ECMbias in the presence of Beamstrahlung Arik Florimonte, UCSC Mike Woods, SLAC WORKSHOP  Machine-Detector Interface  at the International Linear Collider Jan. 6-8, 2005 SLAC M. Woods, SLAC MDI Workshop @ SLAC

Wakefields, Disruption and y-z Kink instability Linac wakefields generate “banana” beam distortions (larger for NLC than for TESLA) NLC example TESLA example Disruption parameter is ratio of bunch length to focal length: Disruption Parameter NLC-500 TESLA-500 Dx 0.16 0.23 Dy 13.1 25.3 (larger for TESLA than for NLC) M. Woods, SLAC MDI Workshop @ SLAC

Summary of ECM Bias studies w/ Beamstrahlung OFF Wakefields + Disruption Y-Z Kink instability E-Spread + E-Z correlation + Y-Z Kink instability ECM Bias E1 and E2 are beam energies measured by the energy spectrometers. (ISR and beamstrahlung are turned off for this study.) Summary of ECMbias LC Machine Design <ECMbias> (Dy = 0) s(ECMbias) Max(ECMbias) vary Dy, hy WARM-500 +520 ppm 170 ppm +1000 ppm COLD-500 +50 ppm 30 ppm +250 ppm M. Woods, SLAC MDI Workshop @ SLAC

Summary of ECMbias NLC TESLA NLC’ LC Machine Design <ECMbias> (Dy = 0) s(ECMbias) Max(ECMbias) vary Dy, hy WARM-500 +520 ppm 170 ppm +1000 ppm COLD-500 +50 ppm 30 ppm +250 ppm NLC'-500 0 ppm 10 ppm M. Woods, SLAC MDI Workshop @ SLAC

Definition of ECMbias (Beamsstrahlung OFF) E1 and E2 are beam energies measured by the energy spectrometers. (ISR and beamstrahlung are turned off for this study.) Definition of ECMbias (Beamsstrahlung ON) ECM for NLC-500 Vary cutoff energy from 480-495 GeV M. Woods, SLAC MDI Workshop @ SLAC

M. Woods, SLAC MDI Workshop @ SLAC

ECM Bias versus Vertical Offset of Colliding Beams M. Woods, SLAC MDI Workshop @ SLAC

Tails are similar in both E1+E2 and Study of distributions for i) ECM (cannot measure this) ii) E1-E2 (closely related to Bhabha acolinearity) NLC NLC w/ random-ordered energy NLC NLC w/ random-ordered energy Negligible difference in 2 distributions Clear difference in 2 distributions NLC NLC w/ random-ordered energy Tails are similar in both E1+E2 and E1-E2 distributions NLC NLC w/ random-ordered energy M. Woods, SLAC MDI Workshop @ SLAC

Tails are similar in both E1+E2 and Study of distributions for i) ECM (cannot measure this) ii) E1-E2 (closely related to Bhabha acolinearity) TESLA TESLA w/ random- ordered energy TESLA TESLA w/ random- ordered energy Clear difference in 2 distributions Negligible difference in 2 distributions TESLA TESLA w/ random-ordered energy Tails are similar in both E1+E2 and E1-E2 distributions TESLA TESLA w/ random-ordered energy M. Woods, SLAC MDI Workshop @ SLAC

Study of distributions for i) ECM (cannot measure this) ii) E1-E2 (closely related to Bhabha acolinearity) NLC’ NLC’ w/ random-ordered energy NLC’ NLC’ w/ random-ordered energy Clear difference in 2 distributions Competing/cancelling ECM bias contributions NLC’ NLC’ w/ random-ordered energy Tails are similar in both E1+E2 and E1-E2 distributions NLC’ NLC’ w/ random-ordered energy M. Woods, SLAC MDI Workshop @ SLAC

Summary of ECMbias without Beamsstrahlung LC Machine Design <ECMbias> (Dy = 0) s(ECMbias) Max(ECMbias) vary Dy, hy WARM-500 +520 ppm 170 ppm +1000 ppm COLD-500 +50 ppm 30 ppm +250 ppm NLC'-500 0 ppm 20 ppm <50 ppm Summary of ECMbias in presence of Beamsstrahlung LC Machine Design <ECMbias> (Dy = 0) s(ECMbias) Max(ECMbias) vary Dy, hy WARM-500 +960 ppm 150 ppm + 1120 ppm COLD-500 +150 ppm 30 ppm +350 ppm NLC'-500 ~0 ppm 20 ppm <50 ppm → Energy spectrometers and Bhabha acolinearity alone are not sufficient to correct for this bias. Need beam dynamics modeling and other input from annihilation data, disrupted energy measurements, … M. Woods, SLAC MDI Workshop @ SLAC