Summary physics WG

Stan Bentvelsen Trigger and Physics week, June 7th, 2007

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CSC endgame has started Targeting toward finishing the CSC notes

Figures and tables available by September Closing date for MC samples Having preliminary results for the late summer conferences

First draft of the notes ready by October I.e. ready for (first) review

Final papers ready by the end of the year 2007 Remember to use the LaTeX and ROOT standard templates

Atlas detector paper based on rel 12 Getting on steam for doing the physics

Most of the data sets are available in rel12 Crucial samples can use rel13 reco – justify the choice

Fix on AOD for 1 mm bug is understood and under control for a number of practical physics cases

Common tools being developed / cross checks No excuse for ‘waiting’ anymore!

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CSC endgame CSC notes trajectory has an end

Extremely useful exercise to prepare tools to understand the detector data

Extremely useful exercise to get the first realistic physics results out of the data

To my mind the ultimate reach on Atlas’ physics performance is not the main goal of the CSC notes

Scope based on initial data sets E.g. the ‘ultimate top mass’ precision for me is outside the scope

of the CSC notes. Although effects of mis-calibrations and mis-alignments should be assessed.

Gap between performance and physics communities? Clearly got smaller in many areas over the last period

Trigger aware analysis took off in impressive way But improvement possible

If object not reconstructed correctly – go and fix it

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Atlantis display

JiveXML interface to Atlantis Now reads some EventView information in addition to AOD

info. Visualise Eventview objects, labels etc.

Use predefined cuts to select event to write-out for later viewing in Atlantis

When was the last time you visualized your favorite data?

Q. Lu, M. Stockton, J. Thomas

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A.Shibata

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CSC data sets: the 1 mm bug 1 mm bug fixed on AOD level

Allow comparison between 30mm simulation, 1 mm bug and 1 mm bug with fix

Electron scale correctly corrected Run 5200 ttbar events

Electron scale in ttbar eventsA. Shibata

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Data sets: the 1 mm bug Same plot for the jets in ttbar events

Smaller shifts in jets but forward region slightly overscaled Run 5200 ttbar events

A. Shibata

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1 mm bug Reconstructing top

‘commissioning analysis’, i.e. reconstructing top w/o b-tag

Backgrounds included For both 30 mm, 1mm and

1 mm bug fix

Fitted top mass shifts almost 3 GeV due to bug

But AOD fix is effective A. Shibata

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Cookbook generic trigger strategy

C. Potter

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B-group strategy for 1031 : ~100 pb-1

Mainly for understanding the detector using J/Jeeplusstart to look at B->, B->K*/and B->K*/ Use fullscan to find K*/

LV1 muon rates 1031 Estimated by downscaling 1033 numbers

EF numbers Lots more work to do to

complete tables. Input needed from you

for rates & comments & suggestions on the menus

Estimating trigger rates at 1031

Thre Trigger Type

Barrel(Hz) From /K EC(Hz) ALL(Hz)

mu4 Low pT 697 91% 226 932mu6 Low pT 130 79% 94 224

“4 GeV” 1031cm-2s-1

Barrel(Hz)

Endcap(Hz)

/K 133 80beauty 19 21charm 11 12

top 6∙10-4 8∙10-4

W 0.03 0.04TOTAL 163 113

J. Baines

Item Rate (Hz)

2MU4 182MU6 1.7

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Trigger objects & environment

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Trigger redundancies Trigger overlaps in ttbar events

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Trigger redundancies in ttbar

For uncorrelated trigger objects with redundancy in physics channel: can efficiencies be determined from data?

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Trigger Aware Example: H→WW→lnqq Trigger efficiencies

Around 80% after alloffline selections are applied

Trigger does not significantlychange the signal mass distribution

Limited by MC statistics

W. Quayle

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Charged Higgs trigger EF object characteristics wrt offline

Mode tt→(bH)(bW)→(btn)(bln)

Most problematic is the MET Resolution not so good. Without MET the trig

efficiency will drop byfactor two

MET broken in 12.0.6 MET is only ‘global’ trigger, all others based on ROI’s

LV1: currently performing. Loop over all cells, no muons taken into account LV2: add muon to LV1 MET – available in rel13 EF: problematic - no noise suppression applied. Timing issue in unpacking LArg

cells.

