bigbite / sbs front-tracker...

BigBite / SBS Front-Tracker GEM

E. Cisbani INFN Rome e Italian National Institute of Health

SBS Meeting 21/July/2016 - JLab

• Workforce and activity

• Assembling

• Integration @ JLab / Mechanics

• Cosmic tests in Rome / some results

• Retina tracking

• Status at the end of June/2016

GEM / Workforce and funding

• *) Scholarship

• INFN/Funding (GEM + Silicon Detector):

• Prototyping and Production (2008-2015): ~650 keuro

• Production and Installation (2016-2017): ~50 keuro/year

• Operation and Maintainance (2018-…): ~30 keuro/year

INFN Group Researcher Tech. Role

Bari R. Perrino Gas system, beam test and analysis

Catania E. Bellini C. Sutera M. Russo

L. Re* (F. Noto)

F. Librizzi D. Sciliberto A. Grimaldi

GEM module assembling, mechanics, beam test, analysis, algorithm development

Genoa P. Musico Electronics design and test

RM/Sanità E. Cisbani (A. Del Dotto

C. Fanelli)

S. Colilli F. Giuliani

M. Lucentini F. Santavenere

(M. Gricia)

Coordination, design, test, chamber integration, analysis

Total 7 / 2.5 6 / 3

Other support (collaboration): CERN / UVa / JLab

2016 / July / 21 SBS GEM Front Tracker 2

GEM Activity 2015/2016 • Production

– Stronger GEM quality check

– 14 Module assembled, 2 rejected

– Introduced aluminized mylar foil to avoid charge-up of entrance windows

– External frame design finalized

– Second GEM chamber delivered to JLab

• Test – Cosmic test HW and analysis progress

• Gas – NI Compact RIO system implemented

• Elettronica and DAQ – Paolo talk

• Algorithms – Hits detection (attempt to move in firmware)

– Track Reconstruction


1. Quick ramp up to 450 V

2. Stay at 450 V for 3 min

3. Quick ramp up to 550 V

4. Stay at 550 V for 3 min

5. Current must stabilize “well” below 10 nA

6. Switch HV to 0

7. Repeat from 1 at least twice for each sector

Controlled Humidity < 10%

(used higher humidity to clean the

foil)

2016 / July / 21 SBS GEM Front Tracker

GEM Foil Tested 50 of 74

Approved 44

Spare 2

Rejected 4

4

By end of June/2016

5

First GEM Chamber at Jlab (15/05)

SBS Front Tracker

Aluminum profiles for mechanical support (carbon fiber not ready at that time)

Cable tray vertical

Total thickness: 14 cm (not compatible with available space for Front Tracker GEM)

6

639.44 mm

From JLab/Bogdan

Tight space constraints

along particle direction!

proposed chamber orientation:

F-F-F-B-F-B

(F=forward, B=backward)

Assuming:

• 131.6 mm chambers height

• 6.6 mm between F-F

• 13.2 mm between B-F

7

From 3cm Aluminum Frame to 2cm Carbon Fiber


Flex-Bck APV

Card

HV Divider

GEM Module Carbon Fiber Frame 2 cm

12 cm

1.5 cm

2 cm

14 cm

Aluminum Profile

30x120 mm

Al

Pro

file

(3

0x

30

mm

)

PVC bar PVC support

APV Card

Old Version Final Version

8

Second GEM Chamber at JLab (15/11) Carbon Fiber mechanical frame

Large extruded PVC Cable Tray

External HDMI cables are now 20 m long, but we intend to use 15 m to reduce cable noise

• Expected green light from JLab for procurement !

9

JLab: 2nd chamber - Details


Distance between modules < 7 mm

24x 3 m long HDMI cables (will be replaced by 2 m long

cables)

Mechanical alignment at the level of 1 mm

10

JLab: current cosmic test stand


Chamber 1

Chamber 0

Gas, Electronics, Low Voltage – connected Two scintillators (from S1) in place, now running (thanks to Mark Jones)

Bottom Plastic Scint.

Top Plastic Scint.

