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Report on UCSC/SCIPP BeamCal Simulation Effort at CERN

This report discusses the BeamCal simulation effort by the UCSC/SCIPP collaboration, focusing on topics such as radiation dose, background noise, and SUSY in the degenerate limit. The report also presents a model for power draw and improved beamcal power consumption. Additionally, the report examines the use of the BeamCal for a two-photon event veto and proposes a prediction algorithm for scattered electrons in two-photon events.

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Report on UCSC/SCIPP BeamCal Simulation Effort at CERN

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  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

  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) PF sensor; 270 Mrad irradiation (see yesterday’s talk)

  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 BeamCalCollapsed into Single Layer 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 electron (positron) 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

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  20. WW Events (both e+ and e- can deflect) S =  |pT| > 1 GeV Prediction Using MC Truth Discard Particle with |cos| > 0.9 Loss of coverage increases “perilous” outcome a bit, but also almost eliminates ability to predict when e hits BeamCal 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

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

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  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

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

  29. 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.

  30. BeamCal Face Geometry Options • “plugged” • Wedge cutout • Circle cutout “wedge” cutout Plug Insert plug here “circle” cutout 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 • https://wikis.bris.ac.uk/display/sid/GuineaPig+simulations+for+BeamCal+study

  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 y 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

  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

  37. BackUp BackUp…

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

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

  40. 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 40 Tom Markiewicz, SLAC

  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

  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

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

  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

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

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

  48. 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* 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

  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 Circle Wedge 50

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