Jet-Vertex Association at low-luminosity

16 May 2007 David W. MillerSLAC ATLAS Forum

1

Jet-Vertex Association at low-luminosity

David W. MillerDavid W. Miller

SLAC ATLAS ForumSLAC ATLAS Forum

16 May, 200716 May, 2007

David W. MillerDavid W. Miller

SLAC ATLAS ForumSLAC ATLAS Forum

16 May, 200716 May, 2007

• Pileup at ATLAS and the LHC– Composition and generation

• Jet reconstruction in the context of pileup

• The jet-vertex association algorithm– Method and implementation

• First results– Small dataset of ttbar events


2

ATLAS Environment at high luminosity

• We expect ~ 25 interactions per bunch crossing– For L ≈ 1034 cm-2 s-1 and

σpp≈100 mb

• “Hard physics” will only begin at 10-4 per bunch crossing level– And of course, what we are

after is much, much further down…

• We must be able to identify the hard interaction physics from among the soft “pileup”


3

ATLAS pileup simulationSimulated pileup has 2 components:

– Multiple p-p interactions per bunch-crossing

• Poisson distribution with mean determined by luminosity

– Cavern background• Uniformly distributed across

all bunch-crossings with mean determined by luminosity

• Thermal n’s, K's and low-E ɣ's escaping the detector and beam

High Luminosity: 10103434

– 23 p-p interactions – Undefined number

of cavern background

Low Luminosity: 2•102•103333

– 4.6 p-p interactions– 5 cavern BG

Very Low Lumi: 10103333

– 2.3 p-p interactions– 2 cavern BG


4

Data samples• Minimum bias & cavern events are overlayed onto top

sample using the ATLAS job transforms– DC3.005200.T1_McAtNlo_Jimmy– misal1_csc11.005001.pythia_minbias – misal1_csc11.007903.cavernbg_sf05

• In addition, a sample with no signal events (only min-bias overlayed onto min-bias) is generated for comparison

• More details:– Geometry: ATLAS-CSC-01-02-00– Production Release: 12.0.6.4– Also: https://twiki.cern.ch/twiki/bin/view/Atlas/PileupDigitization

• Note that when data becomes available, we will use real minimum bias events to overlay onto simulated data.

https://twiki.cern.ch/twiki/bin/view/Atlas/PileupDigitization


5

Jet-Vertex association with pileup

Min-bias Hard Scatter

CPF [PV] = fCPF [PV] = f

CPF [MB] = 1-fCPF [MB] = 1-f

CPF [PV] = 0CPF [PV] = 0

CPF [MB] = 1CPF [MB] = 1

• Isolate and remove those jets not originating in hard scatter interaction

• Match jets to tracks using ΔR association

• Use these jet-tracks to associate jets to vertices

• Define the charged particle energy fraction (CPF): fraction of track energy in jet for each PV

vtx trkskit

trkskit

k vtxtrkp

vtxtrkpvtxCPF

),(

),()(

DØ & A. Schwartzman


6

Minimum-bias at low luminosity• The minimum bias (MB)

events used as pileupShownShown: 100 events, 3.3 MB int. : 100 events, 3.3 MB int.

per BCper BC< 1 MB jet per event|η| distribution fairly central<Jet Et> ~ 15 GeV

All Jets

All JetsAll Jets


7

ttbar events at low luminosity• 50 events @

lumi = 1033

– 2.3 MB PV– 1 signal PV– 2 cavern BG

• Good PV resolution even with pileup– σXY ≈ 15 μm

– σZ ≈ 55 μm

• 50 events @ lumi = 1033

– 2.3 MB PV– 1 signal PV– 2 cavern BG

• Good PV resolution even with pileup– σXY ≈ 15 μm

– σZ ≈ 55 μm

# Pileup Events


9

Jet kinematics and topology• Higher jet multiplicity than

ttbar alone (as expected)• Most MB jets will have been

removed by Et cut, but not all

The goal of this The goal of this algorithm is to be algorithm is to be able to distinguish able to distinguish which of these jets which of these jets originate in the originate in the hard-scattering hard-scattering vertex, and which vertex, and which are simply high-are simply high-energy minimum energy minimum bias jets.bias jets.

The goal of this The goal of this algorithm is to be algorithm is to be able to distinguish able to distinguish which of these jets which of these jets originate in the originate in the hard-scattering hard-scattering vertex, and which vertex, and which are simply high-are simply high-energy minimum energy minimum bias jets.bias jets.


10

Jet-track matching & selection

ΔR Jet-Trk < 0.4

• Track matching is critical to jet-vertex association. – Currently, only a ΔR cut

• No explicit lepton-Jet overlap removal

Pt > 0.4 GeVPt > 0.4 GeV

Pt < 50 GeVPt < 50 GeV

ΔΔR(jet,trk) < 0.4R(jet,trk) < 0.4

ΔΔZ(rec,mc) < 100Z(rec,mc) < 100μμmm

Pt > 0.4 GeVPt > 0.4 GeV

Pt < 50 GeVPt < 50 GeV

ΔΔR(jet,trk) < 0.4R(jet,trk) < 0.4

ΔΔZ(rec,mc) < 100Z(rec,mc) < 100μμmm


11

Track & vertex multiplicities per jet

• MC Truth flags a vertex as “hard-scatter” or “pileup”

• Reconstruction also “chooses” the hard scatter– Mis-reco: few x %

• The reconstructed tracks and vertices are thus also flagged

• Can identify– Min bias tracks, jets– Fraction jet E from

pileup• 30% Jets with at least

1 associated MB PV

Pileup tracks per jetHard scatterTracks per jet

Jet E vs Ntrks # MB PV per jet

SignificantSignificantSignificantSignificant


12

Min-bias and Hard-scatter Jets

• A simple jet Et cut of 40 GeV would remove nearly all minimum bias jets from the sample

• However, the goal is retain a lower Et cut (say, 20 GeV) and instead use tracks to identify min-bias/pileup jets


13

Charged particle energy fraction

Requiring > 2 tracks

• 3 categories of jets:– Hard scatter– Min-bias– No tracks

• Many min-bias jets do not have > 2 tracks.

ttotal

kttotal

k p

vtxpvtxCPF

)()(


14

Jet rapidity distributions


15

First estimate of CPF efficiency• Crude estimate of

efficiency:

– < 4% mis-identified– Are “composite” jets

(track contributions from hard scatter and MB)

• Really, must use full truth info (not just PV) and evaluate the efficiency as a function of jet Pt and average track Pt

PV) (true

PV) reco(

CPF

CPF


16

Jet Selection using CPF• CPF allows a lower jet Et cut

by using track information• Should remove dependence of

jet multiplicity on # vertices– Expect increasing jet mult. due to

MB


17

Summary and outlook

• A first look at studying jet vertexing in the context of pileup at ATLAS

• Implementation of DØ (A. Schwartzman) CPF algorithm– Further refinements and studies ongoing

• Tasks:– Electron overlap removal– Utilize MC truth in detail to understand contributions to

jets at the particle level– Evaluate CPF efficiency in different samples– Optimization of cuts and parameters in algorithms– Understand why jet multiplicity does not increase as a

function of # vertices as expected

Jet-Vertex Association at low-luminosity

Documents

Transcript of Jet-Vertex Association at low-luminosity