Office of Scientific & Technical Information Technical Reports

Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

Office of Scientific and Technical Information (OSTI) is the Department of Energy (DOE) office that collects, preserves, and disseminates DOE-sponsored research and development (R&D) results that are the outcomes of R&D projects or other funded activities at DOE labs and facilities nationwide and grantees at universities and other institutions.

What responsibilities do I have when using this thesis or dissertation?

When

Dates and time periods associated with this thesis or dissertation.

Creation Date

  • August 1, 2007

Added to The UNT Digital Library

  • Sept. 27, 2016, 1:39 a.m.

Description Last Updated

  • Dec. 7, 2016, 11:23 a.m.

Usage Statistics

When was this document last used?

Yesterday: 0
Past 30 days: 0
Total Uses: 1

Interact With This Thesis Or Dissertation

Here are some suggestions for what to do next.

Start Reading

PDF Version Also Available for Download.

International Image Interoperability Framework

IIF Logo

We support the IIIF Presentation API

Kau, Daekwang. Evidence for single top quark production using Bayesian neural networks, thesis or dissertation, August 1, 2007; Batavia, Illinois. (digital.library.unt.edu/ark:/67531/metadc894236/: accessed July 22, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.