Published March 23, 2019 | Version v1
Report Metadata-only

Strong SUSY at ATLAS and CMS [PowerPoint presentation]

Creators

  • 1. Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States)

Description

Introduction points: LHC performed very well, delivering > 150 fb-1; Huge challenge to quickly process this amount of data; Understand detector & object performance; pTmiss tails very important for SUSY searches; Most results on full Run 2 data set will come in Summer; SUSY searches are expanding; Big inclusive searches complemented by dedicated searches to close gaps in coverage; Machine learning for H, b, c, top,… tagging; and Improved analysis techniques

Availability note (English)

Available from https://www.osti.gov/servlets/purl/1570199; https://www.osti.gov/biblio/1570199; DOE Accepted Manuscript full text, or the publishers Best Available Version will be available free of charge after the embargo period

Additional details

Identifiers

URL
https://www.osti.gov/servlets/purl/1570199; https://www.osti.gov/biblio/1570199;
DOI
10.2172/1570199;

Publishing Information

Imprint Pagination
33 p.
Report number
FERMILAB-SLIDES--19-018-CMS

INIS

Country of Publication
United States
Country of Input or Organization
United States
INIS RN
54043968
Subject category
S43: PARTICLE ACCELERATORS; S71: CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS;
Resource subtype / Literary indicator
Non-conventional Literature
Descriptors DEI
CERN LHC; MACHINE LEARNING; SUPERSYMMETRY
Descriptors DEC
ACCELERATORS; ALGORITHMS; ARTIFICIAL INTELLIGENCE; CYCLIC ACCELERATORS; LEARNING; MATHEMATICAL LOGIC; STORAGE RINGS; SYMMETRY; SYNCHROTRONS

Optional Information

Contract/Grant/Project number
AC02-07CH11359
Collaborations
ATLAS Collaboration; CMS Collaboration
Funding organization
USDOE Office of Science - SC, High Energy Physics (HEP) (United States)
Secondary number(s)
OSTIID--1570199