Evidence for single top quark production using Bayesian neural networks
Abstract
We present results of a search for single top quark production in p$$\bar{p}$$ collisions using a dataset of approximately 1 fb-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 σ(p$$\bar{p}$$ → tb + X, tqb + X) = 4.4 ± 1.5 pb.
- Authors:
-
- Florida State Univ., Tallahassee, FL (United States)
- Publication Date:
- Research Org.:
- Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 927940
- Report Number(s):
- FERMILAB-THESIS-2007-58
TRN: US0804754
- DOE Contract Number:
- AC02-07CH11359
- Resource Type:
- Thesis/Dissertation
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS; CROSS SECTIONS; HYPOTHESIS; NEURAL NETWORKS; PRODUCTION; T QUARKS; Experiment-HEP
Citation Formats
Kau, Daekwang. Evidence for single top quark production using Bayesian neural networks. United States: N. p., 2007.
Web. doi:10.2172/927940.
Kau, Daekwang. Evidence for single top quark production using Bayesian neural networks. United States. https://doi.org/10.2172/927940
Kau, Daekwang. 2007.
"Evidence for single top quark production using Bayesian neural networks". United States. https://doi.org/10.2172/927940. https://www.osti.gov/servlets/purl/927940.
@article{osti_927940,
title = {Evidence for single top quark production using Bayesian neural networks},
author = {Kau, Daekwang},
abstractNote = {We present results of a search for single top quark production in p$\bar{p}$ collisions using a dataset of approximately 1 fb-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 σ(p$\bar{p}$ → tb + X, tqb + X) = 4.4 ± 1.5 pb.},
doi = {10.2172/927940},
url = {https://www.osti.gov/biblio/927940},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon Jan 01 00:00:00 EST 2007},
month = {Mon Jan 01 00:00:00 EST 2007}
}