1. Analysis of DHCAL Events
José Repond
Argonne National Laboratory
Frascati, February , 2012

2. The DHCAL Project RPC – based imaging calorimeter
DHCAL = First large scale calorimeter prototype with
Embedded front-end electronics
Digital (= 1 – bit) readout
Pad readout of RPCs (RPCs usually read out with strips)
Extremely fine segmentation with 1 x 1 cm2 pads
DHCAL = World record channel count for calorimetry
Argonne National Laboratory
Boston University
Fermi National Accelerator Laboratory
IHEP Beijing
Illinois Institute of Technology
University of Iowa
McGill University
Northwestern University
University of Texas at Arlington
DHCAL Collaboration
Heads
Engineers/Technicians 22
Students/Postdocs 9
Physicists 10
Total 41
…and integral part of

3. Calorimeters/configurations
DHCAL
38 layers, each 1 x 1 m2
1.2 X0 Fe (+ Cu) absorber plates
350,000 readout channels
Tail Catcher
14 layers, each 1 x 1 m2
8 1.7 X0 Fe (+Cu) X0 Fe (+Cu) absorber plates
129,000 readout channels
Silicon – Tungsten Electromagnetic Calorimeter
30 layers, each 18 x 18 cm2
Variable thickness Tungsten absorber
10,000 readout channels
Minimal Absorber Structure
50 layers, each 1 x 1 m2
0.27 X0 Fe (+Cu) absorber plates
461,000 readout channels

4. Tests in the Fermilab Test Beam
Fermilab Test Beam Facility
120 GeV primary proton beam
1 – 60 GeV/c secondary beam (pions, positrons, muons…)
Broadband muon beam
3.5 second long spills every minute
Muon data taking
+32 GeV/c secondary and 3 m Fe absorber
DAQ rates 500 – 2000/spill
DAQ triggered by a pair of 1 x 1 m2 Scintillator paddles
Secondary beam data taking
DAQ rates 50 – 500/spill
DAQ triggered by a pair of 19 x 19 cm2 Scintillator paddles
1 x 1 m2 Scintillator Paddle A
1 x 1 m2 Scintillator Paddle B
DHCAL
Tail
Catcher
Trigger
DHCAL
Tail
Catcher
Trigger
Cerenkov
19 x 19 cm2 Scintillator A
19 x 19 cm2 Scintillator B

5. World record in calorimetry
The DHCAL in the Fermilab Test Beam
Date
DHCAL layers
Tail catcher layers
Total RPC layers
Configuration
Readout channels
Number of
Muon events
Secondary events
October 2010 38
DHCAL
350,208
1.4M
2.9M
January 2011 13 51
DHCAL + TAIL CATCHER
470,016
1.6M
5.2M
April
2011 14 52
+ CALICE Si-W ECAL
488,952
2.5M
7.3M
June
479,232
3.3M
6.0M
November 50
Minimal Absorber
460,800
0.6M
4.5M
TOTAL
9.4M
25.8M
488,952 readout channels
World record in calorimetry

6. Energy reconstruction in the DHCAL
Data
Consists of hit patterns of pads with signal above 1 threshold and
their time-stamps with 100 ns resolution
Incident particle energy reconstruction
To first order
E ∝ N N = ∑layer Ni … total number of hits
Correction for contribution from noise
E ∝ N - Nnoise Nnoise … accidental hits
Correction for variation in chamber inefficiency
E ∝ ∑layer Ni ·(ε0 /εi) – Nnoise ε0 … average DHCAL efficiency
εi … efficiency of layer i
Correction for variation in pad multiplicity
E ∝ ∑layer Ni ·(ε0 /εi) ·(μ0 /μi) – Nnoise μ0 … average pad multiplicity
` μi … average pad multiplicity of layer i
Second order corrections
Compensate for e/h ≠ 1
Saturation (more than 1 particle/pad) …

