Post on 29-Jan-2016
HEP Tel Aviv University
LumiCal (pads design)Simulation
Ronen Ingbir
FCAL Simulation meeting, Zeuthen
Tel Aviv University HEP experimental Group
CollaborationHigh precision design
HEP Tel Aviv University
Presentation Outline
Reconstruction Algorithms
Detector Simulation
(& Design
optimization)
Fast Detector Simulation
(Luminosity)
Events Selection
Physics Simulation
Electronics Simulation
(Basic model)
And More …
Analyses
CollaborationHigh precision design
HEP Tel Aviv University
Electrons/Bhabhas
)(rad
Bhabha
Pure electrons
Electron energy (GeV)
Pure electrons
Bhabha
CollaborationHigh precision design
Electrons/Positrons - Geant-3 integrated generator.
Bhabha scattering - BHWIDE generator
Beamstrahlung and Beam spread
HEP Tel Aviv UniversityCollaboration
High precision design
Beamstrahlung - Circe generator.
Beam spread – Included separately (home made routine).
HEP Tel Aviv University
250GeV
26 mrad
Events selection - old approach
Gaussian fit and energy
calibration based tail cut
Acceptance cut was based
on the leakage
rec
Detector signal
CollaborationHigh precision design
HEP Tel Aviv University
33 mrad
Energy Resolution )( GeV
)(rad
The most significant event selection cut is the geometric acceptance cut.
This cut was used to get the best energy, angular resolutions and minimum biases.
Events selection
CollaborationHigh precision design
HEP Tel Aviv University
Left-Right balance RL
Simulation distribution
Distribution after acceptance and energy balance selection
Right side detector signal
Lef
t si
de
det
ecto
r si
gnal Right signal - Left signal
)(21 rad
(deg)21 Collaboration
High precision design
HEP Tel Aviv University
Out
In
Eout - EinEout + EinP=
New selection cut
Ring
Signal
CollaborationHigh precision design
HEP Tel Aviv University
Eout-EinEout+EinP=
)(rad
Out
In
CollaborationHigh precision design
HEP Tel Aviv University
3 cylinders
3 Rings
2 cylinders
3 Rings
1 cylinders
3 Rings
Eout-EinEout+EinP=
)(min radCollaboration
High precision design
HEP Tel Aviv University
Reconstruction Algorithms
CollaborationHigh precision design
Angular reconstruction:
• ‘Normal’ energy weight
• Logarithmic weighting with selection cutoff.
• Logarithmic weighting per layer (Bogdan’s algorithm).
• ‘Real life’ approach.
Energy reconstruction:
• Energy resolution.
• Energy calibration.
HEP Tel Aviv University
Reconstruction Algorithm
)]}ln([,0max{T
ii E
EconstW
i
ii
E
EXX
i
ii
W
WXX
Events Num.
)(radgenrec
)(radgenrec
)(radgen
We explored two reconstruction algorithms:
The log. weight fun. was designed to reduce steps in a granulated detector :
1. Selection of significant cells.
2. Log. smoothing.
Log. weight.
E weight.
T.C Awes et al. Nucl. Inst. Meth. A311 (1992) 130.
CollaborationHigh precision design
HEP Tel Aviv University
Logarithmic Constant
Constant value
Constant value
)]}ln([,0max{T
ii E
EconstW
After selecting:
We explored a more systematic approach.
The first step is finding the best constant to use under two criteria:
1. Best resolution.
2. Minimum bias.
400 GeV
))(_( radmean genrec
))(( rad
CollaborationHigh precision design
HEP Tel Aviv University
Energy dependent constant
)]}ln()([,0max{T
ibeami E
EEconstW
The goal is to find a global weight function.
Is the the log. weight constant really a constant ?
Constant value Collaboration
High precision design
HEP Tel Aviv University
Shower reconstruction
Nu
m. o
f C
ells
Nu
m. o
f Se
ctor
s
Nu
m. o
f C
ylin
de r
s
En
ergy
por
tion
(%
)
En>90%
)(rad )(rad
)(rad)(rad
What happens when we select the best log. weight constant ?
Shower size
Log. Weight Selection
Most of the information is in the selected cells.
CollaborationHigh precision design
HEP Tel Aviv University
Algorithms Comparison
CollaborationHigh precision design
15 Cylinders 40 Cylinders 64 Cylinders
Pads - Full Log.
Pads - Bogdans log.
Strips - Bogdans log.
13*10e-5 5*10e-5
14*10e-5
4*10e-5
1. Two methods are equivalent - reason : in both cases Theta is reconstructed directly.
2. There is a saturation limit for the resolution (before 64 cylinders).
HEP Tel Aviv University
Real life algorithm
Working with both sides of the detector and looking at the difference between the reconstructed properties:
(In real life we don’t have generated properties)
2new
CollaborationHigh precision design
HEP Tel Aviv University
‘Pure’ electrons simulation Bhabha+Beam+BS(5e-4)
)(radgenrec
Bias study
44 103.1107.5
CollaborationHigh precision design
Two plots convinced us that the bias observed is not detector design dependent nor imperfect algorithm.
