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UCSC/SCIPP BeamCal Simulation Effort at ECFA Linear Collider Workshop

This report presents the simulation efforts of the UCSC/SCIPP BeamCal Simulation Group at the ECFA Linear Collider Workshop in Santander, Spain. The report covers topics such as power consumption of irradiated Si sensors, determining ILC IP parameters with the BeamCal, Bhabha events and two-photon physics veto, and SUSY in the degenerate limit.

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UCSC/SCIPP BeamCal Simulation Effort at ECFA Linear Collider Workshop

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  1. Report on the UCSC/SCIPP BeamCal Simulation Effort ECFA Linear Collider Workshop Palacio de la Magdalena Santander, Cantabria, Spain May 30 – June 5, 2016 Bruce Schumm UC Santa Cruz Institute for Particle Physics

  2. The SCIPP BeamCal Simulation Group • The group consists of UCSC undergraduate physics majors (and one engineering major) • Christopher Milke (Lead)* Heading to SMU’s doctoral program in fall • Jane Shtalenkova, Luc D’Hauthuille, Spenser Estrada, Benjamin Smithers, Summer Zuber, Cesar Ramirez • AlixFeinsod • Led by myself, with technical help and collaboration from Jan Strube, Anne Schuetz, Tim Barklow • Power consumption for irradiated Si sensors • VXD Occupancy / Anti-DiD Field • Determining ILC IP parameters with the BeamCal • Bhabha events and the two-photon physics veto • SUSY in the degenerate limit

  3. Luc d'Hauthuille Bruce Schumm University of California, Santa Cruz Power Draw of the Beam Calorimeter as a function of Temperature & Radiation Dosage

  4. Motivation • Folk wisdom suggests that Si diode sensors are not ideal for high-radiation environments due to their development of significant leakage current • This may be correct, but is it truly a problem? • We have taken extensive IV data as a function of ambient and annealing temperature, for a P-type sensor exposed to 270 Mrad (~ 3 years) of electromagnetically-induced radiation. • Here, we estimate the resulting distribution & sum of the dark-current power draw in the BeamCal

  5. Assumptions Power modeled as a function of radiation and temperature Power drawn scales linearly with radiation dosage Temperature dependent IV data was taken at SCIPP for a Si sensor exposed to 270 MRads of radiation after a 60˚C annealing process, by Cesar Gonzalez & Wyatt Crockett. A 3rd degree polynomial was fit to this I vs. T data, for a Bias Voltage = 600V

  6. Overview • The LCSIM framework was used to compute the energy deposited from 10 simulated background events (bunch crossings at 500 GeV collision energy) • Energy deposited was then extrapolated for 3 years of runtime, and converted to radiation dosage • Temperature was input and combined with radiation dosage to compute the power draw for each mm^2 pixel, at each layer, for 600V bias (charge-collection about 90% after 270 Mrad) • Power draw of these pixels was plotted on a heatmap for a range of temperatures (-7, 0,7, 15 ˚C)

  7. IV Curves at various Temperatures

  8. Polynomial Fit for Temperature Dependent Current (600 V)

  9. 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.

  10. Layers 2 & 10 of BeamCal at T = 0˚C P_max = 4.59 mW (for a single mm2 pixel)

  11. Layers 2 & 10 of BeamCal at T = 15˚C P_max = 23.16 mW (for a single mm2 pixel)

  12. Power Drawn(Watts) of BeamCal collapsed 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)

  13. Total Power Draw

  14. Further investigations • Power draw maps can provide an input to design a system that avoids thermal runaway • Three other types of Si sensors (NF, PC, NC) have been irradiated to 300 MRads and the PF sensor to 500 MRads, which await damage measurements

  15. Bhabha Events • Issue: • Degenerate SUSY has background from two-photon events • Hope to reduce by detecting scattered primary e+/- in BeamCal and vetoing the event • If a SUSY event is overlain with a Bhabha event with an e+/- in the BeamCal, we will reject SUSY •  What is the rate of Bhabha events with e+/- in the Beamcal? • Bhabhas with virtuality-Q2 > 1 GeV (~ 4 mrad scatter) available at • with cross section  = 278 nb •  Raw rate of 0.76 Bhabha events per beam crossing ftp://ftp-lcd.slac.stanford.edu/ilc4/DBD/ILC500/bhabha_inclusive/stdhep/bhabha_inclusive*.stdhep

  16. Bhabha Event Classes Bhabha events fall into three classes Miss-Miss: Both e-/e+ miss the BeamCal; not problematic Hit-Hit: Both e-/e+ hit the BeamCal; should be identifiable with kinematics (need to demonstrate) Hit-Miss: One and only one of e-/e+ hit the BeamCal; background to two-photon rejection. Naively, 11% of SUSY events would be rejected due to Hit-Miss events, plus whatever fraction of the 48% of Hit-Hit crossings aren’t clearly identified based on e+/- kinematics.

