1. Report on the UCSC/SCIPP BeamCal Simulation Effort
FCAL Collaboration Meeting
CERN
March 6-7, 2017
Bruce Schumm
UC Santa Cruz Institute for Particle Physics
For the SCIPP FCAL group
Don’t forget x,y recon results
X2 background effect
Description of algorithm
Segmentation strategy study 1

2. The SCIPP BeamCal Simulation Group
The group consists of UCSC undergraduate physics majors, and currently comprises
Jane Shtalenkova (Lead)
Luc D’Hauthuille, Benjamin Smithers, Summer Zuber(*), Cesar Ramirez, William Wyatt
(*) Will be a CERN summer student this summer
Led by myself, in consultation and collaboration with Jan Strube, Aidan Robson, Anne Schuetz, Tim Barklow
FLUKA simulation of the BeamCal (radiation dose, backgrounds in the central detector)
Determining ILC IP parameters with the BeamCal
BeamCal reconstruction and design
SUSY in the degenerate limit; forward calorimeter coverage

3. Neutrons in and From the BeamCal
Dark current for Si Diode detectors
Neutron fluence through electronics and into central detector 3 3

4. IV As a Function of Temperature (VB = 600 V)
PF sensor; 270 Mrad irradiation (see yesterday’s talk)

5. P(R,T) = (R/270MRads)*(600V)*I(T)
Model for Power Draw
Using these assumptions, power drawn by a
pixel is:
P(R,T) = (R/270MRads)*(600V)*I(T)
where R is radiation dosage, T is temperature, 600V is the Bias Voltage and I(T) is the current given by the fit.

6. Power Drawn (Watts) of BeamCal Collapsed into Single Layer
Luc D’Hauthuille
T = -7 ˚C
T = 0 ˚C
P_total = W
P_total = W
P_max = mW
P_max = mW
(for a single pixel)
(for a single pixel)

7. Total Power Draw (3 Years of Running with Si Diode Sensors
Operating Temperature (0C)
Total Power Draw (W)
Maximum for 1mm2 Pixel (mW) 15 56 23 7 25 10 11
4.6 -7
4.5
1.9
Luc D’Hauthuille

8. However: Away from shower max, irradiation from ballistic particles may be small, but the peripheral neutron flux must also be considered
Also should consider neutron field through electronics, and perhaps central detector as well 8 8

9. Improved BeamCal Power Consumption Model
T506 results on Si diodes suggest fairly universal leakage current dependence on dose
Conservatively assume that radiation damage entirely due to neutron flux
Using FLUKA simulations of T506 target, “calibrate” relation between neutron fluence and VB = 600V leakage current
Ben Smithers 9 9 9

10. e- e- T506 Target Expanded View Sensor 14 mm T506 Target 46 cm 10 10

11. FLUKA e fluence for T506 sensor for 10 GeV beam
e+e-/primary/cm2
Integral within ~30% of corresponding GEANT result 11 11 11

12. FLUKA neutron fluence for T506 sensor for 10 GeV beam
Integrated fluence takes into account direction cosine and neutron damage energy dependence; result will be calibration of leakage current in terms of n1MeV-cm where n1MeV is the 1 MeV equivalent neutron flux
neutrons/primary/cm2
0.0025 12 12 12

13. will be interfaced to GuineaPig e pair input files Si leakage current
FLUKA BeamCal model;
will be interfaced to GuineaPig e pair input files
Si leakage current
Neutron flux through beamcal electronics
Neutron flux into central detector 13 13 13

14. Two-Photon Backgrounds to SUSY
Notes on use of BeamCal for a two-photon event veto
Consequences of limited hadronic coverage 14 14 14

15. Two-Photon Event Facts
Tim Barklow has simulated   hadrons down to the  threshold
Photon flux from
Beamstrahlung (B)  no pT kick for e
Weiszacker-Williams (W)  e sometimes get pT kick
For only about 15% of  events does an e get a pT kick 15 15 15

16. Most  events leave very little pT in the detector, but for those that do, we’ll need to know they were  events by finding the scattered e if there is one. 16 16 16

