Large R jets and boosted. object tagging in ATLAS. Freiburg, 15/06/2016. #BoostAndNeverLookBack. Physikalisches Institut Universität Heidelberg

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1 Large R jets and boosted object tagging in ATLAS Christoph Anders Physikalisches Institut Universität Heidelberg #BoostAndNeverLookBack Freiburg, 15/06/2016

2 ??? Cambridge-Aachen 2 arxiv: Higgs tagger trimming n-subjetiness Jet substructure large R jets R2D2 BOOST anti kt HEPTopTagger subjets fully hadronic, di-jet mass grooming End of last year! there was a bump

3 Have: Standard Model Want: New physics! Extended gauge sector: Z > tt - W > WZ Extra dimensions: GRS >tt/ww/zz - Susy: stop decays In this context new heavy resonances decaying to pairs of SM bosons (W/Z/H) or top quarks would be nice (we need one to better calibrate our jets!) Hadronic final states? BR(W > hadrons) ~ 2/3 -

4 Detecting particles in ATLAS center of mass energy LHC Run 1: 7 & 8TeV LHC Run 2: 13TeV How about jets? 4

5 Jets Jets: collimated bunches of stable particles originating from partons after hadronization Jet finding: an approximate attempt to reverse engineer this QM process " More than one way to do this! 5 Sequential jet clustering algorithms

6 Sequential jet clustering algorithms Use clusters of calorimeter energy as input particles (also tracks or truth particles can be used) Distance: dij=min(pti 2p,pTj 2p ) ΔRij 2 /R 2 algo: find pair with smallest dij if dij > dib = pti 2p > i is already a jet, remove it else > merge i,j repeat until all particles are clustered into a jet parameters: R: geometrical separation, radius parameter, not a radius! p: energy vs geometry, 2=kt ; 0=C/A ; -2=anti-kt 6

7 kt Cambridge-Aachen Take home message: kt = soft first C/A = closest first anti kt = hard first anti kt Towards Jetography, G. Salam, Eur.Phys.J. C67 (2010)

8 What about BOOST? 8

9 What about BOOST? July 2016 Early bird registration until tomorrow!!! 8

10 9 subjets

11 9 subjets large R jet

12 Angular separation Rule of thumb: standard jet in ATLAS: R= 0.4 JHEP09 (2013) 076 pt>200gev to contain W in R=1.0 jets top in R=1.5 jets 10

13 Two problems Larger jets pick up more junk! How to reject jets from light quarks and gluons? 11

14 recluster into small subjets JHEP 02 (2010) 084 Trimming JHEP09 (2013) 076 ATLAS typical values (for R=1.0 jets): Run 1: Rsub=0.3, fcut = 0.05 Run 2: Rsub=0.2, fcut = remove low pt subjets We ll see this at work in a bit! One easy example:

15 - Side note: lep+jets tt hadronic side leptonic side 13 Graph by D0 experiment

16 - Side note: lep+jets tt study large R jets in data for top decays W decays require BOOST: pt>200gev identify events with 14 Graph by D0 experiment

17 Jet mass Top vs QCD Trimming signal and background JHEP09 (2013) Normalized entries 2 where i = all clusters 0.25 ATLAS Simulation Preliminary anti-k t LCW jets with R=1.0 No jet grooming, no pileup correction s = 14 TeV, 25 ns bunch spacing jet < 1000 GeV jet η <1.2, 500 < p T Pythia8 Z tt (m =2 TeV) Z µ=0 µ=80 µ=140 µ=200 µ= Un-trimmed ATLAS-CONF Leading jet mass [GeV]

18 Jet mass Top vs QCD Trimming signal and background JHEP09 (2013) Normalized Normalized entries entries 2 where i = all clusters 0.25 ATLAS Simulation Preliminary LCW jets with R= ATLAS Simulation Preliminary anti-k t t LCW jets with R=1.0 No Trimmed, jet grooming, pileup no corrected pileup correction s s = = TeV, ns ns bunch spacing jet jet η jet <1.2, < < p p < < 1000 GeV T T Pythia8 Z Z tt tt (m (m jet η =2 =2 TeV) Z Z µ=0 µ=0 µ=80 µ=140 µ=200 µ=300 Un-trimmed Trimmed ATLAS-CONF Leading jet jet mass [GeV]

19 JHEP09 (2013) 076 Trimming signal 0 0 and background 15 ATLAS-CONF Leading jet jet mass [GeV] arxiv: Un-trimmed Trimmed Normalized Normalized entries entries 0.15 jet η anti-k t t LCW jets with R=1.0 No Trimmed, jet grooming, pileup no corrected pileup correction s s = = TeV, ns ns bunch spacing jet jet η jet <1.2, < < p p < < 1000 GeV T T Pythia8 Z Z tt tt (m (m =2 =2 TeV) Z Z!=300!=200!=140!= ATLAS Simulation Preliminary LCW jets with R=1.0!=0!= ATLAS Simulation Preliminary Top vs QCD Works in data too! where i = all clusters 2 Jet mass

