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Update on Diffractive Dijet Production Search Hardeep Bansil University of Birmingham Birmingham ATLAS Weekly Meeting 08/12/2011.

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Presentation on theme: "Update on Diffractive Dijet Production Search Hardeep Bansil University of Birmingham Birmingham ATLAS Weekly Meeting 08/12/2011."— Presentation transcript:

1 Update on Diffractive Dijet Production Search Hardeep Bansil University of Birmingham Birmingham ATLAS Weekly Meeting 08/12/2011

2 Contents Theory & Motivation Analysis Plots Comparison with Prague analysis Next steps 2

3 Diffractive dijets Look for single diffractive events (pp  pX) – Involve a rapidity gap due to colourless exchange with vacuum quantum numbers: “pomeron” Then look for dijet system within X – Hard diffraction Sensitive to the diffractive structure function (dPDF) of the proton Studied at HERA and Tevatron – At Tevatron, ratio of yields of SD to inclusive dijets ≈ 1% – Likely to be smaller than this at LHC 3

4 Motivation Understand the structure of the diffractive exchange by comparison with predictions from electron-proton data and be able to get a measure of F D jj Measure the ratio of the single diffractive to inclusive dijet events Gap Survival Probability – the chance of the gap between the intact proton and diffractive system being lost due to scattering (affects measured structure function) – Tevatron have Gap Survival Factor of 10 smaller than H1 predictions – Khoze, Martin and Ryskin predict LHC to have GSF around 30 4 Rescatter with p? (ξ)(ξ) Comparison of Tevatron results to H1 predictions Gap destruction by secondary scattering

5 Interesting variables Calculate M X 2 ≈ E p ·(E±p z ) X  ξ X = M X 2 /s Calculate z IP ≈ (E±p z ) jj /(E±p z ) X Study jet (η, E T, M jj ) and forward gap properties Determine differential cross sections for as many of these variables as possible 5 M jj MxMx ξX ξX

6 Gap Finding Algorithm Gap finding based on Soft Diffraction analysis – Divides calorimeter into 49 rings of 0.2 in η – Identifies calorimeter cells where energy significance (= cell energy/noise) large enough that probability of noise cell studied in event is small – Where no cells in ring found above ESig threshold  ring is ‘empty’ – Full details in blue box Determine the size of the biggest forward gap 6 Example Single Diffractive Topology Detector gap definition Calorimeter: no cell above threshold E/σ > S th - probability of noisy cell in ring smaller than 10 -4 (electronic noise only, no pile-up environment) Tracker: no good track above pT > 200 MeV, |η| < 2.5 Truth gap definition No stable particle above pT > 200 MeV Δη F :3.4 |η Start |:4.9 Δη F :3.4 |η Start |:4.9

7 Analysis Using Athena version AtlasProduction-16.6.4.2 Using MinBias stream data10 period A and B ESDs – Run 153030 (period B) excluded (due to noise bursts) – Total ∫L dt = 8.71 nb -1 - calculated using online iLumiCalc tool with L1_MBTS_2 ref. trigger Average for selected runs < 0.15  currently ignore pile-up Anti-Kt jets with R=0.6 or R=0.4: – Require >= 2 jets in event passing loose jet quality cuts – E T Jet1,2 |η| < 4.4 – E T Jet1 > 26 GeV, E T Jet2 > 20 GeV for asymmetric jet E T cuts (NLO), cut values suggested based on work by Radek Zlebcik (Prague) – Jet E T Jet2 limit and η cuts based on 2010 jet energy scale systematic Ask for a forward gap: |η start | = 4.9, Δη F ≥ 2.0 7

8 Asymmetric Jet Cuts Parton level studies of single diffractive dijets Using NLOJET++ and Frixione with cuts on right  Look at NLO negative interference terms (order α 3 ) to cross section If p T of sub-leading jet is 20 GeV, then safe cut for leading jet is at 26 GeV (well within exponential drop in csx) Need someone to take over this work from Radek 8 NLO Cross section plots courtesy of Radek Zlebcik Logarithmic y-axis Linear y-axis

