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This content will become publicly available on May 27, 2017

Title: Determination of the WW polarization fractions in ppW±W±jj using a deep machine learning technique

The unitarization of the longitudinal vector boson scattering (VBS) cross section by the Higgs boson is a fundamental prediction of the Standard Model which has not been experimentally verified. One of the most promising ways to measure VBS uses events containing two leptonically decaying same-electric-charge W bosons produced in association with two jets. However, the angular distributions of the leptons in the W boson rest frame, which are commonly used to fit polarization fractions, are not readily available in this process due to the presence of two neutrinos in the final state. In this paper we present a method to alleviate this problem by using a deep machine learning technique to recover these angular distributions from measurable event kinematics and demonstrate how the longitudinal-longitudinal scattering fraction could be studied. Furthermore, we show that this method doubles the expected sensitivity when compared to previous proposals.
Authors:
 [1] ;  [1] ;  [2] ;  [1]
  1. Univ. of Michigan, Ann Arbor, MI (United States)
  2. Brookhaven National Lab. (BNL), Upton, NY (United States)
Publication Date:
OSTI Identifier:
1335491
Report Number(s):
BNL--112187-2016-JA
Journal ID: ISSN 2470-0010; PRVDAQ
Grant/Contract Number:
SC00112704
Type:
Accepted Manuscript
Journal Name:
Physical Review D
Additional Journal Information:
Journal Volume: 93; Journal Issue: 9; Journal ID: ISSN 2470-0010
Publisher:
American Physical Society (APS)
Research Org:
Brookhaven National Laboratory (BNL), Upton, NY (United States)
Sponsoring Org:
USDOE Office of Science (SC), High Energy Physics (HEP) (SC-25)
Country of Publication:
United States
Language:
English
Subject:
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS