1. CLIC choke-mode structure Hao Zha 2013-Oct-09

2. Outlines 1. Choke-mode structure design; 2. Optimization on RF parameters; 3. Experiments. 4. Future plan

3. Overview of CDS design NameDescriptionParametersManufactory & Measurement CDS-AOriginal design; regular choke; Prototype cells made in CERN CDS-BHOM tuned choke; Wakefield suppression Improve; No CDS-CNew choke design, Optimized on wakefield suppression; Prototype cells (aluminium) made in Tsinghua. Wakefield tested in AWA. CDS-DNew choke design; Optimized on RF parameters. No

4. Equivalent circuit model For accelerating mode, ϕ 3 =π/2, so z=∞. Then It is fully reflected by choke. Some HOMs could be also fully (or mostly) reflected.

5. Thin-neck choke design Zc a Short load LaLa section a Plane C Zc b =K*Zc a LbLb section b zaza zbzb z3z3 Plane DPlane A Plane D Plane C S 12 K1234 f236GHz49GHz60GHz69GHz The joint planes (Plane A and Plane D) are equivalent as impedance transformers Purpose of thin-neck design: (1) Increase the 2 nd fully reflected frequency (2) Reduce reactance of HOMs

6. Matching step Purpose of matching step design: (1) Reduce reactance of some HOMs. (2) Compensate residual reflection from the load, possible to design loads with lower price.

7. Dipole detuning (~16GHz)(~18GHz) c1 c2 Purpose of dipole detuning: (1) Detune lower band HOMs (one cell). (2) Provide weak detuning between cells (like DDS).

8. Wakefield simulation results W ⊥ (s=0.15m) WDS5 CDS-A20~30 +Thin-neck10~17 +Matching step7~10 +Dipole detuning (CDS-C)5~6 CDSWDS FcFc 11 F rms 45 F worst 2520

9. RF parameters of CDS-C HFSS simulation results: CDS-CCLIC-G Iris aperture(mm)3.15, 2.35 Q(Cu)4895, 53855538, 5738 Shunt impedance(MΩ/m)59, 8381, 103 Group velocity(%c)1.38, 0.731.65, 0.83 Max E-field(MV/m)246235 Sc (MW/mm^2)5.725.43 Pulse heating(K)23.247.9 Peak input power(MW)67.460.5 Filling time(ns)72.462.2 RF-beam efficiency24.2%28.1%

10. Optimization on RF parameters Optimization target : RF-beam efficiency (η), Max surface field (Es, Sc, Hs). Geometry sizes of irises are the focus points. Input: Geometry sizes of irises Output: η, Es, Sc, Hs Optimization

11. Genetic algorithm Lots of geometry variables => Huge searching space. Genetic algorithm => find optimum solutions more quickly (actually much more quickly). Use C++ to implement it. Fitness η, Es, Sc Individuals Gene: Geometry Born children (with gene mutation) Higher fitness, more children Calculation Discarded Join in low High Random initialization Here we use a simplified way to calculated RF parameters.

12. Optimization results (1) Max population: 400~800 Birth rate: 4/iteration Iteration: 800 Searching time: 2.5×10 6 ; CDS-CCDS-DCLIC-G Iris aperture(mm)3.15, 2.35 3.49, 2.50 3.15, 2.35 Shunt impedance(MΩ/m) 59, 8353, 7481, 103 Group velocity(%c)1.38, 0.73 2.00, 0.75 1.65, 0.83 Bunch population (10 9 )3.724.503.72 Max E-field(MV/m)246223235 Sc (MW/mm^2)5.725.175.45 Pulse heating(K)23.222.047.9 Peak input power(MW)67.479.360.2 Filling time(ns)72.460.862.2 RF-beam efficiency24.2%26.0%28.1%

13. Optimization results (2) Wakefield suppression: 4V/pC/m/mm F c =1.01; F rms =3.8; F worst =35 CDS-C CDS-D

14. Radial line experiments Target: (1) To verify HOMs absorption (S12) in choke-structures; (2) To test the RF load; Reflection S11 can be tested on VNA after calibration (“multi-short load calibration”) To VNA

15. Radial line experiments

16. Reflection of RF load Results are promising;

17. HOMs absorption in choke

18. Layout of AWA G1: Photo cathode + Faraday cup. To study the phonemes of laser trigged RF break down. G2: Witness beam line, Mg cathode + gun + 1*linac, 15MeV, max 100nC. G3: Drive beam line, Semiconductor cathode + gun + 6*linac, 75MeV; >=100nC, can produce bunch train.

19. Set up experiments (1) GUNLINAC Chamber ICT Spectro meter 20GHz oscilloscope, 0~20GHz mixer 1#2#3#4# oscilloscope With loadWithout load

20. Set up experiments (2) Chamber YAG ICT Bellows YAG Bellows Be windows ： 50um thickness ； For 14MeV electron beam, ~30% (calculated by Fluka) of the beam can pass it without any scattering. After optimized on beam dynamics: 1nC Beam size: ~0.7m, 5nC Beam size: ~1.6m, Beam aperture: 5.5mm

21. Set up experiments (3)

22. Wakefield measurement results (1) L0L0 10GHz CABLEAttenuatio n 1#20 dB 2#20 dB 3#0 dB 4#0 dB

23. Spectrum of signal in cable 4# Unidentified dipole mode? It may be the 36GHz – 2*10GHz = 16GHz Fundamental mode 12GHz Dipole mode ~16GHz Unidentified dipole mode? Dipole mode ~19GHz Dipole mode ~23GHz Dipole mode ~28GHz

24. Wakefield measurement results (2) L0L0 No Mixer CABLEAttenuati on 1#30 dB 2#20 dB 3#10 dB 4#0 dB

25. Spectrum of signal in cable 3# Dipole mode at 16GHz and 19GHz Looks like the dipole mode at 50-22= 28GHz Fundamental modeUnidentified Q (@12GHz) = 160~400 Q (@16GHz) = 12.5 Q (@19GHz) = 15.3

26. Future plan Manufacturing & High power test; -Start manufacturing choke-mode cells, 6cells/24cells(Tsinghua); -Single choke-cell for high power test designed (Tsinghua & KEK); -Start to design the compact coupler for choke-mode (Tsinghua). Wakefield test with two beams; - Two beam line facility (AWA) Further optimization (geometry, load design);

27. Thank you!!

28. Multi-short calibration At least 3 different load is needed in the standard calibration Solve the Inconsistent equations to get more precise network parameters (Least square method). - y: reflection detected by network analyzer ; - x: reflection of radial line at plane A …

29. Genetic representation There are 3 selections for genetic representation. The second way has the best practical results. For the first and third selections, it is very difficult to put iris parameters of every cell into chromosomes. We just selected some cells (e.g. first, middle and last cell) as chromosome. linear fit Polynomial co- efficiency polynomial fit

30. Fitness function Early convergence is a big problem of GA: Better solution has more children, and soon it and its posterity will monopolize the whole world. Fitness = Performance – Competition

31. Reproduction Evolution will be aroused in the reproduction by two ways: Mutation; Crossover (not very suitable in our case). About mutation, we find this way of mutation has a better effect ： Sequential mutation (rather than randomly mutation) + Mutation step becomes gradually smaller (rather than constant)