2007-1-6 1

Ideas of BigBite Tracking Monte-Carlo

Xin QianDuke, TUNLMEP Group

2007-1-6 2

Outline

• BigBite Setup During TransversityExperiment.

• BigBite Background Issue.• My understanding of the BigBite Tracking

for Transversity Experiment. • Why do we need a BigBite Tracking

Monte-Carlo?• Ideas of BigBite Tracking Monte-Carlo.

2007-1-6 3

BigBite Setup During Transversity

• Three full wire chambers with 18 planes in total (6 planes each chamber).

• Gas Cerenkov, pre-shower showercounter do the PID.

• Scintillator give the timing information.

Wire chamber

Gas Cerenkov

Shower system

Scintillator

Magnetic field shielding

OpticsSlot-slit

2007-1-6 4

BigBite Background• BigBite high rates

background is a big problem to the wire chamber: – low tracking efficiency, – high dark current, – short chamber life time, – etc…

• High rate background is causing by – secondary particles, – low energy photon, – etc.

2007-1-6 5

BigBite Background• Significant amount of

background is coming from the downstream beam pipe.

• A thick shielding on the side will help reducing background.

• Some shielding material inside BigBite magnet will also help.

2007-1-6 6

From Seamus Riordan

2007-1-6 7

BigBite Background estimation• GEANT3 with modified physics.• Modified Physics:

– Use exclusive event generator: photon-nuclear fragmentation package DINREG in GEANT substitutes old ‘PFIS’ mechanism.

– Electron-nuclear interactions are modeled using equivalent photon representation of an electron.

• Geometry: target, BigBite magnet, detector, beam pipe, beam dump and Hall.

• Code is from Pavel Degtiarenko.

2007-1-6 8

BigBite Background estimation• Rate estimation has been confirmed by

comparison with: – TRAN test run, – N20 test run, – SRC data, – bare wire chamber test run – and GEN data.

• The discrepancy is less than a factor of 2. • For wire chamber, the discrepancy is less than

20-30%.

2007-1-6 9

Comparison between GEN data and TRANSVERSITY

BD1(MHz) BD2(MHz) BD3(MHz) currentGEN: 19.2 22.0 19.3 9 uATRAN: 10.6 23.0 23.0 10 uA

Condition: 6 GeV, 30 degree, with thick shielding wall.Cut 1 keV is a loose cut.

• More shielding in front (collimator design, shield window etc.) can further decrease the background.

• Background rate limitation:– Not on the dark current.– Limitation is on the confidence of the tracking algorithim, – also related to the low tracking efficiency.

2007-1-6 10

2 chambers vs 3 chambers?• With 15 uA beam, background rate ~ 35 MHz

– 0.25MHz/wire for the first chamber, 0.18MHz/wire for the third chamber.

– The probability of firing one wire during 200 ns ~ 4.9% and 3.4%.

– Assuming 5/6 planes firing, the probability of having one faked point

• in the first chamber ~ 25.5%.• In the third chamber ~ 8.5%.

(1 exp( ))P R tδ= − − i

5 5 6 66 1 1 6 1( (1 ) )totP N C P P C P= − +i i i

Here P1 = 5% (for chamber 1)N ~ 140^2*8 for first chamberN represent all the possible regions.Here 8 is due to the U1,V1,X1 plane.

2007-1-6 11

– Assuming shower can reduce 1/2 phase space, the probability of having one track

• for two chamber ~ 0.54%; contamination > 3% faked track.

number of planes contain hits passing shower cut0 2 4 6 8 10 12 14 16

nu

mb

er o

f ev

ents

0

50

100

150

200

250

9uA, 3He

hits only

13 minimum planes in reconstructing tracks

hits and tracks

9uA, 3He

2007-1-6 12

2 chamber vs 3 chamber?• If we have another chamber, we can reduce the faked

track by – 0.0002% for a full chamber– 0.7% for a 3 planes chamber.– leading to negligible effect in the completely random situation.

• If there is some correlation between hits on different planes or even different chambers:– Hard to quantify.– Assuming a factor of 2 increasing in the probability.

• 6 planes on second chamber: ~ 0.13% contamination.• 3 planes on second chamber: ~ 9% contamination.

– Full middle chamber can significantly reduce the probability of faked track.

– A Monte-Carlo may give a more accurate estimation.

2007-1-6 13

What else for 3 chambers?

