1

Update on D0 reconstruction using Vertexing (TPC+SSD+SVT)

I. Secondary micro-vertexing methods

II. Reports on tests performed with :A. Simulation : pure D0 sample

B. Simulation : mixed D0 sample in AuAu hijing

C. Real data

III. summary

BNL : Y. Fisyak, V. PerevoztchikovKSU : J. Bouchet, J. Joseph, S. Margetis, J. VanFossenSubatech : W. Borowski, A. Geromitsos, S. Kabana,

2

Fitting approaches for secondary vertices

• We are investigating 3-methods1. A Linear Fit approach : three lines fit with errors (two tracks plus a parent from the event vertex).2. A Helix swimming to DCA of the two track helices (V0-like) :

a. using the global track parameters to reconstruct helices (StPhysicalHelix) of both tracks candidates. b. using the parameters from StDcaGeometry 3. A Full Helix Fit with errors (a.k.a. TCFit)

- it will allow momentum dependent cut using the full track information.

• GOAL : To know with precision the position of secondary vertex of decaying particle to apply topological cut.Challenging for charmed particles because of the small c (for D0, c ~122 µm)

All this work is directly applicable to HFT

3

We have reported a discrepancy when using the helix swimming (each panel shows the correlation of the 2nd vertex reconstructed vs 2nd vertex from GEANT, for pure D0),for the 3 methods

(top to bottom) : an horizontal band, ie

GEANT says that two tracks come from common point but helix swim finds large DCA at secondary vertex->not real minimum but something else.

The linear fit method shows no correlation (abandoned)

• it is understood now as daughter tracks decaying back-to-back :•http://cnr2.kent.edu/~vanfossen/MySTARPage/D0_uVertexing/Entries/2009/10/15_Pure_D0_secVtx_Reco_and_Phi.htmlc

Reconstructed X Y Z

Po

siti

on

of

dec

ay v

erte

x -

GE

AN

T

DC

AG

Lin

ear

fit

glo

bal

J. VanFossen

4

Low pT D0 (i)

• The daughters are decaying back to back and the parallelism causes poor resolution

• D0 momentum almost null for daughters ~ 18030 deg.

• Want to exploit this correlation to find a possible D0 signal in low momentum.

J. Joseph

5

Low pT D0 (ii)

6

Workshop@subatech

• In december, there was a workshop in Nantes about the micro-vertexing techniques

• Talks can be found here : http://drupal.star.bnl.gov/STAR/blog/bouchet/2009/dec/21/micro-

vertexing-workshop-subatech-15-17-dec-2009

• Work done by W. Borowski and A. Geromitsos : http://www.star.bnl.gov/~borowski/evo/09-12-17

look on CuCu data (btag sample) for e-D0 correlation and evaluate , for the D0, it’s characteristics (decay length, dca between daughters) by doing selection based on S/B ,where S = pure D0 and B= real data

7

Evaluation of Full Fit (TCFIT)

Strategy :1. Use pure D0 sample to find cuts and check that it works (3k events)2. Use mixed sample : 1 D0 embedded in Hijing event (10k events): Use y2007g geometry (last updated for AuAu in simu : http://drupal.star.bnl.gov/STAR/comp/prod/MCGeometry Follow these different steps :

a) Produce AuAu MB 200GeV as backgroundb) Produce 1 D0 per eventc) Mix fz files from background and D0

d) Do the reconstruction with slow simulation for the TPC+ silicon detectors.

Analyze MuDst.root file (it consists in reconstructed tracks), with same code used for real data analysis)

3. Look at the real data using cuts found in 1. and 2.

*For step 1. and 2., D0 is forced (BR =100%) to decay in K-π+

8

A few words on the Full Helix Fit

• TCFIT is a least square fit of the decay vertex, under constraints. [1]• In 2 bodies decay, combine 2 tracks under the constraint that they’re coming from a

common point.• Add constraints (momentum conservation, mass hypothesis) to minimize of the 2 (The

probability is the minimization of the 2 of the fit [3])• Code from [2] uses 1 constraint (decay length) and returns its value, probability and

total 2.• In the next slides, I compared these results (TCFIT) with the helix swimming method

and the input from GEANT.

