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Searches for physics beyond the Standard Model using dijet distributions in ATLAS Lene Bryngemark Lund University Uppsala, October 1 Analysis idea L Bryngemark (Lund University) BSM searches with dijets in ATLAS Uppsala, October 1 2 / 30


  1. Searches for physics beyond the Standard Model using dijet distributions in ATLAS Lene Bryngemark Lund University Uppsala, October 1

  2. Analysis idea L Bryngemark (Lund University) BSM searches with dijets in ATLAS Uppsala, October 1 2 / 30

  3. Analysis idea - The LHC is at the energy frontier – even more so soon! - Would be a waste at this point in time to not make use of available energy - We don’t know what awaits us, so we want broad searches Method: invariant mass and angular distributions of the hardest jet pair (dijet), with moderate cuts. L Bryngemark (Lund University) BSM searches with dijets in ATLAS Uppsala, October 1 2 / 30

  4. Why dijets? • Access to energy frontier - highest mass reach - smallest scales • Hadron collider: partons in – partons out L Bryngemark (Lund University) BSM searches with dijets in ATLAS Uppsala, October 1 3 / 30

  5. But aren’t jets just too messy? What is a jet? The output of a jet finding algorithm. ⇒ need to be defined such that they sensibly find something corresponding to a collimated spray of particles with partonic origin Jets (or jet algorithms) are the bullies of the event! Don’t need to worry about - isolation - charge - fakes - vertex distance parameter ⇒ dijets are in fact a very clean topology! L Bryngemark (Lund University) BSM searches with dijets in ATLAS Uppsala, October 1 4 / 30

  6. But is this really true?? Jets should be intrinsically sensitive to pile-up. • 10-20 simultaneous proton collisions in 2012 and 2015 • signal from these events piles up in the calorimeter read-out - contributes energy (positive or negative) within the jet - distorts p T measurement (scale and resolution) - distorts mass (and other single jet structure) measurement(s) - contributes extra jets ⇒ pile-up is a potential hurdle; suddenly “isolation”, fakes and vertex reconstruction could start to matter! L Bryngemark (Lund University) BSM searches with dijets in ATLAS Uppsala, October 1 5 / 30

  7. Solution: correct for pile-up Imagine we could measure • how much pile-up there is in a given event • how susceptible each individual jet is to pile-up Then we could correct for it! L Bryngemark (Lund University) BSM searches with dijets in ATLAS Uppsala, October 1 6 / 30

  8. Solution: correct for pile-up ... and in fact we can: 0.14 Normalised entries ATLAS Simulation Preliminary 0.12 ≤ 〈 µ 〉 20 < 21 N = 6 N = 10 PV PV N = 14 N = 18 0.1 PV PV Pythia Dijet s = 8 TeV 0.08 LCW TopoClusters 0.06 0.04 0.02 0 0 5 10 15 20 25 30 ρ [GeV] The Anti-k t jet clustering algorithm , M. Cacciari, G. P. Salam, G. Soyez JHEP 0804 (2008) 063 • measure the median p T density ( ρ ) in the event - this is dominated by low- p T “jets” as found by the k t algorithm • the area A is a measure of how much pile-up a jet will contain ⇒ subtract ρ × A from the jet p T . This is the jet-area based pile-up correction implemented in ATLAS and used in most analyses since 2012 data taking. L Bryngemark (Lund University) BSM searches with dijets in ATLAS Uppsala, October 1 7 / 30

  9. Performance 18 [GeV] 1 13 [GeV] ) [GeV] ATLAS Simulation Preliminary ATLAS Simulation Preliminary 16 ATLAS Preliminary 0.8 12 Pythia Dijets 2012 Pythia Dijet s =8 TeV uncorrected 〉 Z → + jets ρ µ µ PV f( 〈 µ 〉 , N ) correction anti-k LCW R=0.4 anti-k LCW R=0.6 14 true t 〈 PV N t ≤ true ρ × T 11 20 p < 30 GeV A correction LCW Topoclusters 0.6 - p T ∂ | η | < 2.4 / 12 T p reco 10 ∂ 0.4 T 10 RMS(p 9 0.2 8 8 6 0 Powheg+Pythia8 MC 7 4 -0.2 Alpgen+Herwig MC Before any correction 2 ρ × 6 After A subtraction Data -0.4 After residual correction 0 5 5 10 15 20 25 30 35 0 0.5 1 1.5 2 2.5 3 3.5 4 5 10 15 20 25 30 35 40 η 〈 µ 〉 | | 〈 〉 µ 6 > 20 GeV 5.5 ATLAS Preliminary MC, No Correction Z → µ µ + jets Data, No Correction • correction goes to 0 in limit of no pile-up 5 T MC, Area Correction , p anti-k LCW R = 0.4 t 〉 ≤ η ≤ Data, Area Correction jet 4.5 0.0 | | 2.1 N 〈 • reduced dependence of jet p T on pile-up 4 3.5 • removes some of the resolution smearing 3 2.5 introduced by pile-up 2 1.1 0 5 10 15 20 25 30 35 40 Data/MC 1.05 • brings the number of pile-up jets down 1 0.95 0.9 0 5 10 15 20 25 30 35 40 〈 µ 〉 After correction we can safely go back to using the bullying jets! L Bryngemark (Lund University) BSM searches with dijets in ATLAS Uppsala, October 1 8 / 30

