FASTION L. Mether, G. Rumolo ABP-CWG meeting 24.11.2016

Outline Introduction Physics model Code implementation, documentation, license Typical usage Performance Future plans

FASTION Code for modeling the fast beam-ion instability (FBII) in electron machines Developed at CERN, by G. Rumolo, based on HEADTAIL for e-cloud Used for studying FBII in linear CLIC structures Recent developments to apply to synchrotrons

Physics model Linear transport of bunch train through machine lattice Linac: 4D transport, energy incremented Synchrotron: 6D with linear bucket, radiation damping (S. White)

Physics model Linear transport of bunch train through machine lattice Linac: 4D transport, energy incremented Synchrotron: 6D with linear bucket, radiation damping (S. White) The machine lattice is represented by interaction points (IP) In each IP, interaction between ions and bunch train is modeled

Ion-beam interaction Residual gas ionization Represent ions generated over s distance between adjacent IP’s Generated through scattering ionization, or field ionization, if bunch e-field exceeds threshold value Multiple gas species with different pressures and ionization cross-sections supported Give velocity kick Generate ions Introduce bunch

Ion-beam interaction E-field calculation Ion and beam fields calculated separately using the same grid Averaged Green’s function PIC solver, open boundary, FFT convolution Accurate for rectangular (non-square) grid cells Dual-grid solver: fine grid around beam, coarse grid for ions over larger area Velocity kicks applied according to e-field of oppositely charged particles Calculate kick Generate ions Introduce bunch

Ion-beam interaction E-field calculation Ion and beam fields calculated separately using the same grid Averaged Green’s function PIC solver, open boundary, FFT convolution Accurate for rectangular (non-square) grid cells Dual-grid solver: fine grid around beam, coarse grid for ions over larger area Velocity kicks applied according to e-field of oppositely charged particles Calculate kick Generate ions Introduce bunch Transport bunch

Ion-beam interaction E-field calculation Ion and beam fields calculated separately using the same grid Averaged Green’s function PIC solver, open boundary, FFT convolution Accurate for rectangular (non-square) grid cells Dual-grid solver: fine grid around beam, coarse grid for ions over larger area Velocity kicks applied according to e-field of oppositely charged particles Calculate kick Ions drift Generate ions Introduce bunch Transport bunch

Ion-beam interaction E-field calculation Ion and beam fields calculated separately using the same grid Averaged Green’s function PIC solver, open boundary, FFT convolution Accurate for rectangular (non-square) grid cells Dual-grid solver: fine grid around beam, coarse grid for ions over larger area Velocity kicks applied according to e-field of oppositely charged particles Calculate kick Ions drift Generate ions Introduce bunch Transport bunch

Code implementation Written in C (developed from HEADTAIL), with a few routines in F77 Tested only on Linux, compiled with gcc compiler The PIC solver uses FFTW Repository: https://github.com/lmether/FASTION Input: config file with beam and vacuum parameters, twiss file for lattice Documentation: minimal overview of input & output License: GPL3 Users: CERN (1), light sources: CESR-TA, APS, ESRF, INDUS

FASTION with PyECLOUD + PyHEADTAIL FASTION is based on HEADTAIL for e-cloud Recently HEADTAIL has been redesigned  PyHEADTAIL Also for electron cloud build-up: ECLOUD  PyECLOUD Decision to incorporate FASTION functionality into PyECLOUD – PyHEADTAIL Benefit from more modern and flexible design Shared workload of maintenance and development Access to features already implemented in PyECLOUD/PyHEADTAIL: PIC solvers with boundary for complex beam chamber profiles (PyPIC) Ion self space charge Magnetic fields Bunch slices Chromaticity Transverse feedback coupled for e-cloud instability studies

FASTION with PyECLOUD + PyHEADTAIL FASTION simulations with PyECLOUD-PyHEADTAIL have been implemented and tested Suitable for simulations in synchrotrons Currently only single residual gas species with scattering ionization PyECLOUD Calculate kick Ions drift Generate ions PyHEADTAIL PyHEADTAIL Introduce bunch Transport bunch