17. The “Prediction Algorithm”
Jane Shtalenkova
Based on the properties of the hadronic () system, can predict trajectory of deflected e up to two-fold ambiguity (don’t know if e+ or e- scattered)
Set transverse momentum eT (pT) of scattered electron (positron) to inverse of  system transverse momentum
Longitudinal momentum ez (pz) given by
H =  system energy; hz =  system longitudinal momentum 17 17 17

18. Prediction Algorithm cont’d
Thus, each event gives us a prediction of where the e- (e+) would have gone if the e- (e+) got the entire pT kick.
If this assumption is true, and the hadronic system is perfectly reconstructed, one of these is exactly correct and the other is wrong (the “wrong” particle in fact goes straight down the exhaust beam pipe).
Assumed veto strategy:
Case 1): If one or both of the e are “predicted” to miss the BeamCal (neither would get enough kick), veto as  event.
Case 2): If both the e+ and e- are “predicted” to hit the BeamCal, veto if either is found in the BeamCal
Peril: If both e are “predicted” to hit the BeamCal, but in fact none does, event is mistaken for SUSY 18 18 18

19. 19 19 19

20. WW Events (both e+ and e- can deflect) S =  |pT| > 1 GeV
Prediction Using MC Truth
True Pred
Both Hit
One Hit
Both Miss
1.8
0.1
0.3
3.0
0.9
0.7
2.9
1.3
89.2
Discard Particle with |cos| > 0.9
True Pred
Both Hit
One Hit
Both Miss
0.4
0.0
1.8
0.9
3.6
3.2
90.1
Loss of coverage increases “perilous” outcome a bit, but also almost eliminates ability to predict when e hits BeamCal 20 20 20

21. SUSY Signal Selection
At SCIPP, have simulated e+e-~+~- ; ~0 over a range of ~ mass and ~/0 degeneracy
m~ = 100, 150, 250 GeV
m = m~-m = 20.0, 12.7, 8.0, 5.0, 3.2, 2.0 GeV
Exploring discriminating observables and the impact of limited detector coverage
Summer Zuber 21 21 21

22. Event Observables
Have explored the following observables so far (“S” is just the scalar sum of transverse momenta mentioned above) 22 22 22

23. 23 23 23

24. 24 24 24

25. 25 25 25

26. 26 26 26

27. Going from full to 90% coverage causes significant loss of discriminating power for “V”.
(But note that “S” improves  can improve definition and/or find additional discriminating variables; looking into thrust vector and razor observables) 27 27 27

28. Using the BeamCal to Obtain Information about Collision Parameters, and Impact of BeamCal Geometry Options 28 28 28

29. Contributors Goal Luc D’Hauthuille, UCSC Undergraduate (thesis)
Anne Schuetz, DESY Graduate Student
Christopher Milke, UCSC Undergraduate
With input from Glen White, Jan Strube, B.S.
Goal
Idea is to explore the sensitivity of various beamstrahlung observables, as reconstructed in the BeamCal, to variations in IP beam parameters. The sensitivity will be explored with various different BeamCal geometries.

30. BeamCal Face Geometry Options
“plugged”
Wedge cutout
Circle cutout
“wedge” cutout
Plug
Insert plug here
“circle” cutout 30 30 30

31. Of these, we believe the following can be reconstructed in the BeamCal:
Total energy and its r, 1/r moment
Mean depth of shower
Thrust axis and value (relative to barycenter; could also use mode of distributions.)
Mean x and y positions
Left-right, top-bottom, and diagonal asymmetries

32. IP Parameter Scenarios
Thanks to Anne Schuetz, GuneaPig expert
Relative to nominal:
Increase beam envelop at origin (via -function), for electron and positron beam independently, by 10%, 20%, and 30%
Move waist of electron and positron beam (independently) back by 100m, 200 m, 300 m.
Change angle  of orientation of transverse electron and positron beam profile (independently) by 5 mrad and 20 mrad
Details at

33. First (Early) Results Luc is coding the following observables:
Deposited energy, mean depth of shower, L/R and up/down and U/V asymmetries, thrust value, r and 1/r moments (relative to barycenter for properly targeted beams when transverse coordinates are in play).
He has explored the following “trajectories”:
Beam envelope for electrons, positrons
Waist position for electrons, positrons
 angle of electron, positron beam profile
Several other targeting anomalies have been generated (including correlations such as y,y/, etc.) but have yet to be simulated.