Wire Number for Plane u10 2 4 6 8 10 12 14

Eff

icie

ncy

0

0.2

0.4

0.6

0.8

1

1.2

0.942 + 0.002 - 0.002

Plane u1

Wire Number for Plane u20 2 4 6 8 10 12 14

Eff

icie

ncy

0

0.2

0.4

0.6

0.8

1

1.2

0.964 + 0.002 - 0.002

Plane u2

Wire Number for Plane u30 2 4 6 8 10 12 14 16 18 20 22

Eff

icie

ncy

0

0.2

0.4

0.6

0.8

1

1.2

0.935 + 0.002 - 0.002

Plane u3

Wire Number for Plane u40 2 4 6 8 10 12 14 16 18 20 22

Eff

icie

ncy

0

0.2

0.4

0.6

0.8

1

1.2

0.987 + 0.002 - 0.002

Plane u4

Wire Number for Plane u50 2 4 6 8 10 12 14 16 18 20 22

Eff

icie

ncy

0

0.2

0.4

0.6

0.8

1

1.2

0.981 + 0.002 - 0.002

Plane u5

Wire Number for Plane x10 2 4 6 8 10 12 14

Eff

icie

ncy

0

0.2

0.4

0.6

0.8

1

1.2

0.954 + 0.002 - 0.002

Plane x1

Wire Number for Plane x20 2 4 6 8 10 12 14

Eff

icie

ncy

0

0.2

0.4

0.6

0.8

1

1.2

0.988 + 0.002 - 0.002

Plane x2

Wire Number for Plane x30 2 4 6 8 10 12 14 16 18 20 22

Eff

icie

ncy

0

0.2

0.4

0.6

0.8

1

1.2

0.952 + 0.002 - 0.002

Plane x3

Wire Number for Plane x40 2 4 6 8 10 12 14 16 18 20 22

Eff

icie

ncy

0

0.2

0.4

0.6

0.8

1

1.2

0.993 + 0.002 - 0.002

Plane x4

Wire Number for Plane x50 2 4 6 8 10 12 14 16 18 20 22

Eff

icie

ncy

0

0.2

0.4

0.6

0.8

1

1.2

0.983 + 0.002 - 0.002

Plane x5

Wire Number for Plane v10 2 4 6 8 10 12 14

Eff

icie

ncy

0

0.2

0.4

0.6

0.8

1

1.2

0.968 + 0.002 - 0.002

Plane v1

Wire Number for Plane v20 2 4 6 8 10 12 14

Eff

icie

ncy

0

0.2

0.4

0.6

0.8

1

1.2

0.974 + 0.002 - 0.002

Plane v2

Wire Number for Plane v30 2 4 6 8 10 12 14 16 18 20 22

Eff

icie

ncy

0

0.2

0.4

0.6

0.8

1

1.2

0.943 + 0.002 - 0.002

Plane v3

Wire Number for Plane v40 2 4 6 8 10 12 14 16 18 20 22

Eff

icie

ncy

0

0.2

0.4

0.6

0.8

1

1.2

0.980 + 0.002 - 0.002

Plane v4

Wire Number for Plane v50 2 4 6 8 10 12 14 16 18 20 22

Eff

icie

ncy

0

0.2

0.4

0.6

0.8

1

1.2

0.979 + 0.002 - 0.002

Plane v5

2007-1-6 14

What else for 3 chamber?

• Improvement on naïve tracking efficiency:– Assuming an average 95% hitting efficiency,

the naïve tracking efficiency (neglect software part) is:

• 96.4 % for 13 out of 15 planes.• 98.9 % for 15 out of 18 planes.

– Middle chamber will be able to fix a point by itself.

• Position of middle chamber– Monte Carlo will help

2007-1-6 15

BigBite tracking• The BigBite tracking code made by

Seamus Riordan is quite successful in treating GEN data.– Brute force method which goes through all the

possible combination within the shower-counter cut.

– The least Chi2 method is used to select the real track.

– The advantage: • in principle will find all the real tracks.

– The disadvantage:• slow in the high rates situation.

2007-1-6 16

BigBite tracking• How slow? 10 Hz level

– GEN: • Average 3 hits per plane in 200 ns window. (15 planes)

– TRAN worst scenario:• Average 7 hits per plane in 200 ns window. (18 planes)

– The ratio is (1+7/2)^18/(1+3/10)^15 ~ 1E10.• In TRAN case, the trigger rates is lower (half Hz level), which

can help reducing the computing time.• Faked contamination is ~ 0.13%. Most combination are not

useful.• Tree searching can reduce O(n) to O(log(n)).

– In this case, a much faster tracking algorithm is possible and necessary for transversity experiment.

2007-1-6 17

Why do we need a BigBiteTracking Monte-Carlo

• Tracking Monte-Carlo can help in studying the software tracking efficiencies:

– During GEN, the tracking efficiency can be studied in hydrogen elastic run by using Neutron arm information.

– Hard to study tracking efficiency in production run– Equally hard to study during TRANSVERSITY production run.

• Tracking Monte-Carlo can help evaluating/improving new tracking algorithm.– Balancing speed and tracking efficiencies?

• Tracking Monte-Carlo can help in fixing the maxima luminosity and the number of planes used in the tracking.

• Understanding Optics?

2007-1-6 18

Some ideas on tracking Monte-Carlo

• Tracking Monte-Carlo can be made based on Comgeant (From Eugene Chudakov)– GEANT3 with updated BigBite detector geometry

– Digitization already exists in the comgeant• Multi-wire proportional chamber• Shower counter

– Need to make a code to convert output of Comgeant into the format which can be read by analyzer: ADC and TDC value. (VDCsim can be used as a reference code)

– In this code, we also need to add background as well• Merging method for wire chamber TDC and shower counter ADC in case of

pile up and adding background.• Modified digitization inside comgeant, non-linear drift time etc.

2007-1-6 19

Acknowledgement

• Eugene Chudakov• Ole Hanse• Robert Feuerbach, Seamus Riordan and

Brandon Craver.• Xiaodong Jiang and Kalyan Allada

2007-1-6 20

• BACK UP slides

2007-1-6 21

Plan• Check the geometry:

– The geometry need to be consistent between comgeant and analyzer.

• Comgeant side:– Be familiar with the running and decoding– Adding background– Develop merging method for additional background.

• Analyzer side: – Create a code which can convert comgeant output

into raw TDC and ADC values which can then be read into Analyzer.

– Be familiar with Analyzer (BigBite).• Expected to be finished in a couple months.

2007-1-6 22

Position of the middle chamber?• Middle chamber can be placed in front of Gas

Cerenkov or on the back of Gas Cerenkov. – Chamber on the back will have less rate per wire

which lead to less probability to have a faked track.– Chamber in the front will have more rate per wire, but

it can help to reduce the multiplicity of the hitting point on the first chamber.

– Naïve study shows the chamber in the front can help more.

– Again, it is hard to quantify without a Monte-Carlo simulation. It is almost impossible to gain information from GEN data, since the middle chamber is fixed in the middle.