1. Benchmarking simulations and observations at the LHC Octavio Domínguez Acknowledgments: G. Arduini, G. Bregliozzi, E. Métral, G. Rumolo, D. Schulte and F. Zimmermann Isola d’Elba, Italy – 6 June 2012

2. O. Domínguez - ECLOUD’12 Workshop – 6 June 2012 Outline  Observations - Description of the problem  Method  Results  Conclusions

3. O. Domínguez - ECLOUD’12 Workshop – 6 June 2012 Outline  Observations - Description of the problem  Method  Results  Conclusions

4. O. Domínguez - ECLOUD’12 Workshop – 6 June 2012 Observations Pressure rises were the first ECE observed in the LHC with 150 and 75 ns Beam 1 Beam 2 No pressure increase Pressure increase 150 ns - 450 GeV G. Bregliozzi

5. O. Domínguez - ECLOUD’12 Workshop – 6 June 2012 Observations Pressure rises were the first ECE observed in the LHC with 150 and 75 ns No electron cloud monitors are placed at the LHC

6. O. Domínguez - ECLOUD’12 Workshop – 6 June 2012 Observations Pressure rises were the first ECE observed in the LHC with 150 and 75 ns No electron cloud monitors are placed at the LHC For the benchmarking we focus on pressure gauges located in warm-warm transitions: 7 m NEG coating SEY estimated by the vacuum colleagues: ~ 1.6 – 1.9 [1] [1] Ø 80 mm StSt – Cu coated

7. O. Domínguez - ECLOUD’12 Workshop – 6 June 2012 Pressure rises were the first ECE observed in the LHC with 150 and 75 ns No electron cloud monitors are placed at the LHC For the benchmarking we focus on pressure gauges located in warm-warm transitions We count on 4 parameters in our simulations: Observations   max : Maximum secondary electron yield   max : Electrons’ energy at which the  max is reached  R: Reflection probability for low energy electrons  P: Pressure rise due to e - cloud

8. O. Domínguez - ECLOUD’12 Workshop – 6 June 2012 Outline  Observations - Description of the problem  Method  Results  Conclusions

9. O. Domínguez - ECLOUD’12 Workshop – 6 June 2012 Method What we measure What we can get from simulations We consider pressure ratios between different beam configurations in order to get rid of all unknowns based on a paper by D. Schulte [2][2]

10. O. Domínguez - ECLOUD’12 Workshop – 6 June 2012 Method p y >10 eV Done for the SPS in 2004 with an electron cloud monitor

11. O. Domínguez - ECLOUD’12 Workshop – 6 June 2012 Method We don’t have EC monitors at the LHC We are facing a four-parameter problem:  We want to infer the three main surface parameters (  max,  max and R )  At injection energy (450 GeV) the primary electrons come from gas ionization, so the pressure of the residual gas, P, plays an essential role We proceed as follows: 1)We fix two of the parameters, namely the pressure and  max  Pressure: We use the final stable pressure for each configuration to take into account the multiturn nature of the pressure evolution in a circular machine   max : We have been using 230 eV as a tentative value, which yield good results, but a thorough study on the effect of this parameter is foreseen

12. O. Domínguez - ECLOUD’12 Workshop – 6 June 2012 Method We don’t have EC monitors at the LHC We are facing a four-parameter problem:  We want to infer the three main surface parameters (  max,  max and R )  At injection energy (450 GeV) the primary electrons come from gas ionization, so the pressure of the residual gas, P, plays an essential role We proceed as follows: 2) We simulate the electron cloud build up for different bunch configurations, scanning the other two parameters,  max and R, in steps of 0.1 and 0.05 respectively (smaller steps introduce statistical noise)

13. O. Domínguez - ECLOUD’12 Workshop – 6 June 2012 Method We don’t have EC monitors at the LHC We are facing a four-parameter problem:  We want to infer the three main surface parameters (  max,  max and R )  At injection energy (450 GeV) the primary electrons come from gas ionization, so the pressure of the residual gas, P, plays an essential role We proceed as follows: 3) For each beam configuration we plot the simulated electron flux  i above a 2D grid spanned by  max and R

14. O. Domínguez - ECLOUD’12 Workshop – 6 June 2012 Method We don’t have EC monitors at the LHC We are facing a four-parameter problem:  We want to infer the three main surface parameters (  max,  max and R )  At injection energy (450 GeV) the primary electrons come from gas ionization, so the pressure of the residual gas, P, plays an essential role We proceed as follows: 4) We fit the flux simulated on the grid to a third order polynomial and then form the ratio of simulated fluxes (that is, dividing the polynomials) for two different bunch configurations [the fluxes and not their ratio are fitted in order to suppress the effect of statistical fluctuations].

