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Multi-Model Inference Ranking and Applications to Physics at the Large Hadron Collider

Citation

Lambert, Valere Regis Westbrooke (2014) Multi-Model Inference Ranking and Applications to Physics at the Large Hadron Collider. Senior thesis (Major), California Institute of Technology. doi:10.7907/43RG-P928. https://resolver.caltech.edu/CaltechTHESIS:06122014-143656852

Abstract

In the measurement of the Higgs Boson decaying into two photons the parametrization of an appropriate background model is essential for fitting the Higgs signal mass peak over a continuous background. This diphoton background modeling is crucial in the statistical process of calculating exclusion limits and the significance of observations in comparison to a background-only hypothesis. It is therefore ideal to obtain knowledge of the physical shape for the background mass distribution as the use of an improper function can lead to biases in the observed limits. Using an Information-Theoretic (I-T) approach for valid inference we apply Akaike Information Criterion (AIC) as a measure of the separation for a fitting model from the data. We then implement a multi-model inference ranking method to build a fit-model that closest represents the Standard Model background in 2013 diphoton data recorded by the Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider (LHC). Potential applications and extensions of this model-selection technique are discussed with reference to CMS detector performance measurements as well as in potential physics analyses at future detectors.

Item Type:Thesis (Senior thesis (Major))
Subject Keywords:Multimodel Inference, AIC, Model Selection
Degree Grantor:California Institute of Technology
Division:Physics, Mathematics and Astronomy
Major Option:Physics
Thesis Availability:Public (worldwide access)
Research Advisor(s):
  • Spiropulu, Maria
Thesis Committee:
  • Stone, Edward C. (chair)
  • Libbrecht, Kenneth George
  • Filippone, Bradley W.
  • Frautschi, Steven C.
  • Tombrello, Thomas A.
  • Politzer, Hugh David
  • Adhikari, Rana
Defense Date:27 May 2014
Non-Caltech Author Email:valerelambert (AT) gmail.com
Record Number:CaltechTHESIS:06122014-143656852
Persistent URL:https://resolver.caltech.edu/CaltechTHESIS:06122014-143656852
DOI:10.7907/43RG-P928
Default Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:8520
Collection:CaltechTHESIS
Deposited By: Valere Lambert
Deposited On:12 Jun 2014 22:47
Last Modified:04 Oct 2019 00:05

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