Benchmark study for CLIC damping ring Bunch train initialized identically in FASTION and PyEC-PyHT Machine lattice divided in 677 interaction points ~ 60 cm long Residual gas: water, A = 18 Pressure 20 nTorr Track over 1 turn Bunch train centroids after 1 turn Instability in vertical plane

Benchmark study for CLIC damping ring Bunch train initialized identically in FASTION and PyEC-PyHT Machine lattice divided in 677 interaction points ~ 60 cm long Residual gas: water, A = 18 Pressure 20 nTorr Track over 1 turn Centroid of last bunch along turn Good agreement between FASTION and PyECLOUD-PyHEADTAIL

Typical use case FASTION simulations are used to estimate necessary vacuum and possibly other requirements to avoid FBII Scans over residual gas composition and pressure, initial seeds Relevant beam parameters: intensity, beam size, bunch spacing, train length Several hundred to a few thousand simulations for a full study Use at CERN In the past applied to linear CLIC structures: main linac, main transfer line Currently: CLIC damping ring (DR) Future studies: CLIC structures after re-baselining, FCC-ee CLIC Main Linac

Computational requirements & performance Typical parameters for CLIC studies (convergence studies on-going) 312 bunches of 104 MP’s 500 ion MP’s/bunch  on average about 7.5 × 104 ion MP’s PIC grid size: 250×250 For LINAC high resolution is necessary  dual grid + larger grid size For DR ideally simulate at least a damping time: τ = 2 ms ~ 1400 turns lsbatch suitable for LINAC simulations, but not really for DR Computation time LINAC Damping ring IP’s 1 2000 260 1400 * 260 FASTION 5 s 5 h 20 min 20 days PyEC-PyHT 7 s - 30 min 30 days

Parallelization with PyPARIS Parallelization layer for PyECLOUD-PyHEADTAIL e-cloud simulations (G. Iadarola) Here applied to FASTION type simulation with PyECLOUD-PyHEADTAIL Machine lattice divided over processors Bunch train tracked through the full part of each process bunch-by-bunch All bunches collected on master at end of every turn 1 2 3 4 5 6 7

Parallelization with PyPARIS Define speed-up for Nproc processors, in terms of time for one turn Tturn Theoretical maximum S = Nproc Estimated maximum, taking into account waiting time at beginning and end of turn Measured on 12-core machine (LIU-PS-GPU) Test case with 64 bunches With ~8 cores: 5-6 minutes/turn 5-6 days/damping time

Summary & Outlook Currently two tools for FASTION simulations: FASTION Suitable e.g. for CLIC linac: requires field ionization, run-time not too long PyECLOUD-PyHEADTAIL Suitable for synchrotrons: synchrotron motion, feedback, parallelization, etc. Gas ionization should be generalized to multiple species Could be extended also with field ionization, to cover linac case Hardware for parallel simulations needed Available manpower main question Past few years, a fraction of 1 person Future? Certainly simulations studies are needed at least

References G. Rumolo and D. Schulte,“Fast ion instability in the CLIC transfer line and main linac”, in Proc. 11th European Particle Accelerator Conf. (EPAC’08), Genoa, Italy, Aug. 2008, pp. 655-–657. G. Rumolo and D. Schulte, “Update on fast ion instability simulations for the CLIC main linac”, in Proc. 23rd Particle Accelerator Conf. (PAC’09), Vancouver, Canada, May 2009, pp. 4658–4660. J.-B. Jeanneret, G. Rumolo, and D. Schulte, “Vacuum specifications for the CLIC main linac”, in Proc. 1st Int. Particle Accelerator Conf. (IPAC’10), Kyoto, Japan, 2010, pp. 3401– 3403. A. Oeftiger and G. Rumolo, “Fast beam-ion instabilities in CLIC main linac: vacuum specifications”, CERN, Geneva, Switzerland, Rep. CERN-OPEN-2011-050, Nov. 2011. L. Mether, G. Iadarola and G. Rumolo, “Numerical modeling of fast beam ion instabilities”, Proc. HB2016, Malmö, Sweden, Jul. 2016.