summary of the emulsion reconstruction wg

Summary of the Emulsion Reconstruction WG

P. Migliozzi

S. Aoki, L. Arrabito, A. Badertscher, M. Besnier, C. Bozza, E. Carrara, M. Cozzi, G. De Lellis, M. De Serio,

F. Di Capua, L. S. Esposito, T. Fukuda, M. Guler, F. Juget, K. Kodama, M. Komatsu, J. Knuesel, I. Kreslo, I.

Laktineh, A. Longhin, G. Lutter, K. Mannai, A. Marotta, F. Meisel, P. Migliozzi, A. Pastore, L. Patrizii,

C. Pistillo, L. Scotto Lavina, G. Sirri, T. Strauss, V. Tioukov, A. Zghiche

• Tracking in an ECC (M. Besnier, C. Bozza, T. Fukuda, K. Kodama, I. Kreslo, Y. Nonoyama, C. Pistillo, C. Sirignano, V. Tioukov, Zghiche)Vertex location as a function of the event classification (L. Arrabito, C. Bozza, M. De Serio, I. Kreslo, A. Marotta, Y. Nonoyama, C. Pistillo, C. Sirignano)Volume scan, vertex reconstruction and decay selection based on topological criteria (M. Besnier, C. Bozza, F. Di Capua, T. Fukuda, K. Kodama, M. Komatsu, I. Kreslo, A. Marotta, Y. Nonoyama, A. Pastore, C. Pistillo, L. Scotto Lavina, C. Sirignano, V. Tioukov, A. Zghiche)

• Brick to brick connection (E. Carrara, M. Komatsu, A. Longhin);Momentum measurement by MCS criteria (M. Besnier, C. Bozza, M. Komatsu, C. Sirignano, A. Zghiche)e/pi separation and energy measurement (S. Aoki, F. Juget, F. Meisel);p/pi and pi/mu separation (S. Aoki, T. Fukuda, I. Kreslo, I. Laktineh, K. Mannai, C. Pistillo);

• Post-scanning 1mu/0mu classification (Y. Nonoyama);• Kinematical decay selection criteria (C. Bozza, A. Marotta, Y.

Nonoyama, C. Sirignano)

List of activities

Now available on the wiki page)

Brick finding

Trigger

Vertex location

Decay search“long” or “short”

decays

decay mode

Kinematics

events

Classifyas / e

yes

no

Electronic detectors

Emulsions

Emulsions

Electronic detectors

eat 1ry vtx ?

Vertex location

Preliminary results for the the -> DIS and -> QE channels

-> DIS

LONG trigger in emulsione = 95%

conferma del trigger = 99%

scanback = 96%

identificazione topologia = 94% idLONG = 92%

idSHORT-LIKE = 8%

SHORT trigger in emulsione = 93%


scanback = 91%

identificazione topologia = 98%

-> QE

LONG trigger in emulsione = 84%

conferma del trigger = 99.9%

scanback = 97.7%

identificazione topologia = 95.6% idLONG = 83%

idSHORT-LIKE = 17%

SHORT trigger in emulsione = 82%


scanback = 62%

identificazione topologia = 98.9%

A proposal for 0 primary vertex location

Cristiano BozzaSalerno Emulsion GroupPhys. Coord. May 2007

Types of NC-like events

X

h

e-

X

h h

h

e-

production, decay to h

production, decay to e(shower likely)

NC showerless

NC with shower

1)

2)

3)

4)

Main problems of 0-

h

e-

h stop in brick

1) TT prediction cannot define a precise slope/position pair reduced filtering function of CS

2) Many tracks can be found in CS (mostly type 2 and 4) scanback takes time with many paths

3) Scanback paths are likely to lead to 2ry vertices; sizable probabilityof not finding 1ry vertex by direct scanback

However, what we can do witha brick is Scanback + Volume ScanSolution should be found there

Further considerations

Scanning load cannot be increased too much

Lead ECC is a relatively dense material – EM 2ry interactions should be near to the 1ry (X0=0.56 cm 4 cells, 9/7X0=0.72 cm 6 cells)

