Beam-Beam Simulations at MEIC Balša Terzić, Yuhong Zhang, Matthew Kramer, Colin Jarvis, Rui Li Jefferson Lab Ji Qiang LBNL EIC Collaboration Meeting, Catholic.

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Presentation transcript:

Beam-Beam Simulations at MEIC Balša Terzić, Yuhong Zhang, Matthew Kramer, Colin Jarvis, Rui Li Jefferson Lab Ji Qiang LBNL EIC Collaboration Meeting, Catholic University of America, July 29-31, 2010

Outline Overview of the MEIC Motivation for beam-beam simulations Beam-beam simulation model Code used in the simulations Scope of simulations Simulation results Future plans Summary

Overview of the MEIC Jefferson Lab has been pursuing design studies of an electron- ion collider for future nuclear physics research (2007 Long Range Plan, DOE/NSF Nuclear Science Advisory Committee) Based on CEBAF, the collider would provide collisions between polarized electrons and polarized light ions or unpolarized heavy ions at multiple interaction points (IP) Staged approach: Immediate goal: low-to-medium energy collider (MEIC) CM energy up to 51 GeV Future upgrade option: a high-energy collider CM energy 100 GeV or higher

Overview of the MEIC p-beam e-beam Beam EnergyGeV605 Collision frequencyMHz1497 Particles/bunch Beam currentA13 Energy spread RMS bunch lengthmm107.5 Horizontal emittance, norm.μmμm Vertical emittance, norm.μmμm Synchrotron tune Horizontal β*cm10 Vertical β*cm2 Distance from IP to front of 1 st FF quad m73.5 Vert. beam-bam tune shift/IP Proton beam Laslett tune shift0.07 Peak Lumi/IP, cm -2 s High luminosity achieved by: - high bunch repetition rate - high average current - short bunches - strong focusing at IP (small β*)

Motivation for Beam-Beam Simulations Key design MEIC parameters reside in an unexplored region for ion beams very small (cm or less) β* to squeeze transverse beam sizes to several μm at collision points moderate (50 to 100 mrad) crab crossing angle due to very high (0.5 to 1.5 GHz) bunch repetition (new for proton beams) Investigating the beam-beam effect becomes critically important as part of feasibility study of this conceptual design The sheer complexity of the problem requires us to rely on computer simulations for evaluating this non-linear collective effect Goals of numerical beam-beam simulations: Examine incoherent and coherent beam-beam effects under the nominal design parameters Characterize luminosity and operational sensitivity of design parameters Take into account coupling to single particle nonlinear dynamics in rings

Simulation Model Numerical beam-beam simulations can be divided into two parts: 1.Tracking of collision particles at IPs 2.Transporting beams through a collider ring Modeled differently to address different physics mechanisms and characteristic timescales In this talk, we focus on disruption of colliding beams by non- linear beam-beam kicks (study 1., and idealize 2.) Beam transport idealized by a linear map, synchrotron radiation damping and quantum fluctuations Strong-strong regime: both beams can be perturbed by the beam-beam kicks

Simulation Code We use BeamBeam3D code (LBNL) (SciDAC collaboration): Self-consistent, particle-in-cell Solves Poisson equation using shifted Green function method on a 3D mesh Massively parallelized Strong-strong or weak-strong mode In our present configuration, results converge for: 200,000 particles per bunch 64x128 transverse resolution, 20 longitudinal slices Simulation runs executed on both NERSC supercomputers and on JLab’s own cluster

Scope of Simulations Model new medium-energy parameter set for the MEIC Approximations/simplifications used: Linear map Chromatic optics effects not included Damping of e-beam through synchrotron radiation No damping in ion/p-beam Head-on collisions 1 IP Strong-strong (self-consistent, but slow) mode: Only study short-term dynamics – several damping times (1 damping time ~ 1500 turns ~ 5 ms)

Simulation Results We address the following issues: Search for a (near-)optimal working point Automated and systematic approach Dependence of beam luminosity on electron and ion beam currents Onset of coherent beam-beam instability

Searching For Optimal Working Point Using Evolutionary Algorithm Beam-beam effect and collider luminosity are sensitive to synchro- betatron resonances of the two colliding beams Careful selection of a tune working point is essential for stable operation of a collider as well as for achieving high luminosity Optimize a non-linear function using principles of natural selection, mutation and recombination (evolutionary algorithm) Objective function: collider’s luminosity Independent variables: betatron tunes for each beam (synchrotron tunes fixed for now; 4D problem) Subject to constraints (e.g., confine tunes to particular regions) Similar algorithm used to optimize photoinjector [Bazarov & Sinclair PR STAB, 8, , 2005; orig. ETH Zürich group] Probably the only non-linear search method that can work in a domain so violently fraught with resonances (very sharp peaks and valleys)

Searching For Optimal Working Point Using Evolutionary Algorithm Resonances occur when m x ν x + m y ν y + m s ν s = n m x, m y, m s and n are integers (m s =0 for now) Green lines: difference resonances (stable) Black lines: sum resonances (unstable) Restrict search to a group of small regions along diagonal devoid of black resonance lines Found an excellent working point near half-integer resonance (well-known empirically: PEP II, KEK-B…) e-beam: ν x = 0.53, ν y = , ν s = p-beam: ν x = , ν y = , ν s = Luminosity about 33% above design value in only ~300 simulations Main point: have a reliable and streamlined way to find optimal work point Gen 1 Gen 2Gen 3 Gen 4 Gen 5

Luminosity at the Optimal Work Point For the optimal working point found earlier, compute luminosity for a large number of turns (20,000 ~ 66 ms) (a few days on NERSC/JLab cluster) After an initial oscillation, the luminosity appears to settle (within a fraction of a damping time) at a value exceeding design luminosity It appears that the beams suffer reduction in beam transverse size at the IP, which yields luminosity in excess of the design value Detailed study of phase space is underway Main point: short-term stability is verified to within the limits of strong-strong code

Betatron Tune Footprint For the optimal working point found earlier, compute tunes for a subset of particles from each beam and see where they lie in relation to the resonant lines (up to 7 th order resonances plotted) Resonance lines up to 6th order plotted Tune footprint for both beams stays comfortably away from resonance lines Main point: for stability, the tune footprint of both beams must be away from low-order resonances

Dependence of Luminosity on Beam Current Near design beam current (up to ~2 times larger): linear dependence Far away from design current for proton beam: non-linear effects dominate Coherent beam-beam instability is not observed Main point: as beam current is increased, beam-beam effects do not limit beam stability linear non-linear

Future Plans Outstanding issues we will address in future simulations: Including non-linear dynamics in the collider rings: Non-linear optics Effect of synchrotron tune on beam-beam Chromatic effects Imperfect magnets Crab crossing (high integrated-voltage SRF cavities) Other collective phenomena: Damping due to electron cooling in ion/proton beams Space charge at very low energy (?) Long-term dynamics: use weak-strong simulations

Summary Beam-beam effects are critical for the MEIC We developed methodology to study beam-beam effects Used existing and developed new codes/methods Presented first results from numerical simulations Main point: beam-beam effects do not limit the capabilities of the MEIC Ultimate goal of beam-beam simulations: verify validity of MEIC design and optimize its performance

Backup Slides

Dependence of Effective Beam-Beam Tuneshift on Beam Current

Electron Beam Vary Electron X TuneVary Electron Y Tune Tune Scan

Vary Proton X TuneVary Proton Y Tune Proton Beam Tune Scan