1. VP 26.MAR.09 V. Previtali CERN & EPFL R. Assmann, S. Redaelli, CERN I. Yazynin, IHEP CC09 - 26 March 2009 CERN Simulations for Crystal (UA9)

2. VP 26.MAR.00 Outline UA9 experiment: the simulation settings –Optics and layout –Collimator database –Initial particle distribution Impact parameter: a critical input for our simulations. Impacting angle: Expected incoming angles versus crystal acceptance Simulation outcome: –Crystal routine –Colltrack results Global inefficiency Beam loss maps Sensitive elements in the ring Conclusions

3. VP 26.MAR.00 Outline UA9 experiment: the simulation settings –Optics and layout –Collimator database –Initial particle distribution Impact parameter: a critical input for our simulations. Impacting angle: Expected incoming angles versus crystal acceptance Simulation outcome: –Crystal routine –Colltrack results Global inefficiency Beam loss maps Sensitive elements in the ring Conclusions

4. VP 26.MAR.00 SPS Crystal experiment: Layout & Optics Crystal W absorber

5. VP 26.MAR.00 SPS experiment the main elements Roman Pots: –0.75 mm Cu represent roman pot scattering –Aperture 6 sigma + 1 mm Detector region: - 3 to 5 Si detector, length 300  m - transversal window (Steel); length 2x 200  m Dead region, 500 um, length 2x 200 um (Steel) Border: 150  m Al, length 3 cm Detector region: 664 - 882  m Dead region: 370  m Border region: 1.16 cm Represented in code by equivalent thickness in Cu

6. VP 26.MAR.00 SPS experiment the main elements Crystal –Si crystal, orientation 110 –150 µrad of total bending angle –Possibility to add amorphous layer (today presenting results with no amorphous layer) –Aperture 6 sigma Collimator –W absorber –0.60 m long –Aperture 6 sigma + 1 mm

7. VP 26.MAR.00 Outline UA9 experiment: the simulation settings –Optics and layout –Collimator database –Initial particle distribution Impact parameter: a critical input for our simulations. Impacting angle: Expected incoming angles versus crystal acceptance Simulation outcome: –Crystal routine –Colltrack results Global inefficiency Beam loss maps Sensitive elements in the ring Conclusions

8. VP 26.MAR.00 The particle initial distribution Once the optics and the layout is defined, we have to decide the particle initial distribution for our simulations. The impact parameter is a critical input for our simulations What is a “realistic” impact parameter for our simulations? Two ways to investigate it: 1.Include diffusion in Sixtrack 2.Write a “fast code” in order to understand the initial distribution of particle on the crystal

9. VP 26.MAR.00 The particle initial distribution Much faster! Once the optics and the layout is defined, we have to decide the particle initial distribution for our simulations. The impact parameter is a critical input for our simulations What is a “realistic” impact parameter for our simulations? Two ways to investigate it: 1.Include diffusion in Sixtrack 2.Write a “fast code” in order to understand the initial distribution of particle on the crystal

10. VP 26.MAR.00 Impact parameter/angle studies code description Purpose: study the variation of the particle “first impact” distribution on the crystal versus different emittance growth rates Write a quick code, which simulates the diffusion of the particles and records the impacting position and angle when a particle hits the crystal for the first time. Both betatron and synchrotron motions are taken into account Assumptions: –Only two dimensions: horizontal and longitudinal –The machine is perfectly linear –Qs and Qx do not vary with the particle amplitude/energy –The optical functions ,  do not vary with the particle amplitude/energy –Only transverse emittance growth is considered –The emittance growth is simulated by a random kick, given to all the particles each turn. Remember:

11. VP 26.MAR.00 For UA9 it is foreseen to increase artificially the beam diffusion by the mean of a kicker. White noise generator Maximum applied voltage 300 V Beta at the kicker beta location= 72.8 m Typical kick: 25 nrad Equivalent emittance growth rate :10 -9 m rad/sec ( ) Impact parameter/angle studies rms kick values k is the kick U the applied voltage  the relativistic facto E 0 the proton rest mass l,d length and distance of the plates

12. VP 26.MAR.00 In amplitude space (a s, a  ) the crystal is described by a line: aa asas CRYSTAL All the particles are generated here (Gaussian distribution), they cannot hit the crystal if the diffusion is zero. Impact parameter/angle studies initial particle distribution

13. VP 26.MAR.00 Impact parameter/angle studies initial particle distribution In amplitude space (a s, a  ) the crystal is described by a line: aa asas CRYSTAL n  cut Usually a “cut” is applied to speed up simulations (n  cut=4.5 ) All the particles are generated here (Gaussian distribution), they cannot hit the crystal if the diffusion is zero.

