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EC Simulations for HL-HLC Beam Scenarios

EC Simulations for HL-HLC Beam Scenarios. C. M. Bhat ECLOUD Meeting CERN October 1, 2012. Motivation of the PS Expt. . Can Bunch lengthening be a viable e-cloud mitigation technique for the LHC or the HL-LHC ?

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EC Simulations for HL-HLC Beam Scenarios

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  1. EC Simulations for HL-HLC Beam Scenarios C. M. Bhat ECLOUD Meeting CERN October 1, 2012

  2. Motivation of the PS Expt. • Can Bunch lengthening be a viable e-cloud mitigation technique for the LHC or the HL-LHC? • PS studies undeniably proved that bunch profiles have significant effect on e-cloud growth. BSM50 mode gives rise to about a factor of two smaller e-cloud growth. Objective is to extend the studies to the LHC using HL-LHC beam parameters Simulations Only • ECLOUD and PyECLOUD C. M. Bhat

  3. Comparison between ECLOUD and PyECLOUD simulations Gaussian Bunches PyeCloud gives 5% smaller heat-load in arcs * * * * * * * * PyeCloud gives ~35% larger heat-load in arcs !?! C. M. Bhat

  4. Simulated Bunch Profiles (ESME) and Analytical form for WB • These bunch profiles are used to generate one SPS batch of injected beam to the LHC • 25 nsec filling pattern: 288 bunches with 200 nsec kicker gap between every 72 bunches • 50 nsec filling pattern: 144 bunches with 200 nsec kicker gap between every 36 bunches C. M. Bhat

  5. HL-LHC Beam Parameters C. M. Bhat

  6. Simulations with ECLOUD and PyECLOUD C. M. Bhat

  7. Average Heatload for the HLLHC beam scenarios PyECLOUD ECLOUD & PyECLOUD C. M. Bhat

  8. Conclusions • We find that changing the bunch profiles will keep EC growth nearly constant. So BSM is not going to help EC growth in the LHC. • However, foreseen use of second harmonic Landau cavity that would change bunch profiles (shorter or nearly flat bunches) and makes beam longitudinally more stable, will not pose any additional EC related problem in the LHC/HL-LHC. C. M. Bhat

  9. Comparison between ECLOUD and PyECLOUD simulations C. M. Bhat

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