2 = ∑ (qi-h(x,pi))T V-1i (qi-h(x,pi))

tracks i

measured track parameters

covariance matrixof measured track

parameters

[1]Decay Chain Fitting with a Kalman Filter,W. D. Hulsbergen http://arxiv.org/abs/physics/0503191[2]$Star/StRoot/StarRoot/TCFit.cxx[3]http://en.wikipedia.org/wiki/Chi-square_distribution

Parametrisationof the track

(helix)

9

A) Probability plots : pure D0 sample• For the pure D0 sample :

Expect flat distribution for pure D0

Expect a peak at low probability and a decreasing curve for background

• TCFIT (as implemented) uses 1 constraint fit : momentum conservation at decay vertex

• Peak at probability <.01 still here for expected signal (red): Underestimation of errors (errors of TCFIT ~ hits

error + track error When increasing the track errors, we observe the

probability distribution gets an assymetry being more at large probability. :

http://www.star.bnl.gov/~bouchet/TCFIT/covMatrix.htm

#entries(probability<10%) / all Entries

–All : 35.5%–K-+ : 34.48%–K+- : 37.14%

we choose to apply a cut at probability > .01 to remove the wrong topological decays calculated by TCFIT.

10

Signed decay length (TCFIT) vs decay length (THelix)

Probability>0.01

Pure D0 sample

11

• all the next plots have pT >1

• decay length from GEANT is the distance (in 3d) between the componants of the PV and the vertex associated to track with GEANT_ID = 37 (D0)

rmsmean

rmsmean

Pure D0 sample

No cut on the probability

Signed decay length (TCFIT) vs decay length (GEANT)

12

rmsmean

rmsmean

Pure D0 sampleProbability>0.01

Signed decay length (TCFIT) vs decay length (GEANT)

13

Comments

• we see :• a correlation between the decay length from TCFIT and the decay length calculated by the helix swimming.• a nice correlation between the decay length from TCFIT and the decay length in GEANT.

• We reported previously (J. VanFossen) the correlation between the decay length calculated by the helix swimming and GEANT.

• There is no systematic shift in reconstructed quantities (mean~0) and the resolution is about 250 microns, independent of pt (expected for SSD+SSD’s resolutions)

14

slength based cuts investigation

All pair tracks Unlike sign Same sign

Goal : use the results from TCFIT (decay length, its error and probability) toapply topological cuts[Jonathan what are the plots? Data, simulation?]

15

Subtraction:positive-negative L/dL contribution

• For the K-+ case : subtraction of # of entries bin to bin first positive bin entries are subtracted with first

negative bin, and so on

First negativebin

First positivebin

difference

16

B) Probability of TCFIT : mixed sample

zoom

• Same observation as the pure sample, peak at very low probability is observed Next slide : explanation of the cut N < 200 tracks.

Number of tracks < 200

Number of tracks < 200

All pair tracks Unlike sign Same sign

All pair tracks Unlike sign Same sign

17

Invariant Mass plots

No cuts on N = number of primary tracks (per event)

N < 200

s/n ~12.3

All the following plots are All the following plots are from mix Dfrom mix D00 sample (SIMULATION) sample (SIMULATION)

•Check : plots w/o any cuts on decay length

nor probability of TCFIT•Fit of mass+background :

Linear + Breit-Wigner where the fitfunction is :

a + bMreco + Γ/[(Mreco -MPDG)2 + (Γ/2)2 ]

• We used the cut N < 200 based on previous observation where a clear signal appears• It would be easier to investigate the effects of other cuts if already a signal is present.

18

Unlike-like sign invariant mass plots

N = number of primary tracks

19

Unlike-like sign subtracted invariant mass plots

Number of Primary Tracks < 500 400 300 200 100 50

s/n 4.72 5.74 9.06 11.84 16.07 16.21

20

Cut on low multiplicities

We were using a cut (<200) on the number of primary track N to get a signal in simu/mix data.• The plot shows the number of primary tracks (per event) for real data :

• we cut the ‘interesting’ part of the event where the S/sqrt(B) is higher as S scales with binary collisions and B as N2 so sqrt(B)~ # of participants

•In simu we embed one D0 per event flat in pT so correlation with real data is complex