14. VP 26.MAR.00 Impact parameter/angle studies Impact parameter distribution Distribution of the impact parameter for different emittance growth rate values All the curves follow an exponential law

15. VP 26.MAR.00 Impact parameter/angle studies Impact parameter distribution Distribution of the impact parameter for different emittance growth rate values All the curves follow an exponential law

16. VP 26.MAR.00 In detail: the first impact distribution for the expected emittance growth The particle distribution has been fit with an exponential: Typical impact parameter  x ~ 13 µm Impact parameter/angle studies Impact parameter distribution

17. VP 26.MAR.00 Rms impact parameter versus emittance growth rate SPS case: ~3  m per turn diffusion LHC RANGE: ~5 nm per turn diffusion

18. VP 26.MAR.00 Impact parameter/angle studies Impacting angle distribution Distribution of the impacting angles for different emittance growth rate values Design impacting angle

19. VP 26.MAR.00 What is happening? (Impact parameter) -The distribution is asymmetrical (especially for larger d  /dt) -For different values of emittance growth, both the peak value and the FWHM value change In detail: the first impact distribution for the expected emittance growth Peak value: 145.13 µrad Angular spread: 8 µrad Inside the channeling acceptance! 120 GeV ~ 30 µrad 270 GeV ~20 µrad

20. VP 26.MAR.00 Outline UA9 experiment: the simulation settings –Optics and layout –Collimator database –Initial particle distribution Impact parameter: a critical input for our simulations. Impacting angle: Expected incoming angles versus crystal acceptance Simulation outcome: –Crystal routine –Colltrack results Global inefficiency Beam loss maps Sensitive elements in the ring Conclusions

21. VP 26.MAR.00 Expected Crystal Effects Each kick corresponds an amplitude increase and a phase shift: These quantities will determine the particle dynamics after the interaction with the crystal. What is the characteristic kick for each process? In theory we know… 0.29

22. VP 26.MAR.00 Effect of crystal described by physics cross-sections. Monte-Carlo simulation based on probabilities. Every interaction can be different! Particles of one bunch may have different processes based on their entry condition (offset, angle, energy). Amorphous crystal orientation Channeling crystal orientation Volume Reflection crystal orientation Expected Crystal Effects Probability [a.u.]

23. VP 26.MAR.00 Outline UA9 experiment: the simulation settings –Optics and layout –Collimator database –Initial particle distribution Impact parameter: a critical input for our simulations. Impacting angle: Expected incoming angles versus crystal acceptance Simulation outcome: –Crystal routine –Colltrack results Global inefficiency Beam loss maps Sensitive elements in the ring Conclusions

24. VP 26.MAR.00 What’s the output –Global inefficiency –Distribution of losses around ring –Histogram at the different elements Colltrack/6track simulations N part (n  )/N part_abs Particle tracks compared with aperture:10 cm accuracy! We can have the losses at the sensitive elements in the ring versus the crystal orientation

25. VP 26.MAR.00 Colltrack/6track: Simulation Scenarios Different cases presented today (more done): For each case crystal tilt varied from -250 to 100  rad. 50K protons with controlled impact parameter. Tracked up to 1000 turns. Detailed aperture model to locate losses with 10cm spatial resolution.

26. VP 26.MAR.00 Global Inefficiency No significant changes when adding amorphous layer or adding diffusion for global inefficiency!? 20% leakage 0% leakage best case Channeling Volume reflection Amorphous (at 14  )

27. VP 26.MAR.00 Outline UA9 experiment: the simulation settings –Optics and layout –Collimator database –Initial particle distribution Impact parameter: a critical input for our simulations. Impacting angle: Expected incoming angles versus crystal acceptance Simulation outcome: –Crystal routine –Colltrack results Global inefficiency Beam loss maps Sensitive elements in the ring Conclusions

28. VP 26.MAR.00 Local Beam Loss vs Global Efficiency Remember: LHC problem is local loss of protons after collimation regions in super-conducting magnets. What matters, are losses in magnets far downstream of collimators, crystals, etc. We want to measure beam loss distributions after crystals and compare with predictions for cleaning and collimation for magnets. Was done in SPS for LHC prototype collimator in 2004 and 2007. Reference paper: –“Comparison between measured and simulated beam loss patterns in the CERN SPS.” S. Redaelli, G. Arduini, R. Assmann, G. Robert-Demolaize (CERN). CERN-LHC- PROJECT-REPORT-938. Results show power of beam loss measurements (BLM) in the SPS and cross-checking with beam loss simulations (Sixtrack with collimator routines). Tracking codes fully qualified by beam tests.