9 Monte Carlo for Analysis Currently using POMWIG LO generator as main comparison – Modifies HERWIG ep photoproduction so e  e+γ becomes p  p+IP – No rapidity gap destruction built in – Generates QCD 2  2 process within diffractive system in different p T ranges (8-17, 17-35, 35-70, 70+ GeV) for SD (system dissociating in ±z direction) – Using MC samples generated by myself (4000 events of each POMWIG sample) Have PYTHIA 6 and PYTHIA 8 Dijet samples to use as background (8-17, 17-35, 35-70, 70-140 GeV) – PYTHIA 8 J0 sample (8-17 GeV) available only with pile up (not used) NLO comparison would be ideal – Need someone to work on this 9

10 Candidate event 10 +η MBTS counters filled -η MBTS counters empty ∆η F =5.2 Large area of calorimeter empty Two jets, one in FCAL (η=3.48) and one in HEC (η=3.05)

11 Ratio of MC to Data suggests a GSF of 15-25 in majority of bins (prev. ≈3) Big factor between PYTHIA and data in the first bin – Should be within a factor of 2 based on inclusive jets analysis By Δη F of 6, ξ = 10 -4.5  M X = 39.4 GeV – cut out phase space for producing pair of 20 GeV jets so get drop in events after this point Dijet samples contribute less at higher gap sizes with new gap algorithm – Still observe forward gaps with sizes of 4, 5, 6 in PYTHIA 6/8 Uncorrected Gap Size Distribution 11 MinBias Data Pomwig SD Pythia 8 Jets Pythia 6 Jets Biggest ND contribution at small Δη F Drop in number of events with Δη F ≥ 6, cuts into phase space POMWIG SD, PYTHIA 6 & 8 Jets weighted relative to luminosity of data runs used and then plotted against MinBias Data

12 To make A compatible with B, scale them to same luminosity as data by applying weighting factor to variables (run dependent) L data – Luminosity of data N gen – Number of events generated σ gen – Csx of events generated N rec – Number of events reconstructed to run over N gen, N rec,σ gen all taken from AMI, checked multiple times but still get big factor difference between data and Truth level cross sections plotted – Show smooth transitions between different pT range samples – Agreement of Pythia samples at high p T (missing P8 J0) Need to understand and fix this issue Normalisation Issues 12

13 POMWIG SD, PYTHIA 6 & 8 Jets weighted relative to luminosity of data runs used and then plotted against MinBias Data Unlike Soft Diffraction, by asking for jets (hard objects) in process, unlikely to see flattening out of data (indicating a diffractive plateau is present) Also tested with lower p T jets (7 GeV) but with similar results – Cannot use PYTHIA 8 for comparison at 7 GeV due to missing 8-17 GeV sample – Drop in events now after forward gap size of 7 as smaller M X is allowed Uncorrected Gap Size Distribution 13 MinBias Data Pomwig SD Pythia 8 Jets Pythia 6 Jets MinBias Data Pomwig SD Pythia 6 Jets Before gap cuts, 20 GeVBefore gap cuts, 7 GeV

14 POMWIG SD, PYTHIA 6 & 8 Jets weighted relative to luminosity of data runs used and then plotted against MinBias Data (all scaled by first bin) Before gap cuts, observe that PYTHIA 6 is best describing MinBias data (until larger forward gap sizes) Pythia 6 has poor model of diffraction so does that suggest First Bin Scaling of Gap Distribution 14 MinBias Data Pomwig SD Pythia 8 Jets Pythia 6 Jets MinBias Data Pomwig SD Pythia 6 Jets Before forward gap cuts, 20 GeV Before forward gap cuts, 7 GeV