1 D0 per event0 2000 tracks

need other cuts to remove/reduce the huge combinatoric background

21

Applying a positive cut L/dL >2 (only)

no cut

with The cut

• When applying only the cut on L/dL, a peak at the invariant mass of the D0 is appearing we can bypass the multiplicity cut

22

summary

L/dL No cut >2 >3 >1.5 >|2| >|1.5|

s/n(BRTW macro)

3.86 5.6 4.9 4.7 4.0 4.3

• Only positive cut has to be applied. • cuts like |L/dL| is not correct since it also selects slength < 0 (=wrong topological decay fitting)

23

c) Real data-QA : Scan of DCA resolution - run 7

• MinBias ,Production2 Issues Improvement for DCA resolution estimation :

• Dependence with η• Dependence with particle Id

• Cuts

|zvertex |<5 cm : to have a clean sampleTPC hits> 15|| in SSD range (~ ||<1.2)

pT >0.1• Fit function :

Reflect the (detector+alignment) resolution and Multiple Coulomb ScatteringFit done for 0.2 < 1/P < 5In the next plots, x-axis = day number (day 110 = April, 20th, day 170 = June,19th)DCA resolution@1GeV (for tracks with N=2,3,4) vs day number to study stability of DCA resolution.

• 4(ssd+svt)3(svt only) silicon hits ,

pointing resolution ~ 220 m at P = 1GeV/c

•The details are here :

–Minbias per run:

http://drupal.star.bnl.gov/STAR/system/files/test_histo_MB_allDetails.pdf

–Production2 per run :

http://drupal.star.bnl.gov/STAR/system/files/test_histo_P2_allDetails.pdf

–Minbias, day110 : DCA resolution per eta-phi slices:

http://drupal.star.bnl.gov/STAR/system/files/Eta_Phi_histo_Allsilicon_noerrorsbar.pdf

24

Pointing resolution

MinBias Production 2

The idea is to use tracks with silicon hits (3 or 4) to reach enough DCA pointing resolution to make cuts based on DCA of daughters. (from the K-π+ association)

Stable during the run.

The more each track has silicon hits, the better the pointing resolution is.

But it represents a small fraction.

PointingResolution

Number ofTracks with 0,1,2,3,4 siliconhits

25

Real Data (production2)

• Up to now (01/10) :

~ 500000 events

170000 events after vertex cuts

The removal of the cut on the number of tracks will allow us to explore the full event (not only low multiplicities).

• All combinations• after dEdx + momentum cuts • after inv. Mass window cut• after TCFIT cuts

•This sample will be our working samplefor cut studies.

Cuts applied directlyin the code

26

slength /slength_error

• The plots show the signed decay length divided by its error for all pair tracks (left) and pairs tracks requiring 3 or more silicon hits (right) as a function of the Kπ pair pT. Note : we consider only the K-π+ combination.

• L/dL has a flat distribution around L/dL ~ 2

27

Invariant mass vs L/dL cut (no silicon hit cut)

•Need more statistic to see the effect of largeL/dL cut.•A cut based on the trackquality (ie its DCA/DCA ) as wellmay be needed to select only ‘good’ tracks.

28

Invariant mass vs L/dL cut (silicon hit>2)

29

Investigation of other cuts

• In Andrea Dainese’s thesis[1], he used a combination of cuts based on the product of DCA of daughters to the primary vertex (PV) and the angle formed by the D0 momentum and the vector joining the PV and secondary vertex.

Negative values for D0 signal

[1] :arXiv:nucl-ex/0311004

30

For the pure sample

background : K+π-signal : K-π+

signal : K-π+

background : K+π-

31

Summary/ next steps

• TCFIT : the full helix fit with errors (cov. matrix of tracks) is implemented, tested and used now. Yuri Fisyak will work on an improvement because this method uses

numerical derivations that take time & CPU. More relevant since now we don’t apply the cut on the multiplicity = large

number of tracks associations.

• Previous issues are understood as low pT D0 : work is ongoing to take advantage of these particular decay.

• Simulation : a comparison of TCFIT results with helix swimming and GEANT are in agreement In parallel of real data reproduction, we investigate some precise cuts

• Real data : Tracks with N>1 benefit from the SVT points precision : the DCA

resolution vs time is stable for these cases. Need statistic now !