29. VP 26.MAR.00 Where are leaking protons lost? Movie of beam loss vs crystal tilt Local inefficiency Losses on crystal, TAL and RP’s Losses on ring aperture

30. VP 26.MAR.00 Local inefficiency Peak Loss Amorphous Peak Loss Channeling Losses on crystal, TAL and RP’s Losses on ring aperture Factor ~20 improvement predicted Where are leaking protons lost? Movie of beam loss vs crystal tilt

31. VP 26.MAR.00 Sixtrack results (Preliminary) The factor 20 improvement is confirmed Up to now: linear machine, no energy spread Much higher statistic (5 million particles - 1000 turns) Colltrack results are reproduced Volume reflection case Channeling case

32. VP 26.MAR.00 Sixtrack results (Preliminary) The factor 20 improvement is confirmed LHC goal can only be reached with multi stage conventional cleaning downstream?! Up to now: linear machine, no energy spread Much higher statistic (5 million particles - 1000 turns) Colltrack results are reproduced Lhc design goal Volume reflection case Channeling case

33. VP 26.MAR.00 Outline UA9 experiment: the simulation settings –Optics and layout –Collimator database –Initial particle distribution Impact parameter: a critical input for our simulations. Impacting angle: Expected incoming angles versus crystal acceptance Simulation outcome: –Crystal routine –Colltrack results Global inefficiency Beam loss maps Sensitive elements in the ring Conclusions

34. VP 26.MAR.00 Looking Element by Element Previous results show SPS loss maps along the accelerator length. Simulations allow to consider losses separately for each element in the model. Next slides: –Show number of inelastic interactions (losses) at each element integrated over the full length of the element. –Plot this versus the orientation of the crystal. –Shows the number of local interactions in the various crystal regimes. Each inelastic interaction induces a particle shower. –Could be used to analyze local losses for specific magnets in more detail (e.g. including installation of additional BLM’s, possibly LHC- type as used for SPS collimator tests).

35. VP 26.MAR.00 1)Inelastic interactions in crystal Case no amorphous layer, diffusion

36. VP 26.MAR.00 4) Inelastic interactions in TAL Case no amorphous layer, diffusion 73 m downstream of crystal

37. VP 26.MAR.00 2) Inelastic interactions in bend MBA52030 Case no amorphous layer, diffusion 72 m downstream of crystal

38. VP 26.MAR.00 3) Inelastic interactions in quad QD52110 Case no amorphous layer, diffusion 99 m downstream of crystal

39. VP 26.MAR.00 5) Inelastic interactions in aperture element Case no amorphous layer, diffusion 420 m downstream of crystal

40. VP 26.MAR.00 Conclusions Beam loss maps will provide a unique method to validate collimation simulations and measurements (as shown for SPS tests of LHC collimators). This relies on distributed beam loss measurement systems as they exist in SPS and Tevatron. The LHC state-of-the-art codes for massive tracking have been adapted to include crystal effects. Detailed loss predictions have been prepared for the SPS all around the ring, including magnet losses. Measurements for every crystal orientation can be compared to the predictions. Element by element predictions allow focusing on critical elements, maybe equipping them with additional beam loss monitors. Work is progressing with full 6D tracking and improving models. Up to now Sixtrack is confirming the Colltrack results (but less cases run)

41. VP 26.MAR.00 Thanks In strict casual (dis)order Chiara bracco, Tatiana Pieloni, Steve Peggs, Werner Herr, Thomas Weiler, Giovanni Rumolo, Guido Sterbini, Emanuele Laface…

42. VP 26.MAR.00 Measurement Approach for CRYSTAL Use the benchmarking method as used for LHC collimators and beam loss simulations in the SPS also for crystal collimation studies. Approach: –For each crystal and beam setup simulate the losses around the full SPS ring. –For every crystal and beam setup measure the losses around the full SPS ring. –Compare measurement and simulation to demonstrate reduction of beam losses in magnets with a crystal. –Successful benchmarking in the SPS will then verify predictions of cleaning efficiency with crystals for the LHC (not reported here but existing). –Use same method also for benchmarking in Tevatron crystal experiments. Next slides: Report loss predictions for SPS with crystals.

43. VP 26.MAR.00 Outline Motivations and goals UA9 experiment: the simulation settings –Optics and layout –Collimator database –Initial particle distribution Impact parameter: a critical input for Sixtrack simulations. Impacting angle: Expected incoming angles versus crystal acceptance Simulation outcome: –Crystal routine –Colltrack/sixtrack(?) results Global inefficiency Beam loss maps Sensitive elements in the ring Conclusions

44. VP 26.MAR.00 Motivation and goals Crystal collimation might be a way to improve cleaning efficiency. Studies in BE/ABP group and the LHC collimation project to assess achievable performance in LHC and analyze SPS & Tevatron tests. Use the same state-of-the-art beam simulations as used for the LHC design and SPS beam tests for LHC collimators: direct prediction of performance change with crystals! Work so far: –Conceptual studies of crystal collimation. –Work with I. Yazinin on crystal simulation routine (phase space match, amorphous layer, general debugging). –Implementation of crystal simulation routine into standard LHC tracking tools for collimation (COLLTRACK operational and Sixtrack ongoing). –Simulations on LHC and SPS with local loss maps and efficiency. Discuss SPS simulations today.

45. VP 26.MAR.00 Impact parameter/angle studies understanding the single particle Maximum impact parameter Synchrotron phase Particle position turn (illustrative example)

46. VP 26.MAR.00 Impact parameter/angle studies understanding the single particle For a single particle is possible to predict the maximum impact and the typical synchrotron phase. Dependence on the emittance growth rate!!! turn Particle position Low emittance growth rate:  ->2  (or  is D x 0 (illustrative example)