Track multiplicity is very high in showers, but low momentum e+/e-

are strongly scattered and travel a short length

Scanback is efficient in finding interaction points quickly

Strategy – Step 1

CS Scanning

Search for base-track pairs on CS (no 3-out-of-4)

SCS = slope differencebetween base tracksSCS < 0.015

Rank tracks with SCS and select the first NpCS = 300

Goal of step 1: discard low momentum tracks as soon as possible

Strategy – Step 2

CS – Target connection

Project CS pairs to first two plates of target using most upstream pos/slope

ACST = area to be searched500500m2

SCST = 0.040 (CS-brickmisalignments possible)

Pick up all candidates for each track

Goal of step 2: minimize track losses (scattering should be small)

Strategy – Step 3

Scanback

Follow scanback paths with the same parameters as for in CC

Many scanback paths with low momentumare lost very soon (hard SB parameters)SSB = 0.020 PSB = 80 mMax missing plates NmpSB = 5 plates

Goal of step 3: follow tracks with high momentum as upstreamas possible, and discard low momentum tracks quickly

Strategy – Step 4

TotalScan/NetScan

Choose the NV = 10 paths stopped most upstream (except passing-through paths)

TotalScan around most upstreamstopping pointsUse latest direction to search for 1ry vertex – skewed volumesVolume width grows upstream (AS = slope acceptance 0.4)Correlation between 1ry vertexposition and products of 2ry interactions

Goal of step 4: limit complexity of scanning procedure despite of a small increase in scanning load

Nu

Nd

Catch conversions and charm decays: Nu = 10

Scanning load and data size

Step 1: 240 cm2×2 sides = 480 cm2

Scanning time for both CS = 24 h (at 20 cm2/h/side) (lower if prediction scan is used)Data size = 60 MB for 105 tracks in each CS

Step 2: 0.75 cm2×2 sides = 1.5 cm2

Scanning time = 4min30s (at 20 cm2/h/side) Data size = negligible

Step 3: 300 predictions×57 platesScanning time = 5h42min (at 1.2s/track) Data size < 5 GB

Step 4: 115 cm2 ×2 sidesScanning time = 11h30min (at 20 cm2/h/side) Data size < 5 GB

Total: 41h/brick, < 10 GB/brick

Conclusions

The procedure should be able to fulfill several conflicting goals

Efficiency should be estimated

If 1ry vertex is not found, event interpretation is affected estimate resulting background

Scanning load and data size acceptable

Many parameters can be optimized work for MC experts!

Comments

• The vertex location for events with a muon in the final state works very well (despite of the low base track efficiency, the usage of micro-tracks helps)

• The situation for 0mu-like events is more difficult. More efforts are needed if we want to be ready by September

• We should review this item by mid of July

Vertex Reconstruction

L. Arrabito, M. Besnier, C. Bozza, A. Pastore, L. Scotto

Lavina, V. Tioukov

Summary

Goal :

- Analysis of vertex reconstruction of CC neutrino interactions

Data set:

- Monte Carlo simulation of 3000 CC events generated by OpRoot-ORFEOv7

Properties: - Monte Carlo data (TreeMSE) with smearing and efficiency correction ( eff = 0.944 – 0.216 * – 0.767 * 2 +1.856 * 3

Analysis:

- Tracking and Vertexing performed by Fedra (Similar results have been obtained by using the AlfaOmega framework)

Interactions inside the OPERA brick

Z (cm)

Y ( cm )

X (

cm)

energy spectrum of interacting

- 3000 CC events

- CNGS energy spectrum

Analysed data sample

CC interaction

Neutrino interaction vertex is at the center of the fiducial volume

P0 +1 +2 +3 +4 +5-1-2-3-4-5

muon

Volume size : 25 mm2 * 11 plates

P0 = first emulsion sheet containing the neutrino-associated ( X0, Y0 ) = position at ZP0