20 kt splitting scales go back one step in the kt clustering Z >qq vs QCD Example: Z >qq: symmetric two-body decay: both subjets apart and of similar pt > large d12 For top decay: go back one more step: d23 JHEP09 (2013)

21 N=2 n-subjetiness Observables related to Nsubjet reclusters jet constituents with kt into N subjets subjets define axes within the jet constituent k distance of k to subjet i 17 Signal JHEP 03 (2011) 015 ratio: background arxiv: subjet like 2 subjet like

22 JHEP 12 (2014) 009! Energy correlation functions m of particle in 2-body decay for beta=1 18 Signal no subjets! background arxiv:

23 Variables arxiv: Are the same, apart from the mass cut! W vs Z Compare fixed signal efficiency Jet collections bkg eff = 50% Pick the following: Jet type and radius parameter, e.g. anti kt R=1.0 Groomer and its parameters, e.g. trimming, Rsub=0.3, fcut=5% Choose substructure variables (of course there are many more!) Building a simple W tagger

24 Run 1 boson tagging in data Large R jet mass arxiv: Select D2, before mass cut

25 Efficiency Signal Di-jets (background) 21 arxiv:

26 q q Large R jet W/Z Heavy Resonance W/Z q q Large R jet

27 Back to the start! arxiv: ish Full disclosure: C/A R = 1.2 jets, modified mass-drop filtering (actually no mass drop), Rsub = 0.3 ntracks < 30 Also WW,ZZ. 23

28 Limits on high mass resonance and other final states jet jet No bump in leptonic channels! lep, neutrino + jet arxiv: lep + jet Run 2 will have to tell! Eur. Phys. J. C (2015) 75:209 Eur. Phys. J. C (2015) 75:69 24

29 q q Large R jet On to Run 2 Di-boson searches: W/Z Heavy Resonance W/Z 25 lepton pair or 2. large R jet

30 Multi jet background == fake bosons Looking good! Basics in Run 2 data

31 Simple Run 2 tagger W/Z boson tagger based on: anti kt, R=1.0, Rsub=0.2, fcut=5% Mass and D2 Constant signal efficiency (25% and 50%) ATL-PHYS-PUB

32 Run 2 di-boson (W/Z) searches Channel VV > JJ VV > J ll VV > Jlν VV > Jνν Trigger Large R jet Boson Tag Large R jet, 360GeV 2 with pt>400/200 GeV 50% W/Z + Ntrack<30 Leptons/MET no Backgrounds mutlijet, shape fit in data electron/muon triggers 1 with pt>200 GeV electron/muon triggers 1 with pt>200 GeV MET trigger, 80GeV 1 with pt>200 GeV 50% W/Z 50% W/Z 50% W/Z e + e - / μ + μ - compatible with Z decay Z+jets, from mj sideband MET>100GeV 1 e or mu W+jet mj sideband top b-tagged CR MET>200 GeV Zmumu and btagged ATLAS-CONF

33 Run 2 di-boson (W/Z) searches Channel VV > JJ VV > J ll VV > Jlν VV > Jνν Trigger Large R jet Boson Tag Large R jet, 360GeV 2 with pt>400/200 GeV 50% W/Z + Ntrack<30 Leptons/MET no Backgrounds mutlijet, shape fit in data electron/muon triggers 1 with pt>200 GeV electron/muon triggers 1 with pt>200 GeV MET trigger, 80GeV 1 with pt>200 GeV 50% W/Z 50% W/Z 50% W/Z e + e - / μ + μ - compatible with Z decay Z+jets, from mj sideband MET>100GeV 1 e or mu W+jet mj sideband top b-tagged CR MET>200 GeV Zmumu and btagged ATLAS-CONF

34 Fully hadronic search == Tagging in action 2 large R jets, W or Z tagged, =50%, rej>90% Ntrack<30, exploiting bigger track multiplicity in background, ~30% improvement in sensitivity efficiency checked in data ATLAS-CONF Leading jet, D2 cut 9<Ntrack < 20 Simulation to match data Fit fraction of W/Z in data In data lower by 5%+- 6% > 6% systematic uncertainty 29

35 Evolution in data Full W/Z w/o mass w/o D2 w/o Ntrack No boson tagging WZ 30 ATLAS-CONF ZZ WW

36 ATLAS-CONF Signal eff. & background fit Reco d signal mass Fit! to MC Stable vs mass Low/high mj control region: Fit! to data CR