15 First bin scaling used and then PYTHIA 6 & 8 Jets subtracted from MinBias Data and plotted against POMWIG SD If (Data – PYTHIA) ≤ 0.0 then do not plot data point Best measure of determining minimum Gap Survival Factor Due to how PYTHIA samples describe MinBias data, get unusual shape in first few bins (MC/Data too large at Δη F =2.0) Best opportunity for studying diffractive dijets may lie with selected candidates having 4.0 < Δη F < 6.0 (GSF ≥ 20 here) First Bin Scaling & Background Subtraction 15 Data – Py8 Pomwig SD Data – Py6 Pomwig SD 20 GeV, MinBias Data – Pythia 620 GeV, MinBias Data – Pythia 8

16 Differential Cross Sections MC samples weighted to lumi of data runs - Differential cross section as a function of forward gap size Some issues with acceptance and errors to fix soon 16 MC/Data ratio suggests GSF of approx. 15 (if not for acceptance issue) MinBias Data Pomwig SD Pythia 6 Pythia 8 Combined Acceptance Weights applied to different samples based on lumi - Migrations can then cause the acceptances to be larger or smaller than expected Needs more statistics

17 Noise Study in “Empty” Events Preliminary look at potential effects of noisy cells destroying gaps in empty events by using RNDM stream Define event as empty by having no reconstructed primary vertex (with 5+ associated tracks) + no MBTS counters fired See that not all events have a full gap (∆η F =9.8) – 47556/7380809 events Looking at cells with high energy significance suggests slightly more activity at +η and φ=-π – Which events pass “Empty” cuts but still have activity? – Is there a new noise burst to consider in these runs? 17 Significant Cells η Significant Cells φ

18 Ratio of SD to ND Dijets Preliminary study to measure the ratio of the single diffractive to inclusive dijet events based on events passing jet cuts as well as gap cuts Only done on MinBias stream (RNDM stream has very low statistics in comparison) On current results, ratio around 0.002%, a lot smaller than at Tevatron where ratio of yields of SD to inclusive dijets ≈ 1% 18 MinBias stream Data : Period A&B (91465899 events total) AntiKt4 Jets (ND)89004AntiKt6 Jets (ND)191682 AntiKt4 Jets + ∆η F >2.0 (SD)173AntiKt6 Jets + ∆η F >2.0 (SD)317 AntiKt4 SD/ND ratio0.00194AntiKt6 SD/ND ratio0.00165

19 Comparison with Prague Group in Prague also looking at diffractive dijets Earlier in analysis but already see difference in strategies Vertex requirement would force ourselves to smaller gap sizes (less likely to see forward jets) Prague agree quite well with inclusive jets analysis for 2010 – How do I test this for only Periods A and B? 19 BirminghamPrague Data used & StreamMinBias 2010 A&BL1Calo/JetTauEtmiss - all 2010 VertexNo requirementOnly 1 vtx (5+ tracks) TriggerMBTS_2MBTS + Jet Pt dependent Preferred SD MCPomwig SDHerwig++ SD Preferred ND MCPythia 8Herwig++ ND

20 Comparison with Prague Herwig++ is C++ version of Pomwig but has known “feature”: factor of 3 increase in cross section Issue with compatibility of hadronisation models between Pomwig (cluster model) and Pythia (string model) Herwig++ ND produces events with very large gaps – Looks wrong Try comparing HERWIG++ & POMWIG SD samples soon Will need to get official Monte Carlo production done soon – Held up until settled on stats required / new filter to simulate larger gaps in events with gaps / move from ESD to dAOD 20 BirminghamPrague Preferred SD MCPomwig SDHerwig++ SD Preferred ND MCPythia 8Herwig++ ND

21 Next steps SHORT TERM Fix normalisation issues Truth level studies to compare MC samples Get cross sections produced soon (with correct errors & acceptances) LONGER TERM Get official production of MC samples in new format Improve gap noise study Make NLO calculations? Check if OTX cuts are an issue 21


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