(X0,Y0)

Pb plate

Emuls. film

Fiducial volume

MC truth vs MC reconstructed vertices

MC truthprimary vertex

primary tracks

secondary tracks

MC recreconstructed

primary vertex

reconstructedprimary tracks

secondary track wrongly attached

to the vertex

x = 0.34 m y = 0.37 m

z = 2.77 m

MC truth vs MC reconstructed vertices: vertex position

1) Study of CC

Nf<1%

z=8.9µmxy= 1.1µm

MC truth

MC rec

p

p

+

+

-

-

e+e-

e+e-

MC truth vs MC reconstructed vertices: interaction products

hadrons

hadrons e+,e-

e+,e-

secondary tracks wrongly attached to the neutrino vertex

tracks really belonging to the neutrino vertex

dz < 1300 m 97 % signal selected

dz < 1300 m 23 % of “wrong” tracks survive

MC truth vs MC reconstructed vertices: interaction products

Generated interactions

3000

TrackReconstructi

on (n primary tracks)

n = 064

(2.2 ± 0.3)%

n = 1583

(19.5 ± 0.7)%

n 22353

(78.4 ± 0.8)%

Multi-prong vertex successfully

reconstructed

2541(86.5 ± 0.6)%

Vertex detection efficiency

Purity (all tracks attached to the vertex are primary)> 99 %

(tracking) ~ 100% for P>1GeV, drastically decreases below 1 GeV

(vertexing) ~ 95% for P>2GeV, drastically decreases below 1 GeV

50% of generated tracks with P<1GeV large angles Low reconstructed

multiplicity

Vertex detection efficiency: dependence on momentum

Overall summary (1/4)

The data/MC comparison on 8 GeV pions shows that data behavior is compatible with MC expectations, apart IP distribution, where a strong discrepancy is present at small values.

The IP distribution discrepancy must be understood. The plate misalignment, together with the inefficiency and the track smearing already simulated, could (at least partially) explain it. Investigations are in progress.

So far, the data/MC comparison on pions is used to make a systematic comparison between data and our MC.To predict the exact IP distribution found in data we need to simulate all the effects:- tracking inefficiency;- track parameters smearing;- plate misalignment;- cosmics and uncorrelated background.

Summary of present activitieson vertex reconstruction and decay search

Studies on CC interactions show that:the tracking efficiency is ~100% for P > 1GeV, drastically decreases below 1 GeV;the vertexing efficiency is ~95% for P > 2GeV, drastically decreases below 1 GeV

Studies on CC () and CC (3h) events show that:Several selection categories are populated by events with low momentum particles, in particular the momentum of particles from decay

All these simulations don’t take into account the effects of electronic reconstruction and neutrino location on the neutrino energy spectrum. Concerning events, they are roughly using the CNGS spectrum without taking into account the energy dependence of oscillations.


The neutrino oscillation effect is very easy to reproduce.The electronic reconstruction and neutrino location effects have been parametrized in function of neutrino energy


Neutrino energy spectrum

CNGSinteracting

CNGSwith m2=2.5x10-3

Interacting

CNGSafter electronicreconstruction



Studies on multiple vertices events like CC (3h) and charmed events show that low efficiencies and purities occur in the reconstruction and correct recognition of vertices while reconstructing 2 vertex in the same fiducial volume.

The reason is the confusion between track associations when the primary and the secondary vertex are too near each other.

Such effect is amplified where tracks have low momentum and high angles and by the presence of fake vertices (wrong associations, interactions, e-pairs,...). A study for the e-pair rejection is shown.

Pair Based Vertexing algorithms implemented in FEDRA cannot be used for the topologies recognition as they are. The pairs association should be studied according to the analysis peculiarities.Global Vertexing method could be more effective and its effectiveness is under study.The study of the microtracks near the vertices could play an important role.


