QCD and d the e Search rch for Exotic tic Physic ysics Holly - PowerPoint PPT Presentation

QCD and d the e Search rch for Exotic tic Physic ysics Holly Pacey 17/07/2019 QCD@LHC2019

2 Why? • The physics of ATLAS pp collisions is mostly QCD. • We produce LOADS of events with jets up to several TeV. • BSM models like to • Be strong: couple to quarks • Be heavy: make high energy resonances. • For new physics searches, being able to control and understand the QCD background is key

3 Conte tents ts 1. Analyses covered 2. QCD background intro and modelling 3. General strategy 4. Dijet analysis 5. Dijet – 1 Isolated lepton analysis 6. Dijet – ISR Photon analysis 7. Conclusion

4 Recent ATLAS results ATLAS-CONF- 2018-015 Dijet+1 Too many analyses with QCD backgrounds to • Analyses Isolated discuss them all! discussed Lepton Focus on recent results using di-jet • in this signatures: QCD dominates! Final states chosen to …. talk • EXOT-2018-05 Dijet + 1 - Probe models with lower Masses ISR photon - Exploit lower momentum triggering alternatives (leptons or photons rather than jets) ATLAS-CONF- - Probe models with higher masses 2019-007 Dijet Main background in all 3 is QCD multijets • - Data Driven background estimate! - QCD MC used for validation only

5 BSM Models with dijet signatures ATLAS-CONF- 2018-015 Dijet+1 Analyses Isolated Sequential Z’ discussed Dark Lepton Standard Matter in this Model W’ talk Excited EXOT-2018-05 Dijet + 1 Quarks ISR photon Charged Higgs More Generic ATLAS-CONF- Generic gaussian 2019-007 gaussian Dijet resonances! resonances Techni- colour

6 Dijet QCD background • Mainly 2-2 scattering in QCD • Dominant in t-channel → very forward compared to possible signals • Can place upper bound on jet rapidity difference: 𝑧 ∗ = 1 1 − 𝑧 𝑘𝑓𝑢 2 2 𝑧 𝑘𝑓𝑢 • High dijet invariant mass M jj Log events smooth & continuously falling spectrum M jj

7 QCD Monte Carlo Dijet+1 Isolated [See Marcello Fanti’s talk] Dijet @LO Scaled Sherpa models Lepton Pythia 8.186 [1] • inclusive photon σ better than pythia in some places [21] LO NNPDF23 PDFs [2] A14 • Dijet + tune [3] 1 ISR Renormalisation/Factorisati • photon on scales = ave. pT of 2 leading jets Reweight to NLOJET++ • [4,5,6,7] Sherpa 2.1.1 [8] • NLO ME merged with • Sherpa Parton shower [9] using ME+PS@LO [10] CT10 PDF [11] •

8 QCD Monte Carlo Dijet+1 Isolated Dijet Lepton Pythia 8.186 [1] • Scaled Sherpa models inclusive photon σ best [21] LO NNPDF23 PDFs [2] A14 • Dijet + tune [3] (Link) NEW PUB note: 1 ISR Renormalisation/Factorisati • Updates to ATLAS photon on scales = ave. pT of 2 QCD MC leading jets configurations... Reweight to NLOJET++ • [4,5,6,7] Coming to an analysis near you! Sherpa 2.1.1 [8] • NLO ME merged with • Sherpa Parton shower [9] using ME+PS@LO [10] CT10 PDF [11] •

9 Strategy – Sliding Window Fit • Model SM bkg by fitting data M jj distribution to a smooth function ⊚ Mainly QCD: smoothly falling background ⊚ M jj from 2 highest 𝑞 𝑈 jets ⊚ → tail: lower mass resolution/stats: wider bins. ⊚ Best function found ⊙ 𝜓 2 p-value with data etc. ⊙ 𝑞 5 introduced for more flexibility at low M jj ⊙ Generally at higher M jj : 3 param: 𝑞 5 = 𝑞 4 =0 or 4 param: 𝑞 5 = 0 ⊙ 𝑌 = Τ 𝑁 𝑡 𝑘𝑘 Example of data & function fit shape from ISR photon analysis

10 Better than using a global fit? Better simultaneous modelling of tail AND low M jj region • Sliding window fit to obtain function parameters + + + ⊚ (1) Take 𝑂 ≤ 𝑂 𝑈𝑝𝑢𝑏𝑚 /2 bins (2) Fit for params Data + + (3) Set as bkg in centre bin if Sliding Window Estimate + Function being fitted good enough fit, else modify + window width / function (4) Slide along so next bin is in the centre… ⊚ Uncertainty = STDev of poisson fluctuations of pseudodata from fit result

11 Strategy – Bkg Fit Validation • • Spurious signal tests Signal injection tests ⊚ In SM BG fit – should not find ⊚ As above but add some given signal! signal events. ⊚ Likelihood test to compare S+B ⊚ See how many of them can be hypothesis (MC sig+bg) to SM extracted in pull. BG fit. ⊚ Ideally the fit identifies all of ⊚ Look for bias in pull the signal you added ( 𝑡𝑗𝑕𝑗𝑜𝑘𝑓𝑑𝑢𝑓𝑒 =0) 𝑡𝑗𝑕𝑗𝑜𝑘𝑓𝑑𝑢𝑓𝑒 −𝑡𝑗𝑕𝑓𝑦𝑢𝑠𝑏𝑑𝑢𝑓𝑒 pull = 𝑣𝑜𝑑𝑓𝑠𝑢𝑏𝑗𝑜𝑢𝑧 expect mean 0, var 1