EF trigger MET turn-on

C. Potter

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Triggering Susy Many studies based on MET + multijets

Preselection cuts typically ≥ 4 jets, PT > 50 GeV Leading jet PT > 100 GeV MET > 100 GeV Lepton selection, if applicable

Suggest to de-emphasize MET or keep it very loose Also historically MET triggers take time to establish MET has good discrimination power for signal versus

background E.g. do multijet triggers to select SUSY?

Not relying on MET trigger altogether? Thresholds guided by minbias rates (assuming 65 mb)

1jet > 115 GeV, rate: 9.5 ± 3.9 Hz 4jets > 25 GeV, rate: 9.5 ± 3.9 Hz

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Efficiency for SusyExample of SU3 point

Efficiency after offline jet selection cuts

≥ 4 jets, pT > 50 GeV Leading jet pt> 100 GeV

Efficiency without any offline selection cuts

Need alternative in case the offline requirements are loosened on Njet

E.g. rely more on single jet tigger

88% acceptance for SU3 for L1jet>115 GeV

4jet trigger deadG. Redlinger

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Susy and MET trigger MET trigger in HLT in

development For now, assuming only

L1MET To get rate down to EF limit

implies MET>50 GeV To go lower in MET: must

combine MET with jets or leptons

Dijet+MET efficiencies May work, but eats in Susy

efficiency rapidly Color coding according to bsolute

efficiencies for SU3 Also provide good sample for jet

response, needed for QCD bkg estimation

G. Redlinger

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Estimate QCD contribution to MET Determine QCD background in MET, including

normalisation, from data Measure jet smearing using multijet events with one jet

pointing to MET direction in phi MET>60 GeV |Df(MET,jet)|<0.1

Estimate true jet pT as: pT

est=pTrec+MET

Select multijet events with small MET/sqrt(ETsum)

Dominated by QCQ Smear each jet by resolution

function as determined fromdata

Expect to reproduce the tailof the MET

Plot PTrec/pT

estD. Tovey

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Estimate QCD background to MET Method looks promising

Shape of MET distribution from this procedure equivalent to the QCD MC

Normalisation estimated from data by selecting regions in (Njet-MET) space

QCD dominant at small MET, large Njet

D. Tovey

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Dropping MET requirement

Eample in ttbar analysis: Isolated lepton >20 GeV 4 jets with pT>20 GeV 3 of them: >40 GeV MET>20 GeV

Dropping the requirement on the missing ET:

Increase of QCD background Estimated with Atlfast QCD

samples 1,2,3,4,5,6+ parton

samples in Alpgen, MLM matched

LMU Munich

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QCD background in ttbar QCD non prompt leptons in ttbar events

Isolated leptons from semi-leptonic decay in jets Yield estimated as ‘good’ electrons in ttbar muon events

with full simulation Fraction of events with

isolated leptonswith pT>20 GeV: 2∙10-4

Standard Top Standard Top, no MET requirement

Verkerke&vVulpen

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Talking about tops….

Top peaks of various groups Start to speak the same language

Setting the samples & selections is almost debugged

Current issues: Combinatry versus non-ttbar

background How to separate these?

Udine/ictp rel 12 AShibata rel 12

Nikhef rel11

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Susy in Di-lepton+jet+MET Selection straighforward

number of leptons=2, Pt(lep) > 10 GeV number of Jets >= 4,

Pt(J1)>100 GeV, Pt(J2)>50GeV, Pt(J3), Pt(J4)>20 GeV

Bgk: ttbar, Wbb+jets, W+jets, WW+jets.

lqql

g~ q~ l~

~

~p p

Missing energy

LeptonsJets

A sample SUSY decay chain

Same Sign

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Trigger and event selection Many presentations involve trigger menu

Creative proposals for multiple object trigger MET+jets, MET+tau, tau-tau, etc etc.