  10. Jets in ATLAS EM or LCW Jet area based pile- Residual pile-up Origin Correction constituent scale jets up correction correction Jet finding applied to Changes the jet direction Function of µ and NPV 
 Function of event pile-up topological clusters at to point to the primary applied to the jet at energy density and jet area EM or LCW scale vertex. Does not affect E. constituent scale Global sequential Residual in-situ Absolute EtaJES calibration calibration Corrects the jet 4-vector Based on tracking and A final residual calibration to the particle level scale. muon activity behind jets. is derived using in-situ Both the energy and Reduces flavour dependence measurements and is direction are calibrated. and energy leakage effects. applied only to data The other steps in the calibration chain: • bring the jets to “particle level” energy (Jet Energy Scale, JES) • ensure that different energy response in different detector regions is compensated for • makes use of a number of in-situ techniques (using a reference object in data to restore p T balance) L Bryngemark (Lund University) BSM searches with dijets in ATLAS Uppsala, October 1 9 / 30

  11. The dijet search L Bryngemark (Lund University) BSM searches with dijets in ATLAS Uppsala, October 1 10 / 30

  12. Search strategy Recall the method: invariant mass and angular distributions of the hardest jet pair (dijet), with moderate cuts. QCD is an overwhelming background! Make use of the knowledge: QCD BSM • No new scales above top mass • A new scale (particle mass, – smooth mass distributions interaction) – feature in the mass spectrum • Incoming partons predominantly undergo • New particle production or new small-angle scattering interaction predominantly ( t -channel) isotropic ( s -channel like) • Probe the scale: bin in dijet mass • Find the isotropic events: bin in jet rapidity difference L Bryngemark (Lund University) BSM searches with dijets in ATLAS Uppsala, October 1 11 / 30

  13. - Use lowest unprescaled single jet trigger y B = y 1 + y 2 2 ⇒ dictates leading jet p T > 410 GeV y ∗ = y 1 − y 2 - Two or more anti-k t 0.4 jets 2 χ = e 2 | y ∗ | (pile-up dictates second jet p T > 50 GeV) - m jj cut for unbiased kinematics more QCD-like • The distribution in χ (or y ∗ ) is our isotropy measure • Rapidity is additive – measure in the dijet frame more BSM-like This talk refers to two searches: Search for New Phenomena in the Dijet Angular Distributions in Proton-Proton Collisions at √ s = 8 TeV with the ATLAS Detector, Phys. Rev. Lett., 114:221802, 2015. arXiv link Search for New Phenomena in Dijet Mass and Angular Distributions with the ATLAS Detector at √ s = 13 TeV, ATLAS-CONF-2015-042, Aug 2015. CDS link L Bryngemark (Lund University) BSM searches with dijets in ATLAS Uppsala, October 1 12 / 30

  14. Event selection Angular distribution search: Mass resonance search: - | y ∗ | < 1.7 - | y ∗ | < 0.6 - | y B | < 1.1 (suppress QCD) - m jj > 2.5 TeV - m jj > 1.1 TeV At high m jj - Cut on y ∗ - Bin (coarsely) in m jj - Prediction for SM shape (lowest - Fit to smooth SM background – relies order: flat!) – relies on modelling “only” on good fit function choice - Deviation at low χ for some m jj ⇒ - BumpHunt for most discrepant region in m jj ⇒ discovery, or, limit setting discovery (or else, limit setting) ⇒ sensitive to wide or non-resonant ⇒ sensitive to narrow resonances (fit phenomena swallows other deviations) Maximise discovery potential by exploiting this complementarity! L Bryngemark (Lund University) BSM searches with dijets in ATLAS Uppsala, October 1 13 / 30

  15. The search: (angular) 8 and 13 TeV Spring: • Used 17.3 fb − 1 of 8 TeV data • Mature data set, collected since a long time • Partial data set to validate search Why this rush? Summer: • Used 80 pb − 1 of 13 TeV data • The first approved ATLAS search • Lots of validation work on-the-fly within the group • Analysis strategy, cuts etc already set in stone before data taking started L Bryngemark (Lund University) BSM searches with dijets in ATLAS Uppsala, October 1 14 / 30

  16. The search: (angular) 8 and 13 TeV Spring: • Used 17.3 fb − 1 of 8 TeV data • Mature data set, collected since a long W.J. Stirling, private communication time WJS2013 100 ratios of LHC parton luminosities: 13 TeV / 8 TeV • Partial data set to validate search gg _ luminosity ratio Σ qq qg Summer: 10 • Used 80 pb − 1 of 13 TeV data • The first approved ATLAS search MSTW2008NLO 1 100 1000 M X (GeV) • Lots of validation work on-the-fly within the group Discovery potential! • Analysis strategy, cuts etc already set in stone before data taking started L Bryngemark (Lund University) BSM searches with dijets in ATLAS Uppsala, October 1 14 / 30

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