12 Strategy – BumpHunter • Search for local excesses in + + + M jj distribution: Data + BumpHunter! [12,13] Sliding Window Estimate + • Calculate p-value for bkg- + only hypothesis in each bin + • Use pseudo-experiments to +++++++ + + get global significance and most significant local excess + + + + + + +

13 Dijet Analysis /Event Selection 139 fb -1 data 2015-2018; 𝑡 = 13 TeV • First full run-2 dijet search! ~4x data as previous analysis @ 37fb -1 • Trigger on events with ≥ 1 jet with 𝑞 𝑈 >420 GeV. • Require M jj >1.1 TeV for trigger efficiency. • Events selected with ≥ 2 jets, two highest jet 𝑞 𝑈 s>150 GeV. • |y*| < 0.6 to reduce forward QCD background. Highest mass dijet AntiKt4, R=0.4 event Jets (backup)

14 Dijet Analysis /Bkg Estimate • Sliding window fit over M jj bins ⊚ 4 param nominal fit ⊚ Require fit to give: (1) global chi2 p>0.05 (2) BumpHunter p>0.01 ⊚ If fit fails iteratively try: (1) 𝑞 5 !=0 (2) shrinking window • Validation: ⊚ Signal Injection + spurious signal tests; robust apart from a signal with 15% width/mass at 6 TeV – account for with a systematic uncertainty.

15 Dijet Analysis /Fit • BumpHunter: ⊚ Biggest = 0.8 σ @ 7.052 – 7.326 TeV (blue lines) ⊚ Data consistent with SM background hypothesis! • Uncertainties: ⊚ Dominant: Choice of fit function + params: Compare with estimate using floating 𝑞 5 , look at poisson variations. ⊚ Jet calibration: Jet Energy Scale: 1-3% ⊚ M jj resolution: 2.4-2.9%

16 Dijet Analysis /Results • Limits on q* and gaussian models used HistFitter packages [18] ⊚ 95% Confidence level on upper limit of BR x σ x acceptance ⊚ Uses CLs method with binned profile likelihood ratio [19] • Exclude q* up to 6.7 TeV! 700 GeV better than old 37fb-1 result ☺ • Also place limits on width/mass for generic gaussian peaks

17 Dijet – 1 lepton /Event Selection • First ATLAS run-2 result looking at dijet+1lepton! 79.8fb -1 data 2015-2017; 𝑡 = 13 TeV • Add final state lepton (e or mu) to ⊚ Trigger on lepton – can probe lower M jj >0.22 TeV ⊚ Lower QCD background! (QCD is 90-99% of bkg) • Potential bias from leptons faking jets or signal bumps. ⊚ Study in 3 jet Control Region ⊚ Compare MC to global fit of 5param function ⊚ no deviations, function is appropriate ☺ • “looser” ID electrons more likely to be mis - reconstructed jets… ⊚ Control region: Dijet + 1 loose (and NOT tight) electron. ⊚ Use sliding window fit to compare to MC: Simplest+best fit: 5 param <1 TeV, 3 param single fit above.

18 Dijet – 1 lepton /Bkg Estimate • Check function is appropriate using likelihood fit 𝜓 2 𝑜𝑐𝑗𝑜𝑡 = 1.3 ☺ to MC QCD+Wjets+ttbar. Τ • Fit over M jj ⊚ <1 TeV sliding window fit: 5 param. ⊚ >1 TeV single fit: 3 param. ⊙ Overlaps well with sliding window fit ⊙ params not constrained by low stats in tails. ⊚ Also optimise window sizes – 20 bins best • Validation: ⊚ Spurious signal test: 3 param function fit less accommodating to spurious signals, equally good fit quality.

19 Dijet – 1 lepton /Fit • Bumphunter largest deviation: 3.56 TeV ⊚ Only 0.7 σ – consistent with SM! 50fb @ 0.25 TeV • Main uncertainties: 0.1fb @ 6 TeV ⊚ Function choice: use alternative fit 𝑦 <1 TeV; 𝑞 5 𝑚𝑜 2 𝑦 → Τ 𝑞 5 𝑞 5 =0 >1 TeV. dominant % >4.5 TeV. ⊚ Jet Energy Scale+Resolution dominant <1 TeV @ 1.4% • Model dependent limits on generic gaussian resonances for different width/mass ratios. Limits on cross section x acceptance x efficiency x BR

20 Dijet – 1 lepton /Results • Also place model dependent limits on W’ and technicolour models. Exclude: 1. Sequential Standard Model W ’<2 TeV 2. Technicolour 𝜍 𝑈 <0.5 TeV 1 2

21 Full cuts in Dijet – ISR Analysis /Event Selection backup First ATLAS run-2 result looking at 2 jets +1 ISR photon! 79.8fb -1 data 2015- • 2017; 𝑡 = 13 TeV • Look for lower mass events boosted by 1 ISR photon. 0.225 TeV< M jj <1.1 TeV. ⊚ Lower mass than available with jet triggers Complements existing searches by ATLAS & ⊚ Higher mass than 1 large-radius jet CMS • 4 event categories: ⊚ 2 jets (1) any flavour, (2) b-tagged to enhance sensitivity to resonances preferring b-quarks. ⊚ Events triggered by (A) single photon 𝐹 𝑈 >140 GeV, (B) combined photon+2jet trigger with 𝑞 𝑈 s>50 GeV: combined has higher signal acceptance at higher M jj • Reduce 80% of QCD background again with |y|<0.75

22 Dijet – ISR Analysis /Bkg • • Sliding window fit: Signal injection tests Try 5, 4, 3 param show can find signals with width/mass < 15%