7. General DHCAL Analysis Strategy
Noise measurement
- Determine noise rate (correlated and not-correlated)
- Identify (and possibly mask) noisy channels
- Provide random trigger events for overlay with MC events (if necessary)
Measurements with muons
- Geometrically align layers in x and y
- Determine efficiency and multiplicity in ‘clean’ areas
- Simulate response with GEANT4 + RPCSIM (requires tuning 3-6 parameters)
- Determine efficiency and multiplicity over the whole 1 x 1 m2
- Compare to simulation of tuned MC
- Perform additional measurements, such as scan over pads, etc…
Measurement with positrons
- Determine response
- Compare to MC and tune 4th (dcut) parameter of RPCSIM
- Perform additional studies, e.g. software compensation…
Measurement with pions
- Compare to MC (no more tuning) with different hadronic shower models
- Perform additional studies, e.g. software compensation, leakage correction…
This talk
This talk +
Poster

8. Some cute muon events Note: Consecutive events (not selected)
Look for random noise hits

9. DHCAL rotated by 100 Increased MIP detection efficiency
Average pad multiplicity
→ As seen with cosmic rays

10. Estimation of contributions from noise
Data collection (in general)
Trigger-less (all hits) mode for noise, cosmics
Triggered (record hits in 7 time bins of 100 ns each) for noise, cosmics, testbeam
→ Only hits in 2 time bins used for physics analysis
Noise measurement
These results from trigger-less mode
In quantitative agreement with measurements with random trigger
Results
Noise rate measured to be 0.1 – 1.0 Hz/cm2
Rate strongly dependent on the temperature of the stack
(FE-electronics embedded into stack and generates heat)
Tail catcher in 4/2011 run
DHCAL in 4/2011 run
DHCAL in 10/2010 run
Noise rate [Hz/cm2]
0.1
0.5
1.0
Nnoise/event in DHCAL + Tail Catcher (2 time bins)
0.009
0.05
0.09
Nnoise/event in DHCAL + Tail Catcher (7 time bins)
0.033
0.165
0.33
1 hit corresponds to ~ 60 MeV!
Contribution from noise negligible for most analysis

11. Tracking Clustering of hits Loop over layers 1 cluster 2 clusters
Performed in each layer individually
Use closest neighbor clustering (one common side)
Determine unweighted average of all hits in a given cluster (xcluster ,ycluster)
Loop over layers
for layer i request that all other layers have Njcluster ≤ 1
request that number of hits in tracking clusters Njhit ≤ 4
request at least 10/38(52) layers with tracking clusters
fit straight line to (xcluster,z) and (ycluster,z) of all tracking clusters j
calculate χ2 of track
request that χ2/Ntrack < 1.0
inter/extrapolate track to layer i
search for matching clusters in layer i within
record number of hits in matching cluster

12. Geometrical alignment
For each readout board i plot residual in x/y
Rix = xi cluster- xitrack
Riy = yicluster - yitrack
Average residuals per front-end board
in x
in y

13. After SW alignment of each readout board
Note expanded y-scale
RMS
1104 → 62 μm
RMS
265 → 21 μm
1 entry/readout board

14. Simulation Strategy Comparison Parameters GEANT4
Experimental set-up
Beam (E,particle,x,y,x’,y’)
Measured signal Q distribution
Points (E depositions in
gas gap: x,y,z)
GEANT4
RPC response simulation
Hits
Parameters
Distance cut dcut
(within which only 1 avalanche)
Charge adjustment Q0
(if needed)
Exponential slopes a1, a2
(of signal spread in pad plane)
Ratio R
(between 2 exponentials)
Threshold T
(of discriminator)
Hits
Comparison
DATA
With muons – tune a1, a2, R, T, (dcut), and Q0
With positrons – tune dcut
Pions – no additional tuning

15. x = Mod(xtrack + 0.5,1.) for 0.25 < y < 0.75
y = Mod(ytrack – 0.03,1.) for 0.25 < x < 0.75
Scan across one 1 x 1 cm2 pad
Note These features not implemented explicitly into simulation
Simulation distributes charge onto plane of pads…

