Particle incident angle study with Mimosa 17
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Transcript of Particle incident angle study with Mimosa 17
Particle incident angle study with Mimosa 17
C.Dritsa, J.Baudot
Outline• Motivation• Digitiser• Analysis• Summary
11th CBM collaboration meeting GSI Darmstadt
Motivation
Open charm feasibility studies are of major importance for CBMThe MVD is the key detector for open charm measurements.
Background & Signal Generation
Transport
(GEANT)
Simulate detector’s response
For MVD:gaussian smearing
The actual model using gaussian smearing is not adapted for studying event pile-up and delta electrons.
Can this model be improved ?
The implementation of a more realistic MAPS response ( digitisation model ) will allow us studying the impact of the above points especially on the open charm reconstruction. This work is under progress at IPHC, Strasbourg.
Geometry (thickness, stations’ position)
Simplistic illustration of the digitisation model
Digitisation model for non depleted detector (MAPS detector):
1. Particle trajectory divided in segments inside the sensitive volume.2. Energy deposited in each segment is translated into charge.3. Charge spread in the sensitive volume within a defined cone.
No Electric Field:
Electrons are diffusing sensitive volume
θ
Advantage of digitiser: possibility to study particles with inclined tracks.Need to adapt the model’s parameters in order to reproduce experimental data.
Beam Test
•Beam test performed in November 2007 at CERN with a 120 GeV pion beam.
•The chip under test was a MIMOSA 17 :30 μm pitch - 14μm epi
MIMOSA 17
MAPS response to tracks with large incident angle was not studied in detail yet.
• The two external planes (reference planes) are used for track reconstruction.• The middle plane is the Detector Under Test (DUT): the tracks extrapolated in the DUT are matched with the hit located closest to the reconstructed track position.• Measurements were taken for several angles:• θ: 0°, 15°, 30°, 45°, 60°, 75° and 80°
Analysis steps
Top view of the setup
Reference plane:MIMOSA 17
Reference plane:MIMOSA 17
DUT
θ: 080!
Charge collected
in each pixel
PitchSize
tN pix
tan
How is the cluster shape affected when track is inclined ?
L
,PitchSizeNU pix
Lt
L: length of the particle trajectory in the epitaxial layert: epitaxial layer thicknessθ: angle of incidence with respect to the vertical
cos
80 tQ tot
tantU
cos
tL ,)/(80 LmeQ tot
• 7x7 cluster
• Each square represents one pixel
•Color scale normalised
Average Cluster Shape
Q on seed (MPV, e-)
250
249
285
348
506
823
964
Angle (°)
0
15
30
45
60
75
80
0° 15° 30°
45° 60° 75°
80°
Differences in the average cluster shape are obvious for large angles (>60o)
0° 15° 30°
45° 60° 80°
Cha
rge
colle
cted
(el
ectr
ons)
Collected charge
Signal to Noise Ratio on seed
• For small angles (<30o) the SNR is almost constant
• For bigger angles (>60o) the SNR varies significantly
Residuals
U
Vσ of the distribution of track-hit distance.
Can the inclination of the track be derived from cluster properties?
The number of significant pixels (above given threshold) is higher for 80° than for 0°.The aspect ratio is different.
Allow to identify and suppress hits from delta electrons?
U
V 0° 80°
Comparison of properties of average clusters for two angles:
....
...)3()2()1(
3,32,21,1
23,3
22,2
21,1
2
uvuvuv
uvuvuv
QQQ
vQvQvQ
Q
VQWidth defined by :
- 0°- 80°
V cluster width
U c
lust
er
wid
th
V cluster width
Can the inclination of the track be derived from cluster properties?
80°v=
u
Beam test (pions, 120GeV) on inclined tracks up to 80° was performed.
For small angles (<30o) the SNR of the seed, the charge of the seed and the charge of the full cluster are constant.
For large angles (>60o) the SNR of the seed , the charge of the seed and the charge of the full cluster increase significantly.
The residuals along the V direction (along the rotation axis) remain constant but the residuals along the U direction increase (up to 4 times for 80 degrees, but algorithm not optimised)
It seems possible to identify hits created from tracks with large incident angle. Investigate possible applications of this identification.
Next steps:Implementation of the digitiserPerform simulation study to evaluate the fraction of particles with large incident angle.
Summary and results
MotivationImplement MAPS digitiser.Study MAPS response to inclined tracks.
1 1
1 1 1 1
1 1 1
Can the inclination of the track using information from the cluster be derived ?
Q(Vi,Ui) Q(1,1)
Q(0,0)
Q(-1,1)
....
...)1()1()0(
1,11,10,0
21,1
21,1
20,0
2
QQQ
QQQ
Q
VQ
U
V
1 Digital3 CoG 3x35 CoG 5x57 Eta 4var9 Eta 3x311 Eta 2x213 Eta 5x5
0 degrees 80 degrees
Residuals 7x7 cluster: Different methods
The residuals obtained from eta 3x3 are the best even for 80 degrees rotation
Res
idu
als
(μm
)
Charge on Seed
250 249 285348
506
823
964
0
200
400
600
800
1000
1200
0 10 20 30 40 50 60 70 80 90
rotation anlge (degrees)
elec
tro
ns
Charge on seedMIMOSA 17 ( 14microns epi )
Charge 49 pixelsMIMOSA 17 ( 14microns epi )
Charge on 49 pixels
886 895 10051258
1847
3755
5048
0
1000
2000
3000
4000
5000
6000
0 10 20 30 40 50 60 70 80 90
rotation angle
char
ge
on
49
pix
els
(e-)
Noise on seed
14,8 14,8
14,7
14,8
15
14,9
14,5
14,4
14,5
14,6
14,7
14,8
14,9
15
15,1
0 10 20 30 40 50 60 70 80 90
rotation angle (degrees)
elec
trons
Noise on seedMIMOSA 17 ( 14microns epi )
Charge on 49 pixels
886 895 10051258
1847
3755
5048
0
1000
2000
3000
4000
5000
6000
0 10 20 30 40 50 60 70 80 90
rotation angle
char
ge
on
49
pix
els
(e-)
cos
80 tQ tot
constQtot cos
if CCE is const and clustering is correct:
Qtot*cos(theta)
750
800
850
900
950
1000
-20 0 20 40 60 80 100
angle (degrees)
Q(4
9pix
els)
*co
s(th
eta)
~10%
Error bars correspond to 1o
error in defining the rotation
angle
With a 10% precision CCE can be approximated as constant wrt the particle incident angle
What about charge collection efficiency at large angles?
Charge on 49 pixels (Qtot)
0 degrees 80 degrees
Residuals 7x7 cluster
μm μm
0 15 30
45 60 75
80
SNR on seed (MPV in e-)
250
249
285
348
506
823
964
Angle (degrees)
0
15
30
45
60
75
80
0 15 30
45 60 75
80
• 7x7 cluster
• Each square represents one pixel
•Color scale normalised
Mean Cluster Form (3D)