HEP Tel Aviv University
48 sectors design
(deg)genrec X (cm)
Y (cm)
Bias study
CollaborationHigh precision design
HEP Tel Aviv University
Magnetic field
CollaborationHigh precision design
HEP Tel Aviv University
Energy resolution
Ntuple
No
cuts
With
cuts
Pure electrons
31% 29%
Bhabha
42% 24%
Bhabha + Beamstrahlung
45% 24%
Bhabha + Beamstrahlung + Beam spread (0.05%)
46% 25%
Bhabha + Beamstrahlung +Beam spread (0.5%)
49% 29%
CollaborationHigh precision design
HEP Tel Aviv University
Angular resolution
CollaborationHigh precision design
Pad design
0.34 cm Tungsten
0.31 cm Silicon
Cell Size1.3cm*2cm>1.3cm*6cm<
~1 Radiation length
~1 Radius Moliere
HEP Tel Aviv University
15 cylinders * 24 sectors * 30 rings = 10800 cells
RL
8 cm
28 cm
6.10 mCollaboration
High precision design
Dense0.156e-3Regular0.137e-3
Dense, 35%
Regular, 27%
0 0.05 0.1 0.15 0.2 0.25 0.3 0.35
Ang
ular
res
olut
ion
(rad
)E
nerg
y re
solu
tion
(GeV
)^0.
5
Regular
Dense
HEP Tel Aviv University
0.34 cm Tungsten
0.31 cm Silicon
0.55 cm Tungsten
0.1 cm Silicon
Dense design
CollaborationHigh precision design
HEP Tel Aviv University
30 radiation length detector47 radiation length detector
Z (cm)
Detector Signal
0.8cm
1.1cm
Moliere radius & Radiation length
CollaborationHigh precision design
HEP Tel Aviv University
)(rad
Energy Resolution )( GeV
)(rad
Events
New geometric acceptance
CollaborationHigh precision design
HEP Tel Aviv University
Detector optimization
CollaborationHigh precision design
HEP Tel Aviv University
Optimization
CollaborationHigh precision design
HEP Tel Aviv University
Optimization
CollaborationHigh precision design
HEP Tel Aviv University
Margins around cells
Having margins
Means
Losing InformationCollaboration
High precision design
HEP Tel Aviv University
One cylinder One sector
Radius (cm) ) deg(
Det
ecto
r si
gnal
Det
ecto
r si
gnal
Loosing information
CollaborationHigh precision design
HEP Tel Aviv University
Margins in between cells
Energy resolution Polar resolution
CollaborationHigh precision design
HEP Tel Aviv University
Our basic detector is designed with
30 rings * 24 sectors * 15 cylinders = 10,800 channels
Do we use these channels in the most effective way?
Maximum peak shower design
30 rings 15 cylinders
20 cylinders
10 cylinders
24 sectors * 15 rings * (10 cylinders + 20 cylinders) = 10,800 channels
4 rings 15 rings 11 rings
10 cylinders
CollaborationHigh precision design
HEP Tel Aviv University
Maximum peak shower design
Basic Design
Angular resolution improvement
without changing the number of
channels
Other properties remain the same
))(_( radmean genrec
))(( rad
Constant value
Constant value
Polar reconstruction
0.11e-3 rad0.13e-3 rad
CollaborationHigh precision design
HEP Tel Aviv University
Electronics Simulation
CollaborationHigh precision design
Normal Cells
'Dead' Cells
Noise Cells
totalNnormalNdeadNnoiseN ____
Noise Function
5_
_
NoiseTotal
SignalTotalCase Study in which:
min max
(Signal+noise) - (signal)
70% Noise Cells example
Noise signal
N
N
(Basic model)
Random selection of cells
HEP Tel Aviv UniversityCollaboration
High precision design
0%
50%
25%
10%
Signal (including Dead Cells)Signal (including Noise Cells)
100%
0% 50% NN
5_
_
NoiseTotal
SignalTotal
Noise Cells / Dead Cells
Case Study:
HEP Tel Aviv UniversityCollaboration
High precision design
)%(
)( GeVHaving ‘Dead’ cells affects both the reconstruction of the energy and the angles in the same way.
Having Noise in the cells:
1. Assuming noise function with no extreme values.
2. Assuming high signal to noise ratio.
3. Using log weight function with revised cut value (that takes into account the new average ‘zero level’).
Similar resolutions
Performance with noise and dead cells
preliminary
HEP Tel Aviv University
Fast Detector Simulation
CollaborationHigh precision design
Motivation :
High statistics in required to notice precision of : 410L
L
There is an analytic calculation (and approximation) :
(Which is the precision goal of the ILC)
*2
L
L
Is it a good approximation ? This calculation takes into account only the Bhabha angular distribution, how does other factors affect (backgrounds, detector design, electronics noise) ?
We need a mechanism to actually count events, as if it was real life.
HEP Tel Aviv University
High Statistics MC
)),(( N
NL
L
)(rad)(rad
BHWIDE + fast detector simulation
CollaborationHigh precision design
min
*2
L
L 310
HEP Tel Aviv University
R&D status
))(,,),(( EENN
LL High statistics MC
410 N
NElectronics noise and ‘Dead’ Cells
CollaborationHigh precision design
Design optimization (Dense design, Margins in between cells, Maximum peak shower design)
Pure electron MC
Detector properties
Events selection
‘Real physics’ MC
Bhabha + Beamstrahlung + Beamspread
Reconstruction Algorithms
HEP Tel Aviv University
Future Steps
CollaborationHigh precision design
‘Real physics’ MCFinal
optimization
Luminosity with a crossing angle
Luminosity with polarised beams (Gideon Alexander)
Pad/Strip comparison
Geant-4 transition
Additional background studies (two photon events, beamstrahlung hitting the detector)
Additional hardware design constrains and electronics simulation (digitisation, reality noise parameters, silicon production constrains)
HEP Tel Aviv University
THE END
CollaborationHigh precision design