11

JLab: cosmic test setup / details


• 48 x 20 m long cables

• 8 MPDs (3 of them taken apart for UVa

and HU tests)

• 2 Low Voltage lines

• Ar/CO2 gas pipe (with flow regulator)

• HV ready to be connected

12

Mechanical frame design finalized

(identical to second chamber, except longer crossbeams)

Procurement of the carbon frame components underway

Cost increaded by ~60% respect to 2014 (!)

8 weeks for production (from formal order)

13

Extruded PVC cable tray

Carbon fiber rod Front-end electronics

GEM module

Support rod for cable tray

GEM chamber – final design

1824

120

1180

SBS Front Tracker

(All mm)

Expected green light

from JLab for frame

production

14

Single Chamber Gas Piping

Parker-Legris Components

IN

OUT

Expect each chamber to have a single gas flow control

due to radiation it cannot sit close to the chamber

15

Rome: Cosmic Test Setup and trigger

2 50x25 cm2 Scintillators

2 50x25 cm2 Scintillators

10x10 cm2 Scintillator

Reference 10x10 GEM

GEMs

under test

TRIGGER

AND

OR

OR

188 mm

183 mm

385 mm

SBS Front Tracker

16

M08x

M08y

M09x

M09y

M10x

M10y

Sample 0 Sample 1 Sample 2 Sample 3 Sample 4 Sample 5

Event Display

SBS Front Tracker

6*25 ns

17

Data processing

1. Common Noise Suppression

a) Mean or Median methods

2. Pedestal Subtraction

3. Hit Identification

a) Samples analysis to get time info

b) Help from Genetic Programming

4. Hits Aggregation on cluster

5. x-y Cluster Association

a) Charge and time correlation

6. Tracking

a) Clusters association (NN, Retina ?)

b) Precise Tracking (Kalman Filter)

Steps 1 and 2 already in firmware

Work in progress to have reliable

hit ID also in firmware

Not optimized yet!

GOAL: Find a simple and robust function (to be implemented in

firmware) that can discriminate real hits from background

Try: Artificial Intelligence methods (AI)

Use Neuro-Genetic Programming (Brain Project) to determine the optimal

function that approximate the experimental data (symbolic regression)

Select (unbiased) learning subsets of the data (signals and noise)

BP criterion found: Erf (q4 * q5)>0.5

qi = ADC values/(3*RMS_ped) of sample i; (25 ns step) It uses only 2 sample (q4 and q5) !

Validate on a large set of data


M. Russo, «A distributed Neuro-Genetic

Programming Tool», Swarm and Evolutionany

Computation 27 (2015) 145-155

Use 2 “robust” hit criteria that use all 6 samples information (visually checked on

large number of events)

applied to the hits that passed the ERF method (and a simple thresholding method)

ERF method recognizes the average 96% of the “real” hits

All Modules M08 M09 M10 S2

4150 V (96) 91.4 % 93.8 % 89.9 % 90.9 % 88.5 %

4200 V (102) 97.0 % 97.4 % 96.8 % 97.0 % 96.7 %

4200 V (138) 95.5 % 97.7 % 95.5 % 93.5 % 91.2 %

4250 V (143) 99.1 % 99.2 % 99.0 % 99.1 % 99.5 %

4250 V (186) 96.5 % 96.2 % 97.2 % 96.5 % 93.3 %

All Modules M08 M09 M10 S2

4150 V (96) 6.73 2.25 2.07 2.13 0.27

4200 V (102) 6.86 2.22 2.19 2.17 0.27

4200 V (138) 7.14 2.35 2.45 2.18 0.23

4250 V (143) 7.46 2.46 2.56 2.20 0.24

4250 V (186) 7.33 2.30 2.43 2.36 0.24

“True” Hits / Erf Candidates

“True” Clusters (from Erf Candidates) / Events

Method «True»/Candidates

Erf 91.2%

«Thresholding» 3 samples

81.6%

Work is in progress


20

Module 08

x

y

Charge

Correlation

Max

Charge

Correlation

Cluster

Position

#hit in

cluster

Sample

with max

#cluster

Trigger timing not optimized (max sample =4-5)