One of the urgent questions: How do we assess the trigger efficiencies from data? Can we utilizing redundancies of uncorrelated trigger

objects? Somewhat linked: How to assess the (offline) event

selection efficiencies Both needed for absolute normalization – cross section

determinations

Assume that efficiencies and selections are not what they are predicted by MC

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Pile-up and cavern background Its clear now that next year will be setup with beam,

first collisions and 75 ns running Min bias pile-up will not be a major issue Cavern background will certainly be present

Especially analysis with muons will suffer. By how much? Nevertheless: Example pile-up study: VBF H→tt(lh)

Compare pileup events Lumi 2∙1033, pileupCollisions=2.3, include det noise, cavern bkg = 2

S. Tsuno

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Pile-up in VBF H→tt(lh) Jet trigger very active

Big difference by variousgenerators (fragmentation)

Large systematics in rate estimations

Mostly very forward Muon trigger

L1 low pT muon rate increased At EF level increase ~10%

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Decay modes ZZ l+l- l+l- ZW l+l - l WW l+ l-

SM Triple-gauge- bosons couplings New physics control samples

Discovery H ZZ, WW SUSYZ’ WWG WW T ZW ZZ

H

SUSY signal

Ex New analysis: di-boson production

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Separating signal from background

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WW and WZ analyses with BDT How to build a decision tree ?For each node, try to find the best variable and splitting point which gives the best separation based on Gini index.Gini_node = Weight_total*P*(1-P), P is weighted purityCriterion = Gini_father – Gini_left_son – Gini_right_sonVariable is selected as splitter by maximizing the criterion.

How to boost the decision trees?Weights of misclassified events in current tree are increased, thenext tree is built using the same events but with new weights.Typically, one may build few hundred to thousand trees.

How to calculate the event score ?For a given event, if it lands on the signal leaf in one tree, it is given a score of 1, otherwise, -1. The sum (probably weighted) of scores from all trees is the final score of the event.

Ref: B.P. Roe, H.J. Yang, J. Zhu, Y. Liu, I. Stancu, G. McGregor, ”Ref: B.P. Roe, H.J. Yang, J. Zhu, Y. Liu, I. Stancu, G. McGregor, ”Boosted decision trees as an alternative to Boosted decision trees as an alternative to artificial neural networks for particle identificationartificial neural networks for particle identification”, physics/0408124, NIM A543 (2005) 577-584.”, physics/0408124, NIM A543 (2005) 577-584.

Sum of 1000 trees

H. Yang

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Results for WWe+X BDT do seem to work

Background event sample compared to Rome sample increased by a factor of ~10; compared to post Rome sample increased by a factor of ~2.

Improvement: Simple Cuts: S/B ~ 1.1 Boosted Decision Trees with 15 variables: S/B = 5.9

But how to asses the systematics?

S/B =5.9

H. Yang

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Streaming Samples Streaming samples

10 runs with (nominally) 1.8 pb-1/run Same events stored two ways:

Inclusive & exclusive From production: 12.0.6.5 HPTView

Caveats about streaming samples: Trigger table is STR-01

no muon endcaps streaming decision from

release 12.0.3+patches trigger decision from 12.0.6

production csc11 simulation, 12.0.6

reco/calibrations

Stream TriggersJet jet25, jet50, jet90, jet170,

jet300, jet550, 4jet50, 4jet110, sumet1000, sumjet1000

Electron e15i, e25i, 2e15i, e15i&mu10

Muon mu6, mu20, 2mu10Photon g20i, g60, 2g20iTau/MET tau35i, tau35ietmiss45,

jet45etmiss45, jet70etmiss70, etmiss200, etmiss1000

Sample composition is ‘correct’ only for high-pT processes: expect an unnaturally low fake rate

We ‘don’t know’ top kinematics in data: MC@NLO with no weights

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Trigger in stream samples

First check (comparing with earlier studies using MC truth): Overall efficiency vs. electron ET, η, φ: denominator is the number of

tight (isolated) reconstructed electron ‘probe’ candidates from Z decays Clearly also need to measure reconstruction efficiency

this uses 75% of inclusive electron dataset streamtest data has insufficient statistics for a map in

(ET, η, …): can we use other triggers?

(csc11 W MC) L1*L2 efficiency w.r.t. truth

(streaming sample) L1*L2 efficiency w.r.t. reco

LBL

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Calculating luminosity

18 pb-1 is delivered sample luminosity recorded is less (sample prescales, online ‘deadtime’ ) on disk may be even less (reconstruction job errors)

How to find delivered luminosity from AOD files: keep track of used luminosity blocks

create LumiBlock metadata in tags or ntuple files How to apply prescale/deadtime corrections:

LumiCalc: uses metadata ntuples, database prototype Still to-do: (release 12 user tools), validate the DB