37 Putting it all together ATLAS-CONF = WZ ZZ WW 32

38 Putting it all together ATLAS-CONF = WZ ZZ WW 32

39 ATLAS-CONF Limits Run 1 excess not excluded Need more data 33

40 The other channels J ll J l# J ## Same conclusion > Need more data! ATLAS-CONF ATLAS-CONF ATLAS-CONF

41 Boosted Higgs bosons b RSG >hh >4b b large R jets h b jets inside large R jets X match small (R=0.2) b-tagged track jets to large R jets h b b 35 larger jets ATL-PHYS- Boost smaller jets

42 Higgs boson tagging b-tagging + Jet substructure jet mass ATL-PHYS-PUB = D2 anti kt R=1.0 Rsub=0.2 fcut=5% Most discrimination from b-tagging, but JSS can help. 36 New in Run 2

43 Back to the original fat jets subjets large R

44 Top tagging Simple taggers possible as for boson tagging Top decays have a few more handles There are more advanced taggers on the market Large R jet Simple tagger example: Select

45 Adv. Tagger Example: JHEP 1010 (2010) 078 HEPTopTagger Identify top to hadron decays with pt top >200GeV Use Cambridge/Aachen R=1.5 jets and their substructure Filter against pile-up b Identify top quarks via mass ratios C/A R=1.5 top candidate top g g q q Pictures G. Kasieczka 39

46 mw/mtop HEPTopTagger in lep+ jet data = m(subjet 2 and 3) m(subjet 1, 2 and 3) top candidate mass 40

47 Efficiency measurement ~40% ~80% Simple Tagger HEPTopTagger ~25-30% ~2-3% 41

48 Fully hadronic tt - resonance search Lots of non top background (QCD) JHEP 1301 (2013)

49 Fully hadronic tt resonance - search (Run 1) It works! JHEP 1301 (2013)

50 ATL-PHYS-PUB Run 2 top tagging ~ constant efficiency Pick two variables 44

51 - tt resonance search in lepton+jet events (Run2) Lepton Large R jet, top tagged Di-top mass ATLAS-CONF main background contains top quarks high efficiency wanted! (comes with low rejection)

52 - tt resonance search in lepton+jet events (Run2) Lepton Large R jet, top tagged Di-top mass ATLAS-CONF main background contains top quarks high! low efficiency wanted (comes with rejection)

53 Jet Reclustering or doing it all backwards Large R jets are great, but they require extra work (calibrations, uncertainties etc) Reclustering: Use standard small R(=0.4) jets as inputs to the large R jet finding! by B. Nachman Advantages: inherit calibrations and uncertainties from well understood small R jets, easy to correlate with MET, faster, Disadvantages: less information used, need to understand close-by-jet effects, it wasn t my idea 46

54 A use case Has been pioneered in ATLAS SUSY analyses How about VLQ: } Many heavy objects to tag! Standard top, W or H taggers not ideal Require a lepton and MET and a few b-tags Reclustered large R jet(s) with mj>100 GeV (i.e. keep H and top) ATLAS-CONF

55 A use case Has been pioneered in ATLAS SUSY analyses } How about VLQ: Many heavy objects to tag! Standard top, W or H taggers not ideal Require a lepton and MET and a few b-tags Reclustered large R jet(s) with mj>100 GeV (i.e. keep H and top) ATLAS-CONF

56 A use case Has been pioneered in ATLAS SUSY analyses How about VLQ: } Many heavy }objects to tag! 1 of many Standard SRs top, W or H taggers not ideal Require a lepton and MET and a few b-tags Reclustered large R jet(s) with mj>100 GeV (i.e. keep H and top) ATLAS-CONF

57 A use case Has been pioneered in ATLAS SUSY analyses How about VLQ: } Many heavy }objects to tag! 1 of many Standard SRs top, W or H taggers not ideal Require a lepton and MET and a few b-tags Reclustered large R jet(s) with mj>100 m}w GeV (i.e. keep H and top) ATLAS-CONF

58 Of course there is more! There will be/ is more W > tb SM W/Z xs Eur. Phys. J. C (2015) 75:165 arxiv: stop search arxiv: SM boosted ttbar xs 48 at 13TeV in Run 2!

59 Of course there is more! Eur. Phys. J. C (2015) 75:165 JHEP 09 (2014 ) 015 W > tb stop search 49 SM W/Z xs arxiv: arxiv: SM boosted ttbar xs W/Z discrimination area subtraction template overlap method There will be more at 13TeV in Run 2! quark gluon tagging q jets mass calibration shower deconstruction in situ JES from top mass subjet calibration variable R jets uncertainty estimation

60 Summary Dramatic increase in understanding of hadronic final states in the last few years Boosted/jet substructure techniques have been shown to work in Run 1 of LHC + been employed in analysis They are even more important at the higher center of mass energy we are running at now First Run 2 results are in > Tagging still works well! We are already thinking about the even more boosted regime G. Salam (not touched on today) 50

61 Closing remark