SBS Front Tracker

21

Module 09

x

y

Charge

Correlation

Max

Charge

Correlation

Cluster

Position

#hit in

cluster

Sample

with max

#cluster

SBS Front Tracker

22

Module 10

x

y

Charge

Correlation

Max

Charge

Correlation

Cluster

Position

#hit in

cluster

Sample

with max

#cluster

SBS Front Tracker

23

All modules, «first» cluster position Mod 08 Mod 09

Mod 10

SBS Front Tracker

Few channels missing in module 10, due to cut in

kapton terminals

24

Module 8 - performance over time

High treshold cut

17/Mar/2016

19/May/2016

> month of continuos

running

Time (h)

Curr

ent

(nA

)

HV=4200

Something is going on in M8

25

GEM sector issue

xray image

Conductivity of the HV distribution

line to the GEM has been tested (by

multimeter): notingh relevant found

Resistor has been re-soldered

→ cosmic test in the coming weeks

To do: single GEM foil HV

current monitor (without HV

divider)

26

Hit Tracking

SBS Front Tracker

1. Select «true» hits on two modules

2. Compute the straight line passing for the two hits

3. Project the line on the third module

4. Compute the distance of the projected point from the measured hit

Module 8 «tested»

Module 9 «tested»

Module 10 «tested»

Residual Cosmic polar angle

Run 143

HV=4200 V

27

Estimating Tracking Efficiency Assume the module can have 3 output states: • one true hit from a cosmic with probability PD

• no hit from cosmic (unefficiency) with probability PU = 1 - PD

• noisy hit (not from cosmic) with probabilty PU*PN

Assume also: • false trigger (no track passing the GEM) have probability: (1-PT)

• if a track pass one module it pass all of them

PD, PU, PN and PT determine the probability of events: • a single module has hits (independently from the others)

• two modules have hits (independenty from the others)

• all three modules have hits

• two modules define the track, hits

of third is checked in fiducial area (s)

(A = total module area)

conservative

assumption

28

Estimating Tracking Efficiency (results)

• Preliminary Minimization (use

ROOT/Minuit2 and random brute force)

• Now looks much stable (same results

using two minimization methods)

Tracking efficiency at the level of 85%

Reasonable consistent with observed event

display

Run 102:

Module Area 200000.000000 and Fiducial Area 15.707500

Total Events : 10000.000000

Combined efficiency (0,1) (0,2) (1,2): 0.383192 0.320980 0.361130

Combined efficiency (0,1,2): 0.210755

Type 0 / idx 0 : 0.583600

Type 0 / idx 1 : 0.656600

Type 0 / idx 2 : 0.550000

Mod 0: Conditional Track Efficiency: 0.142700

Type 1 / idx 0 : 0.429700

Type 1 / idx 1 : 0.360500

Type 1 / idx 2 : 0.420300


Type 2 / idx 0 : 0.291600


FCN=0.120771 FROM MIGRAD STATUS=FAILED 293 CALLS 294 TOTAL

EDM=0.0163612 STRATEGY= 1 ERR MATRIX NOT POS-DEF

EXT PARAMETER APPROXIMATE STEP FIRST

NO. NAME VALUE ERROR SIZE DERIVATIVE

1 pT 9.77427e-01 5.07038e-04 0.00000e+00 -1.90898e-01

2 pD0 7.00417e-01 4.60406e-02 -0.00000e+00 3.71340e-02

3 pD1 8.87866e-01 1.92789e-03 -0.00000e+00 2.55492e-01

4 pD2 8.08472e-01 6.04075e-03 -0.00000e+00 7.57888e-02

Minuit Min: 0.977 0.700 0.888 0.808 -> 0.121

Rand Min: 0.977 0.753 0.859 0.779 -> 0.095 (max=49.49)

Run 143:

