@misc{10481/58793,
year = {2019},
url = {http://hdl.handle.net/10481/58793},
abstract = {This paper describes a strategy for a general
search used by the ATLAS Collaboration to find potential
indications of new physics. Events are classified according
to their final state into many event classes. For each event
class an automated search algorithm tests whether the data
are compatible with the Monte Carlo simulated expectation
in several distributions sensitive to the effects of newphysics.
The significance of a deviation is quantified using pseudoexperiments.
A data selection with a significant deviation
defines a signal region for a dedicated follow-up analysis
with an improved background expectation. The analysis of
the data-derived signal regions on a new dataset allows a statistical
interpretationwithout the large look-elsewhere effect.
The sensitivity of the approach is discussed using Standard
Model processes and benchmark signals of new physics.
As an example, results are shown for 3.2 fb−1 of proton–
proton collision data at a centre-of-mass energy of 13 TeV
collected with the ATLAS detector at the LHC in 2015, in
whichmore than 700 event classes and more than 105 regions
have been analysed. No significant deviations are found and
consequently no data-derived signal regions for a follow-up
analysis have been defined.},
organization = {We acknowledge
the support of ANPCyT, Argentina; YerPhI, Armenia; ARC,
Australia; BMWFW and FWF, Austria; ANAS, Azerbaijan; SSTC,
Belarus; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada;
CERN; CONICYT, Chile; CAS,MOST and NSFC, China; COLCIENCIAS,
Colombia; MSMT CR, MPO CR and VSC CR, Czech Republic;
DNRF and DNSRC, Denmark; IN2P3-CNRS, CEA-DRF/IRFU,
France; SRNSFG, Georgia; BMBF, HGF, and MPG, Germany; GSRT,
Greece; RGC, Hong Kong SAR, China; ISF and Benoziyo Center,
Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO,
Netherlands; RCN, Norway; MNiSW and NCN, Poland; FCT, Portugal;
MNE/IFA, Romania; MES of Russia and NRC KI, Russian Federation;
JINR;MESTD, Serbia; MSSR, Slovakia; ARRS andMIZŠ, Slovenia;
DST/NRF, South Africa; MINECO, Spain; SRC and Wallenberg
Foundation, Sweden; SERI, SNSF and Cantons of Bern and Geneva,
Switzerland; MOST, Taiwan; TAEK, Turkey; STFC, United Kingdom;
DOE and NSF, United States of America. In addition, individual groups
and members have received support from BCKDF, CANARIE, CRC
and Compute Canada, Canada; COST, ERC, ERDF, Horizon 2020, and
Marie Skłodowska-Curie Actions, European Union; Investissements d’
Avenir Labex and Idex, ANR, France; DFG and AvH Foundation, Germany;
Herakleitos,Thales and Aristeia programmes co-financed by EUESF
and the Greek NSRF, Greece; BSF-NSF and GIF, Israel; CERCA
Programme Generalitat de Catalunya, Spain; The Royal Society and
Leverhulme Trust, United Kingdom.},
publisher = {Springer Nature},
title = {A strategy for a general search for new phenomena using data-derived signal regions and its application within the ATLAS experiment},
doi = {10.1140/epjc/s10052-019-6540-y},
author = {Aaboud, M. and Aguilar Saavedra, Juan Antonio and Atlas Collaboration},
}