FakedTrigger DB forStreaming test

CondDB ESD/AOD/TAG filesTrigger config

LB #s used to make fileTrigger config

reco

Run-lumi DB prototype LB: luminosity,

prescales

Det statusLumi-calc

tool L

diagr

am: R

ichar

d Ha

wking

s

A. Holloway

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Streamtest data: dilepton mass

Udine/ICTP

Offline cuts on jet, lepton, missing ET are sensitive to calibrations

we can measure some efficiencies in data: lepton identification, isolation: reconstructed Z candidates

Derive corrections to apply to MC for energy measurements

calibrate electron energy: Z mass peak missing ET: W missing ET/ MT Jet energy calibrations:

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Top mass and x-sec

92 selecte evtsGood agreement inshape with CSC data

The exclusive ele sample has about 27% to 28% of evts compared to inclusive

ele for commissioning selection.

Udine/ICTP

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Outlook To large extend a Trigger & Physics week

CSC efforts at high intensity Large Atlfast data sets (800M) will be run next week

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backup

Stream test data

Stan Bentvelsen June 6th, 2007

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Reconstruction & calibrations

W+0 jets5104 (12.0.6)vs. inclEle (11.0.X)

•pT e > 25 GeV•no MET cut•Cone 0.4 jets

W+1 jet

Offline cuts on jet, lepton, missing ET are sensitive to calibrations

we can measure some efficiencies in data:

lepton identification, isolation: reconstructed Z candidates

Derive corrections to apply to MC for energy measurements

calibrate electron energy: Z mass peak

missing ET: W missing ET/ transverse mass Jet energy calibrations:

trickier -- constrain errors on the overall scale by comparing to the hadronic W mass

LBL

MC production

Stan Bentvelsen June 6th, 2007

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SUSY MC production

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SUSY MC production

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Top MC: 30 micron samples

Single top resimulation running P. Ferrari

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Top MC production: systematics

Study of ISR/FSR samples for top mass systematics: AcerMC ttbar + various pythia parameters: 500 K each are available

Different samples might be needed for cross-section UE systematics dataset 5565 (same as 5200 without

UE) 500 k ATLFAST B-fragmentation systematics:

with ATLFAST looking at the best choice of parameters using as baseline

sample 5205. Flavour tagging group will also produce some fullsim for that

Pile-up, 100 K events with fullsim have been submitted with version 12.0.6.5. The jobs are running.

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Top MC production: background QCD multijet background events with ALPGEN

ATLFAST/FULLSIM: official production for CSC notes -2pb-1 ||<2.5 and Njets >=4 (no pT cuts), for single top analysis

as request for hard lepton reduces the contribution and 2 pb-1 is enough to evaluate fake leptons from QCD.

9pb-1 of ||<2.5 and Njets >= 5 jet pT>15 waiting for joboption files.

Wbb and Wcc 200 pb-1 i.e. 10K events ALPGEN FULLY SIMULATED

RUN numbers 6280-6287: will enter in 12.0.7 that will start within days.

Wc sample 10k events will be produced in the flavour tagging quota:

job optioons not ready yet

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Top MC: single top signal simulating with ATLFAST t-channel ( and s-channel) single top

events with MC@NLO3.3, which do have spin correlations to compare with toprex.

sytematics:

-ISR samplesa. ISR Lambda_QCD = D*2.0 AND ISR_cutoff = D*0.5  --> tend to increase the jet multiplicity & efficiencyb. ISR Lambda_QCD = D*0.5 AND ISR_cutoff = D*2.0 --> tend to decrease jet multiplicity & eff.

-FSR samplea.  FSR Lambda_QCD = D*2.0 AND FSR_cutoff = D*0.5b.  FSR Lambda_QCD = D*0.5 AND FSR_cutoff = D*2.0

This would mean4 configurations for 2 (3) single-topchannels,  ie 8 (12) dataSets The numbers in parenthesis include the Wt channel

Decision to be taken soon.

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Exotics MC production

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B-physics: MC production

J. Catmore

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Trigger issues Optimize the low luminosity trigger menu

Based on 1031 luminosity See S Rajagopalan last Monday

The draft menu is still not complete Missing trigger items, especially topological triggers Rates/performance are slowly coming in.

Some datasets not yet available Physics input needed

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Layout CSC efforts From trigger to physics Status of various CSC activities

Standard Model B-working group Top physics Higgs Susy Exotics Heavy Ion

Streamingtests as prelude to FDR A priority list

How to spend the summer holidays