Module Area 200000.000000 and Fiducial Area 15.707500

Total Events : 10000.000000

Combined efficiency (0,1) (0,2) (1,2): 0.621229 0.578736 0.606703

Combined efficiency (0,1,2): 0.467040

Type 0 / idx 0 : 0.769800

Type 0 / idx 1 : 0.807000

Type 0 / idx 2 : 0.751800


Type 1 / idx 0 : 0.684200

Type 1 / idx 1 : 0.620900

Type 1 / idx 2 : 0.679300


Type 2 / idx 0 : 0.577400


FCN=0.0797257 FROM HESSE STATUS=OK 53 CALLS 603 TOTAL

EDM=8.87514e-05 STRATEGY= 1 ERROR MATRIX ACCURATE

EXT PARAMETER STEP FIRST

NO. NAME VALUE ERROR SIZE DERIVATIVE

1 pT 8.69444e-01 2.14062e-02 1.29814e-03 -7.92343e-02

2 pD0 8.02158e-01 1.97294e-02 6.93234e-04 -1.52240e-01

3 pD1 9.25127e-01 1.44478e-02 7.41597e-04 -4.85990e-02

4 pD2 8.17338e-01 1.65073e-02 6.50453e-04 -1.39510e-01

Minuit Min: 0.869 0.802 0.925 0.817 -> 0.0797

Rand Min: 0.870 0.800 0.929 0.814 -> 0.081 (max=9.39)

Track Reconstruction • Multistep approach:

– Hit association: Neural Network (need smart energy function)

– Precise tracking: Kalman filter (rather consolidated approach)

• (Slow) work in progress: – Consolidate NN

– Implementation of artificial RETINA approach (for hit association)


Alessio Del Dotto Cristiano Fanelli

29

30

Retina Tracking – a simple case ● The original idea is in (L. Ristori,

NIM A, 452 (2000) 425)

● Reconstruction of tracks in absence

of magnetic field using the

decoupled x-y coordinates in the

detector plane

● Considering x coordinate

● Retina is an adaptive algorithm,

and we need to fix the “receptor”

mapping the (m,q) parameters

space (each point in the plot is the

centre of a parameter space

discrete cell)

To go to a more realistic case, a smart mapping of the detector “receptor space”

is the crucial point!


31

Working principle Let us consider all the hits in a given detector plane k, (zn,xn)k the

response of the cellular unit (mi,qj) is

Where xrij

is an hypothetical hit in the plane r on the basis of the (mi,qj) space

segmentation.

The parameter σ in the denominator gives the size of the uncertainty on the

hits and it is strictly related to the choice of the parameter space segmentation.

(In SBS: if r!=k then sijkr>>s)

The maxima of Rij correspond to potential tracks


32

Receptors above threshold (i.e. >4)

are considered “on”

Full receptors responce for

the case of 3 tracks

<m> and <q> can be reconstructed from the above

threshold receptors as a weighted mean

Retina: example of results Physical space


33

Receptors above threshold (i.e. >4) are considered “on”

Full receptors responce for

the case of 2 tracks & ghost hits

<m> and <q> can be reconstructed from the above

threshold receptors as a weighted mean

Good tracks

Retina: example of results Physical space


Retina for track association

• Tracks finding → search maxima in parameter space

• Relevant aspects:

– Define the segmentation of the parameter space in a smart way

– Choose a robust maxima search algorithm

• Parallelizzation (implemented on GPU), though essentially a global method

• Can be extended to curved trajectories (e.g. magnetic field)



Production/Test Summary Produced or Assembled

Tested or under

test

NOT Accepted

Comment

GEM foils 74 (-6 ?) 50 2+4 2

Readout+Honeycomb 22 + 20 16 2 bad assembling, 1 probably still usable

GEM Module 14 / 18 9 2 *Open issue: 2-3 modules delivered to JLab may be damaged (by visual inspection); HV sectors in cosmic test !

External Carbon Frame

1 / 6 1 Waiting production (expecting feedback from JLab)

Front End Electronics 345 / 345 200 10 * minor bugs

VME Modules 28 / 28 16 3 minor bugs

Backplane (rigid) 80 / 80 40 6

Backplane flex-rigid 36 10 26 new just arrived

Patch Panel (adapters) 50 / 50 30 2

35

Activity 2016 2017

• Complete module production (4 for the end of 2016) + spares

(3-4 first half of 2017)

• Try to understand «HV sector issue»

• Continue test and characterization

• Integrate all chambers (2 in 2016 + 2 in 2017)

• Installation at JLab, cosmic and parassitic tests

• Hits detection (in firmware?) and track reconstruction algorithm


Module M0-M4


M0

M1

M3

M4

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