Comments• The vertex reconstruction is well under

control for νμ events– There are different algorithms with similar

performance. We are in the process to select the “best” algorithm

• The decay search algorithms have to be tuned. In particular, it was shown that– The hunting for short decays (decays in lead) has

to be optimized– The search for multi-prong decays is more difficult

than single-prong. An approach on the so called “Global vertexing” is being tried

• The usage of micro-tracks is mandatory

Momentum measurement by MCS

M. Besnier

Perfect MC linearity, shift for 4 GeV data (250MeV offset)

The MC indicates that it is possible to measure momentum until 8GeV with a resolution of

26%.

MC/data studyData fome from TBàCERN in 2002-04

Resolution update after fit range studies

independently determined!

Large angle results 3 effects appear at large angles ( >0.1rad )

1) Crossed Lead thickness more important

0.1

0.2

0.3

0.4

0.5

0.6

MC 4GeV pions at different 3D angle :

How to determine correctly with OPERA track configuration ?

-PMS at 0rad is now implemented in FEDRA with a s set to 1.8mrad. The Z correction with slope is also taken into account.

But no dependance with slope => wrong momentum estimation at large angles.

-First idea of using passing-through cosmic tracks to evaluate the has to be reconsidered because of wide angular and momentum dispersions.

-A way to get the is to parameterise its value with data and update it often.

Pgen (GeV) for cosmic muons with x/y < 0.4rad

x (rad) for cosmic muons

Alberto’s cosmics simulation

Conclusion :

•Some updates on momentum resolutions at 0rad : fitting range does not exceed 14 plates.

• free in the calculation is a wrong way to evaluate the momentum

• angular dependance (under studies) :

-should be parametrised in X and Y directions separately

-or should be avoided by changing coordinates frame

A draft discussing the results related to the first 2 points is in preparation

41

OPERAAnalysis status in Neuchatel

Frank Meisel, Frederic Juget, Guillaume Lutter

01.06.2007

Université de Neuchâtel

42

Status in Neuchatel

Three major projects on emulsion reconstruction (besides scanning):

Developing and integration of an advanced shower reconstruction algorithm/library into FEDRA

Testing different methods of shower reconstruction

Continue/Improve the energy measurement of an electromagnetic shower

43

libShower

First version has been adopted by Frederic, can be used

still options for improving / modifing gives reconstructed shower output file user has to decide which showercandidates to

put in... In the near future me (FWM) will provide

idea/implementation of a shower reco using maybe tracks or more sophisticated

(up to know we have to know the initiating basetrack)

44

Testing different methods shower reconstruction

Using different parametersets to find best set for efficency / purity of a shower with a induced (microscope) bg.

slightly modified algorithm (going downstream instead of upstream)

ConeTube, Neuchatel scanned empty (peanut) Brick for BG

have to scan over 250Mio. parametersets->taking long time.... still running......(Submit on any cluster machine prefered)

taken then best paramters in ShowerReco and for energymeasurement.

For example:

Electron energy

and BG contamination

45

Continue/Improve the energy measurement of an electromagnetic shower

e/pi_Algorithm and variables for e/pi separation taken over:

Number of Basetracks, dR, dTHeta distributions (mean, rms) Longitutinal profile (number of BT per each plate (11...56 sheets)

ANN Structure InputNeurons: 5+#LongProfile => 16...61 variables HiddenLayer1,2: n+1, n (n=InputNeuron) OutputNeuron, 50 TrainingsEpochs on the cont. sample (0.5..6GeV,

0.5..10GeV) 35kEvents

Energy correction has to be done on the output Linear fit function: E_(measured) -> E_(true) Run again with: E_(measured) -> E_(corrected)

Plots/Results for the first ParameterSet:

46

ANN Outputs

Before Linear Energy

Correction

(Trained on

0.5..10GeV,

20Sheets)

After Linear Energy Correction

47

Before Linear Energy Correction After Linear Energy Correction

Shower Resolution can be improved (now ...~50%/Sqrt(E))

20 sheets

48

Summary

Neuchatel is continuing on scanning and simulation:

energy measurement slight improvements in energy resolution: but to early to have

complete datasets insert into shower package also...