16. Efficiencies, multiplicities
Select ‘clean’ regions away from
- Dead ASICs (cut out 8 x 8 cm2 + a rim of 1 cm)
- Edges in x (2 rims of 0.5 cm)
- Edges in y (6 rims of 0.5 cm)
- Fishing lines (12 rectangles of ±1 cm)
- Layer 27 (with exceptionally high multiplicity)
Measured average response
Note: Simulation of RPC response tuned to this data
Tail towards higher multiplicity reproduced with 2nd exponential

17. Response over the entire plane
Implemented dead areas of data in MC (= corresponding hits deleted)
Note
x/y-axis in [cm] not [pad number]
x-distribution
Well reproduced
y-distribution
Inter-RPC gaps well reproduced
Fishing lines well reproduced
Edges well reproduced

18. Calibration constants, etc…
Calibration factors = mean of multiplicity distribution/(average over detector) = ε·μ/ ε0·μ0

19. Analysis of Primary and Secondary Beam Data
50 GeV pion showers
Muon traversing stack
No isolated hits
photons, neutrons
Isolated hits from

20. Unidentified μ's, punch through
Results - October 2010 Data
CALICE Preliminary
Gaussian fits over the full response curve
Unidentified μ's, punch through

21. Pion Response N=aE As expected, linear up to > 25 GeV
CALICE Preliminary
(response not calibrated)
N=aE
Standard pion selection
+ No hits in last two layers
(longitudinal containment
16 (off), 32 GeV/c (calibration off)
data points are not included in the fit.
As expected, linear up to > 25 GeV

22. Energy Resolution for Pions (response not yet calibrated)
CALICE Preliminary
(response not yet calibrated)
B. Bilki et.al. JINST 4 P10008, 2009
MC predictions for a large-size DHCAL based on results from small scale prototype.
32 GeV data point is not included in the fit.
Standard pion selection
+ No hits in last two layers (longitudinal containment)
Measurements confirm prediction

23. (response not yet calibrated)
B. Bilki et.al. JINST 4 P04006, 2009
Positron Response
CALICE Preliminary
(response not yet calibrated)
N=a+bEm
Non-linearity
Due to saturation (more than 1 hit/pad)
Can be improved with software compensation
Not detrimental: this is a hadron calorimeter!
Data (points) and MC (red line) from small prototype test and the MC predictions for a large-size DHCAL (green, dashed line).
Measurements confirm prediction

24. Compensation? Due to saturation (=more than
one hit/pad) for em showers
→ Can be overcome with software
compensation, fractal analyses…
As usual in calorimeters
with Iron absorbers
Careful choice of segmentation (1 x 1 cm2 pads)
→ Compensation

25. Events taken with Minimal Absorber
Stack
50 layers
Cassette contain 2 mm Cu and 2 mm Fe
0.27 X0/layer → 13.4 X0 total
0.038 λI/layer → 1.9 λI total
Beam
1,2,3,4,6,8,10 GeV/c secondaries
8 GeV e+
16 GeV/c π+
8 GeV/c π+

26. Concept of a Digital Hadron Calorimeter (almost) validated
Conclusions
The DHCAL provides new insight into showers
Preliminary results have been presented using muons
Geometrical alignment
Response across pad
Performance parameters in ‘clean’ regions
Performance parameters over the entire plane
Performance as function of time
Comparison with track segment method
Results compared to GEANT4 + RPCSIM simulation
RPCSIM tuned to reproduce performance in ‘clean’ regions
Overall reasonable agreement with data observed
Preliminary results have been presented using the secondary beam
Response to pions and positrons consistent with expectations
Concept of a Digital Hadron Calorimeter (almost) validated

27. Backup Slides

28. RPCSIM Parameters Distance dcut Charge Q0 Slope a1 Slope a2 Ratio R
Distance under which there can be only one avalanche
(one point of a pair of points randomly discarded if closer than dcut)
Charge Q0
Shift applied to charge distribution to accommodate possible differences in
the operating point of RPCs
Slope a1
Slope of exponential decrease of charge induced in the readout plane
Slope a2
Slope of 2nd exponential, needed to describe tail towards larger number of hits
Ratio R
Relative contribution of the 2 exponentials
Threshold T
Threshold applied to the charge on a given pad to register a hit
Only used in
2 exponential
parameterization