Report on the UCSC/SCIPP BeamCal Simulation Effort FCAL Collaboration Meeting CERN March 6-7, 2017

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

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

4. IV As a Function of Temperature (VB = 600 V)

5. 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 Luc D’Hauthuille T = -7 ˚C T = 0 ˚C P_total = 4.467 W P_total = 11.01 W P_max = 1.86 mW P_max = 4.59 mW (for a single pixel) (for a single pixel)

7. Total Power Draw (3 Years of Running with Si Diode Sensors 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

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

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

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

13. 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

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

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

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 e- (e+) to inverse of  system transverse momentum Longitudinal momentum ez (pz) given by H =  system energy; hz =  system longitudinal momentum 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

19. 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 19

20. Event Observables Have explored the following observables so far (“S” is just the scalar sum of transverse momenta mentioned above) 20

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26. 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) 26

27. Using the BeamCal to Obtain Information about Collision Parameters, and Impact of BeamCal Geometry Options 27

28. Contributors • 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.

29. BeamCal Face Geometry Options • “plugged” • Wedge cutout • Circle cutout “wedge” cutout Plug Insert plug here “circle” cutout 29

30. 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. What is wise choice though? Maybe just (0,0)?) • Mean x and y positions • Left-right, top-bottom, and diagonal asymmetries

31. 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 • https://wikis.bris.ac.uk/display/sid/GuineaPig+simulations+for+BeamCal+study

32. 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.

33. Example: size of bean envelope y 33

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36. IR Layout Low-Z Mask M1 Mask BeamCal L* 36

37. 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 37 Tom Markiewicz, SLAC

38. 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. 38

39. 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 39

40. Nominal IR Geometry Occupancy Distributions (Barrel) Stacked histograms! 15 x 15 1 BX 30 x 30 5 BX x10-3 x10-3 40

41. Nominal IR Geometry Occupancy Distributions (Endcap) Stacked histograms! 15 x 15 1 BX 30 x 30 5 BX x10-3 x10-3 41

42. 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 42

43. Barrel: Mean Occupancy vs. Phi x10-4 30 x 30 5 BX Occupancy roughly constant in phi 43

44. Endcap: Mean Occupancy vs. R 30 x 30 5 BX Occupancy varies drammatically with radius; dominated by inner radii 44

45. BeamCal Efficiency L* Dependence Base Small L* larger L* consistently displays higher efficiency 45

46. BeamCal Efficiency L* Dependence Factorized Difference is largely geometric 46

47. BeamCal Efficiency and the Anti-DiD Field Noticeable but small effect 47

48. Beam Envelope Scan (Electrons and Positrons)

49. Summary and Conclusions • First look at BeamCal observables and IP parameter dependence • Need to finish coding observables (thrust definition question) • Need to increase statistics (~100 pulses generated; working on simulation) • Need to develop some more interesting IP parameter variations (discussion!) • Need to explore sensitivity to BeamCal geometry • But this should be a good foot in the door for now…

50. Vertex Occupancy Dependence on L* Configuration 30 x 30 5 BX x 10-4 3.5 m L* L* occupancy differences appear to depend on backscatter deflection angle 4.1 m L* 50