15. O. Domínguez - ECLOUD’12 Workshop – 6 June 2012 Method We don’t have EC monitors at the LHC We are facing a four-parameter problem:  We want to infer the three main surface parameters (  max,  max and R )  At injection energy (450 GeV) the primary electrons come from gas ionization, so the pressure of the residual gas, P, plays an essential role We proceed as follows: 5) Comparing the latter ratio with the experimental ratio of measured pressure increases yields a curve in the  max -R plane. Different configurations yield different curves in that plane.

16. O. Domínguez - ECLOUD’12 Workshop – 6 June 2012 Method We don’t have EC monitors at the LHC We are facing a four-parameter problem:  We want to infer the three main surface parameters (  max,  max and R )  At injection energy (450 GeV) the primary electrons come from gas ionization, so the pressure of the residual gas, P, plays an essential role We proceed as follows: 6) If the measurements contain sufficient information and the simulation model is reasonably accurate we expect to obtain a unique intersection between lines corresponding to different bunch configurations. This crossing point then defines the solution for  max and R.

17. O. Domínguez - ECLOUD’12 Workshop – 6 June 2012 Outline  Observations - Description of the problem  Method  Results  Conclusions

18. O. Domínguez - ECLOUD’12 Workshop – 6 June 2012 Results 50 ns bunch spacing 36-bunch trains 1 st experiment: varying train spacing 2 nd experiment: varying the # of trains 6 April 2011 (Beginning of the scrubbing run) 6  s 11.5  s 4  s 2  s 2.125  s In agreement with vacuum colleagues estimations

19. O. Domínguez - ECLOUD’12 Workshop – 6 June 2012 Results 10 April 2011 (End of the scrubbing run) 50 ns bunch spacing 36-bunch double trains (36b + 225 ns + 36b) Experiment: varying the # of trains 4.85  s 225 ns

20. O. Domínguez - ECLOUD’12 Workshop – 6 June 2012 Results 19 May 2011 (1 st injection test with triple trains) 50 ns bunch spacing 36-bunch triple trains (36b + 225 ns + 36b + 225 ns + 36b) Experiment: varying the # of trains 925 ns 225 ns

21. O. Domínguez - ECLOUD’12 Workshop – 6 June 2012 Results 25 October 2011 25 ns bunch spacing 72-bunch trains Experiment: varying the # of trains 4  s 16  s 3  s 2  s  max = 260 eV

22. O. Domínguez - ECLOUD’12 Workshop – 6 June 2012 Results Summary

23. O. Domínguez - ECLOUD’12 Workshop – 6 June 2012 Outline  Observations - Description of the problem  Method  Results  Conclusions

24. O. Domínguez - ECLOUD’12 Workshop – 6 June 2012 Conclusions  A new method to monitor the LHC surface conditioning due to electron cloud by benchmarking simulations against experimental results is under development  The observable considered is the  P resulting from the electron cloud (  P ∝  )  Benchmarking the ratios of experimental pressures and of simulated electron fluxes for different beam configurations, we can pin down the value of the  max as well as R (assuming a certain  max and taking into account measured pressure)  Despite the lack of measurements+accuracy and the need of further analysis, this method provides so far clear evidence for surface conditioning, from an initial  max of about 1.9 down to about 1.35, for R ≈ 0.2 THANK YOU FOR YOUR ATTENTION

25. O. Domínguez - ECLOUD’12 Workshop – 6 June 2012 References [1] G. Bregliozzi, E-cloud vacuum observations and forecast in the LHC, CERN-GSI E-cloud workshop 2011, CERN, Geneva (Switzerland)G. Bregliozzi, E-cloud vacuum observations and forecast in the LHC, CERN-GSI E-cloud workshop 2011, CERN, Geneva (Switzerland) [2] D. Schulte et al., “Electron cloud measurements in the SPS in 2004,” Proc. Particle Accelerator Conference (PAC 05), Knoxville, Tennessee, 16-20 May 2005, pp 1371, 2005D. Schulte et al., “Electron cloud measurements in the SPS in 2004,” Proc. Particle Accelerator Conference (PAC 05), Knoxville, Tennessee, 16-20 May 2005, pp 1371, 2005

26. O. Domínguez - ECLOUD’12 Workshop – 6 June 2012 Spare slides 1 R. Cimino, I. Collins et al. C. Yin Valgren Cu as received:  max ≈ 160 eV Cu fully scrubbed:  max ≈ 250 eV There is an important shift during the scrubbing process towards higher values Cu as received:  max ≈ 330 eV The during the scrubbing process is very little

27. O. Domínguez - ECLOUD’12 Workshop – 6 June 2012 Spare slides 2 25 October 2011 25 ns bunch spacing 72-bunch trains Experiment: varying the # of trains 4  s 16  s 3  s 2  s  max = 230 eV

28. O. Domínguez - ECLOUD’12 Workshop – 6 June 2012 Spare slides 3 10 April 19 May