34. Example: size of bean envelope y34 34 34

35. Example: size of bean envelope y
In process of exploring full set of observables for each mistargeting scenario (soon!)
Next step will be to explore dependence upon BeamCal geometry 35 35 35

36. Summary and Outlook Several studies underway Neutrons from the BeamCal
leakage current
flux through electronics
central detector occupancy
Nearly-degenerate SUSY
BeamCal performance
detector hermeticity
Mistargeting signatures
BeamCal geometry
Shooting significant progress for ALCW2017 (SLAC/SCIPP), June 26-30 36 36 36

37. BackUp
BackUp…
Bruce Schumm

38. Effect of L*, Anti-DID, and BeamCal geometry on Vertex Detector Occupancy from BeamCal Backsplash38 38 38

39. IR Layout
Low-Z Mask
M1 Mask
BeamCal L* 39 39 39

40. Beam entrance and exit holes
Incidence of pair backgrounds on BeamCal with and without “anti-DiD” field
BeamCal Face
Without anti-DiD
With anti-DiD
Beam entrance and exit holes
Tom Markiewicz, SLAC 40 40 40

41. Configurations Explored
Nominal: L* = 4.1m; no antiDiD; plug in place
Then, relative to Nominal:
Small L*: L* = 3.5m
AntiDID: Include antiDiD field
Small L* AntiDID: L* = 3.5m with antiDiD field
Wedge: Remove BeamCal plug
Circle: Remove additional BeamCal coverage as shown in prior slide. 41 41

42. Vertex Detector Configurations
We have studied occupancy as a function of two aspects of the VXD readout architecture
Pixel size
15 x 15 microns2
30 x 30 microns2
Integration time
1 beam crossing
5 beam crossings 42 42 42

43. Nominal IR Geometry Occupancy Distributions (Barrel)
Stacked histograms!
15 x 15
1 BX
30 x 30
5 BX
x10-3
x10-3 43 43 43

44. Nominal IR Geometry Occupancy Distributions (Endcap)
Stacked histograms!
15 x 15
1 BX
30 x 30
5 BX
x10-3
x10-3 44 44 44

45. We note that: Pulse-by-pulse variation is small
Occupancy only appreciable for largest pixel size (30x30) and greatest integration time (5 Bx)
Inner layer (0) dominates occupancy in barrel
Inner layer (0) characteristic of occupancy in endcap
Study IR configuration dependence with layer 0 (both endcap and barrel) for 30x30 pixel integrating over 5 Bx.
In terms of: azimuthal dependence in barrel; radial dependence in endcap 45 45 45

46. Barrel L0: Mean Occupancy vs. Phi
x10-4
30 x 30
5 BX
Occupancy roughly constant in phi 46 46 46

47. Endcap: Mean Occupancy vs. R
30 x 30
5 BX
Occupancy varies drammatically with radius; dominated by inner radii 47 47 47

48. Vertex Occupancy Dependence on L* Configuration
5 BX
x 10-4
3.5 m L*
L* occupancy differences appear to depend on backscatter deflection angle
4.1 m L* 48 48 48

49. Vertex Occupancy Dependence on Anti-did Field
Plug is in place!
30 x 30
5 BX
x 10-4
Base
Anti-did field generally improves occupancy in barrel and consistently improves occupancy in endcap
Anti-did 49 49 49

50. Occupancy Dependence on Plug Geometry
x 10-4
Base
As expected, occupancy gets progressively lower as more of the BeamCal plug is cut away
Wedge
Circle 50 50 50

51. BeamCal Efficiency L* Dependence
Base
Small L*
larger L* consistently displays higher efficiency 51 51 51

52. BeamCal Efficiency L* Dependence Factorized
Difference is largely geometric 52 52 52

53. BeamCal Efficiency and the Anti-DiD Field
Noticeable but small effect 53 53 53

54. Tiling strategy and granularity study
Constant
7.6x7.6
5.5x5.5
3.5x3.5
Variable
Nominal
Nominal/2
Nominal/2