  17. Hit/Hit events: e+-e- angular correlation “Type a quote here.” –Johnny Appleseed

  18. After cut of  < 1.0 Mrad, 33% of Hit/Hit Bhabhas remain (16% of crossings). Can possibly eliminate with energy cut (need to balance against two-photon and SUSY events)

  19. For Hit/Miss events, there may well be useful kinematic handles… but again, need to compare to two-photon and SUSY signal distributions

  20. Degenerate SUSY and Electron Tagging • SUSY has a cosmologically-motivated corner where a weakly-coupled particle (stau) is nearly generate with the LSP (0) • We have generated events at Ecm= 500 GeV with • M~= (100, 150, 250) GeV • ~-0splittings of (20.0, 12.7, 8.0, 5.0, 3.2, 2.0) GeV • Concern: Two-photon events provide • greater and greater background as • splitting decreases. • Hope: We can tag the scattered electron or • Positron in the Beamcal and veto. • But: If photons are from Beamstrahlung, electron/positron do not get a pTkick (is this right Tim?)

  21. Two-Photon Event Rate • Thanks to Tim Barklow, SLAC, we have ~107 generator-level two photons events, with electron/positron photon fluxes given by the Weizsacker-Williams approximation (W) and/or the Beamstrahlung distribution (B). • Events have been generated down to M = 300 MeV. • For this phase space, the ILC event rate is approximately 1.2 events/pulse. • 1 year of  events corresponds to (1.2)x(2650)x(5)x(107) events, or about 1.6x1011 events per year. • How do we contend with such a large number of events in our simulation studies?

  22. Two-Photon Approach • Convenient data storage in 2016: ~5 TB • Tim Barklow: • 5 TB is about 109 generated (not simulated!) events • 1011 events requires 4000 2-day jobs • Jan Strube: Don’t worry about CPU (really?) •  Proposed approach: • Do study at generator-level only. • Except: Full BeamCal simulation to determine electron-ID efficiency as a function of (E,r,) of electron. Parameterize with 3-D function and use in generator-level analysis • Devise “online cuts” applied at generation that reduce data sample by x100 (can this be done?) • Store resulting 109 events and complete analysis “offline”

  23. In Search Of: “Online Selection” • For now, looking at three observables: • M: mass of  system • S: Sum of magnitudes of pT for all particles in  system • V: Magnitude of vector sum of pT for particles in  system • Each of these is done both for McTruth as well as “reconstructed” detector proxy • Detector Proxy: Particles (charged ot neutral) detected if • No neutrinos • |cos()| < 0.9

  24. ISO “Online Selection”:  Mass (M) 0 Mass 2 GeV Splitting SUSY Signal; ~ Mass = 150 GeV Two-photon background Seems like a clean cut, but what is seen in the “detector”?

  25. “Detected”  Mass (M) 0 Mass SUSY Signal; ~ Mass = 150 GeV Two-photon background For 2 GeV splitting, even a cut of 0.5 MeV removes some signal

  26. S Observable: “Detected” 0 Mass SUSY Signal; ~ Mass = 150 GeV Two-photon background Fairly promising as well; but is it independent of M?

  27. V Observable: “Detected” 0 Mass Two-photon background SUSY Signal; ~ Mass = 150 GeV Not as promising; looks better for “true”, but even for Vtrue = 0, reconstructed V has significant overlap with SUSY signal (save for “offline” part of study?)

  28. Cut flow for S, M Distributions • News is not the best: • S and M observables very correlated • 3% loss of signal (at 2 GeV!) reduces background by only ~2/3 • Other discriminating variables?

  29. IR Layout Low-Z Mask M1 Mask BeamCal L* 31

  30. BeamCal Face Geometry Options • “plugged” • Wedge cutout • Circle cutout “wedge” cutout Plug Insert plug here “circle” cutout 32

  31. 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 33 Tom Markiewicz, SLAC

  32. 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. 34

  33. 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 35

  34. Nominal IR Geometry Occupancy Distributions (Barrel) Stacked histograms! 15 x 15 1 BX 30 x 30 5 BX x10-3 x10-3 36

  35. Nominal IR Geometry Occupancy Distributions (Endcap) Stacked histograms! 15 x 15 1 BX 30 x 30 5 BX x10-3 x10-3 37

  36. 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 38

  37. Barrel: Mean Occupancy vs. Phi x10-4 30 x 30 5 BX Occupancy roughly constant in phi 39

  38. Endcap: Mean Occupancy vs. R 30 x 30 5 BX Occupancy varies drammatically with radius; dominated by inner radii 40

  39. BeamCal Efficiency L* Dependence Base Small L* larger L* consistently displays higher efficiency 41

  40. BeamCal Efficiency L* Dependence Factorized Difference is largely geometric 42

  41. BeamCal Efficiency and the Anti-DiD Field Noticeable but small effect 43

  42. Forward EMCal Readout Buffer Depth Study • Issue: • EMCal read out by KPiX chip • KPiX chip has limited number of buffers (currently 4). This limits the number of hits that can be recorded per pulse train • Study backgrounds to determine if buffer depth needs to be extended, and if so, by how much.

  43. Event Types Included BhaBha Pair Backgrounds Low Cross-section (down to 0.1 events/train) Gamma-gamma to Hadron 46

  44. Hit Number Distribution (Integrated over a full train) 47

  45. Fraction of Hits Lost During the Train as a Function of KPiX Buffer Depth 48

  46. But: Are there “Hot Spots”? Fractions of Hits Lost, By EMCal Layer 49

  47. Fractions of Hits Lost, By Radius (Distance from Beam Line) 50

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