32

Back up

33

. (circle center)

.(0,0).DCA

Pt_GL

Beam Pipe

SVT1,2

(first hit)

Pt @ DCA

x

DcaGeometry

Event

R- plane

34

•o1,o2 = starting point of helicesh1 and h2•Start the scan with helix h1•Search in forward direction•D1 = minimal distance

Forward direction x

x

h1h2

D2o1

o2

•o1,o2 = starting point of helices h1 and h2•Start the scan with helix h1•Search in forward direction•D2 = minimal distance•But D2 is different from D1•Should use Backward() in that case ?

h1

y

xx

h2

o1o2

D1

x

y

x

35

Signed decay length (TCFIT) vs decay length (THelix)

Increase the probability of TCFIT improves a lot, as we see a clear correlation with the decay from the helix swimming.

Probability>0.75

Pure D0 sample

36

decay length(TCFIT) vs decay length GEANT

Probability>0.1

sigmamean

sigmamean

37

Cut on probability

• result of the Breit-Wigner fit

• change the probability cut

• cut number of tracks N<200

no cuts/n~12.36

probability>0.01s/n~11.87

probability>0.2s/n~9.93

All the following plots are All the following plots are from mix Dfrom mix D00 sample sample(simulation)(simulation)

38

Invariant mass vs decay length cut

• a cut on the decay length may act like for strange particles, where we cut on the decay length to remove some background

Probability>0.01

Probability>0.2

Decay length increasing

39

s/n estimation vs multiplicity

• Next slides, study of signal/noise vs. multiplicity cut., using the (unlike-same signs) subtraction.

• In the next plots, red markers are unlike signs associations, black are same signs associations.

40

DCA resolution vs η

• For very low pT(yellow), the DCA resolution is not good for single silicon hits.• For low pT (<.6), we see some detector edges effect the dca resolution is degraded• For pT~1, we reach the SSD(+SVT) resolution uniformly in η

ssd only

ssd+svt(1)

ssd+svt(>1)

41

DCA resolution for pions

• selection of π with :•|Nσπ| < 2•Rejection of K with |NσK| < 2

•The X-axis is then 1/βPThe fit is in better agreement with the data points up to 1/βP = 3.5

42

Invariant mass (pure sample)

allK-π+

K+π-

•simulation with Starsim :D0->K-π+ ,with BR =100% •black = all pair tracks associations• red = supposed to be the signal (K-π+)• green = reflection (K+π-)

Wrong sign assignment of daughters make the invariant mass broader

σ=0.014 σ=0.093

43

(Transverse) momentum cut : pure D0 sample

•These plots show the transverse (top) momentum (bottom) for all pair tracks (left) and daughters tracks from the D0 input (right)a cut can be applied in the analysis code (pT>.5 GeV/c)

44

Cuts used in reco code (simulation)

• Slow simulator • Cuts in MuKpi :

|Zvertex| < 30 cm NoTracks<200 (800)

SiliconHits>0 ||<1.2 (SSD acceptance) dEdxTrackLength>40 cm p >.1GeV/c Dca(transverse) < .1 cm

|slength(linear)|<.15 cm (probability(tcfit)>0.01 && slength(tcfit)<.1cm)

|nK|<2, |nπ|<2 (|nK|<3, |nπ|<3 )

old/new : we based the cut on decay length with the result from TCFIT

45

Cuts used in reconstruction code (real data)

• Cuts in MuKpi : TriggerId : 20001,20003,20010 |zvertex| < 10 cm |zvertex|< 200µm NoTracks (primaries)<200 (removed)

SiliconHits>1 (we want tracks with good dca resolution) p >.3GeV/c (from plot pPion vs. pKaon in pure sample -include the plot- we

see we can apply a lower limit in the momentum of daughters) ||<1.2 (SSD acceptance) dEdxTrackLength>40 cm (http://www.star.bnl.gov/~bouchet/TCFIT/deDxTrackLength_study.ppt.htm)

Dca(transverse) < .1 cm

probability>0.01 && slength(tcfit)<.1cm |nK|<2.5, |nπ|<2.5