Shower Reconstruction (focused on e for now) slight improvements in efficency, purity: but to early to have

complete datasets

developing convenient and useful shower algos and their insertion in fedra

still ongoing....

//separationseparation

Results of Perrine Royole (IPNL)dE/dx (data)

Using only the dE/dX

Multiple scattering

Multiple scattering (simulation)Multiple scattering (simulation)

Multiple scattering

dE/dx

Muon

Pion

Simulation

Multiple scattering (data)

Volume_grains (data) N_ grains (data)

et et separation (data)separation (data)

)3.2_()25.6( 2

grainsNbVolume

Preliminary

// separation (data)separation (data)

% misidentified pions

% muons identification efficiency

Preliminary

Comments

The particle identification in a brick (electron, pion, muon, proton) as well as the momentum/energy measurement is well under control

New test-beams are very important to fine tune the algorithms (see Next talk on TB activities)

Tracking in an ECCTracking in an ECC (M. Besnier, C. Bozza, T. Fukuda, K. Kodama, I. Kreslo, (M. Besnier, C. Bozza, T. Fukuda, K. Kodama, I. Kreslo, Y. Nonoyama, C. Pistillo, C. Sirignano, V. Tioukov, Zghiche)Y. Nonoyama, C. Pistillo, C. Sirignano, V. Tioukov, Zghiche)Vertex location as a function of the event classificationVertex location as a function of the event classification (L. Arrabito, C. Bozza, M. (L. Arrabito, C. Bozza, M. De Serio, I. Kreslo, A. Marotta, Y. Nonoyama, C. Pistillo, C. Sirignano)De Serio, I. Kreslo, A. Marotta, Y. Nonoyama, C. Pistillo, C. Sirignano)Volume scan, vertex reconstruction and decay selection based on topological Volume scan, vertex reconstruction and decay selection based on topological criteriacriteria (M. Besnier, C. Bozza, F. Di Capua, T. Fukuda, K. Kodama, M. Komatsu, (M. Besnier, C. Bozza, F. Di Capua, T. Fukuda, K. Kodama, M. Komatsu, I. Kreslo, A. Marotta, Y. Nonoyama, A. Pastore, C. Pistillo, L. Scotto Lavina, C. I. Kreslo, A. Marotta, Y. Nonoyama, A. Pastore, C. Pistillo, L. Scotto Lavina, C. Sirignano, V. Tioukov, A. Zghiche)Sirignano, V. Tioukov, A. Zghiche)

Brick to brick connectionBrick to brick connection (E. Carrara, M. Komatsu, A. Longhin)(E. Carrara, M. Komatsu, A. Longhin)Momentum measurement by MCS criteriaMomentum measurement by MCS criteria (M. Besnier, C. Bozza, M. Komatsu, (M. Besnier, C. Bozza, M. Komatsu, C. Sirignano, A. Zghiche)C. Sirignano, A. Zghiche)e/pi separation and energy measuremente/pi separation and energy measurement (S. Aoki, F. Juget, F. Meisel)(S. Aoki, F. Juget, F. Meisel)p/pi and pi/mu separationp/pi and pi/mu separation (S. Aoki, T. Fukuda, I. Kreslo, I. Laktineh, K. Mannai, (S. Aoki, T. Fukuda, I. Kreslo, I. Laktineh, K. Mannai, C. Pistillo)C. Pistillo)

Post-scanning 1mu/0mu classificationPost-scanning 1mu/0mu classification (Y. Nonoyama)(Y. Nonoyama) Kinematical decay selection criteriaKinematical decay selection criteria (C. Bozza, A. Marotta, Y. Nonoyama, C. (C. Bozza, A. Marotta, Y. Nonoyama, C.

Sirignano)Sirignano)

summary of the emulsion reconstruction wg

Documents

eidentificazione topologia

vertex reconstruction

low momentum e e

ry interactions

mcs criteria

topological criteria

cs scanningsearch

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