1. GPT Simulations of the Ion Source Beam
Simon Jolly
Imperial College
FETS Meeting, 31/8/05

2. LEBT Optimisation
To effectively optimise LEBT, must have accurate model of beam at start of LEBT ie. at source extraction.
Various data on source beam:
Measurements of beam emittance 600mm downstream (DF) - use measured and simulated beam profiles.
Optimised emittance and beta functions from ISIS RFQ (APL).
MAFIA simulations of source output (DF).
Create optimised model based on this data…

3. Ion Source Measurements (1)
Measurements made 600mm downstream from Ion Source (DF):
Hrms = 0.92, Vrms = 1.01  mm mrad.
xtot = 90mm, x’tot = 110 mrad.
ytot = 110mm, y’tot = 155 mrad.
For GPT, use uniform x/x’ dist., quadratic y/y’ dist. (see next slides).
Run GPT simulation backwards to measure beam at ion source extraction.

4. Ion Source Measurements (2)
Horizontal and Vertical emittance measurements

5. Ion Source Measurements (3)
Horizontal emittance profiles X X’

6. Ion Source Measurements (4)
Horizontal emittance profiles X X’

7. Ion Source Measurements (5)
Vertical emittance profiles Y Y’

8. Ion Source Measurements (6)
Vertical emittance profiles Y Y’

9. Ion Source Reverse Sim. (1)
“Final” emittance profiles Y X

10. Ion Source Reverse Sim. (2)
“Initial” emittance profiles - no space charge Y X

11. Ion Source Reverse Sim. (3)
“Initial” emittance profiles - 10% space charge Y X

12. Ion Source Reverse Sim. (4)
“Initial” emittance profiles - 20% space charge Y X

13. Ion Source Reverse Sim. (5)
“Initial” emittance profiles - 30% space charge Y X

14. Ion Source Reverse Sim. (6)
“Initial” emittance profiles - 50% space charge Y X

15. Optimised ISIS Values (APL)
Fitted / functions and normalised RMS emittance:
Hrms = 0.76, Vrms = 1.23  mm mrad.
x = 1.53, y = 1.04.
x = -8.93, y = -6.6.
Gives the following beam parameters at ground plane:
xrms = 10.4 mm, x’rms = 8.5 mrad.
yrms = 10.9 mm, y’rms = 13.1 mrad.
Run GPT using various particle distributions and space charge.

16. GPT Simulation - APL (1)
Initial horizontal emittance: quadratic, uniform and gaussian distributions

17. GPT Simulation - APL (2)
Final horizontal emittance: quadratic, uniform and gaussian distributions; 90% space charge

18. GPT Simulation - APL (3)
Final horizontal emittance: quadratic distributions; 0, 50 and 90% space charge

19. GPT Simulation - APL (4)
Vertical beam trajectories, 0, 50 and 90% space charge; quadratic distribution

20. Results: Target Values
Ion Source measurements - 600mm (DF):
Hrms = 0.92, Vrms = 1.01  mm mrad.
xrms = 26.0 mm, x’rms = 32.0 mrad.
yrms = 24.6 mm, y’rms = 35.0 mrad.
Optimised ISIS Values - 0mm (APL):
Hrms = 0.76, Vrms = 1.23  mm mrad.
xrms = 10.4 mm, x’rms = 8.5 mrad.
yrms = 10.9 mm, y’rms = 13.1 mrad.

21. APL Results (600mm) S.C. xrms xrms’ yrms yrms’ xmax ymax xmax/xrms
ymax/yrms 0%
11.8
8.5
13.7
13.1
63.3
75.5
5.3
5.5
10%
14.1
12.6
15.9
16.9
71.0
83.1
5.0
5.2
20%
16.3
18.2
18.0
21.9
78.7
90.5
4.8
30%
18.3
23.8
20.0
27.1
86.0
97.6
4.7
4.9
40%
20.3
29.2
32.2
93.1
104.5
4.6
50%
22.3
34.4
37.1
99.9
111.2
4.5
60%
24.1
39.3
25.6
41.8
106.6
117.7
4.4
70%
25.9
44.0
27.4
46.4
113.1
124.1
80%
27.7
48.6
29.1
50.7
119.5
130.4
4.3
90%
29.4
52.9
30.8
55.0
125.7
136.5
100%
31.1
57.1
32.5
59.1
131.9
142.5
4.2

22. Ion Source Results (0mm)
S.C.
xrms
xrms’
yrms
yrms’
xmax
ymax
xmax/xrms
ymax/yrms 0%
7.3
32.0
4.7
26.2
4.4
5.5
10%
8.8
26.0
6.1
29.2
37.9
31.4
4.3
5.2
20%
10.2
20.6
7.4
24.0
43.6
36.4
4.9
30%
11.6
16.0
8.7
19.4
49.2
41.3
4.2
40%
13.0
12.0
10.0
15.5
54.7
46.0
4.6
50%
14.3
9.1
11.3
12.4
60.0
50.6
4.5
60%
7.9
12.6
10.4
65.2
55.1
70%
16.8
13.8
70.2
59.6
80%
18.0
11.0
15.0
11.1
75.1
63.9
90%
19.2
13.9
16.2
13.2
79.9
68.2
100%
20.3
17.0
17.3
15.8
84.7
72.3

23. Mafia Data Simulation
Input position & velocity data of 10,000 particles to GPT, generated from Mafia simulation (DF). X Y

24. Mafia Data Results (10% SC)X Y

25. Mafia Data Results (100% SC)X Y

26. Mafia Input Results (600mm)
S.C.
xrms
xrms’
yrms
yrms’
xmax
ymax
xmax/xrms
ymax/yrms
Initial
3.6
2.3
6.1
12.7
14.6
4.1
10%
9.5
16.2
12.6
21.3
37.9
48.6
4.0
3.8
30%
17.9
36.5
21.0
41.7
71.7
79.9
50%
24.7
51.9
27.9
57.1
99.0
105.8
70%
30.7
64.9
33.9
70.1
123.0
128.7
100%
38.7
81.6
41.9
86.8
154.7
159.3

27. Matlab Interpolation (1)
Need to produce input file for GPT from DF measured data. Start with raw data file (histogram data)…

28. Matlab Interpolation (2)
Convert histogram data into individual particle data: use random distribution of points for each phase space cell (increases emittance)…

29. Matlab Interpolation (3)
Reduce number of particles to 10,000 total to produce suitable number for GPT input…

30. Matlab Interpolation (4)
Reproduce histogram for beam distribution compare to real data. Data can now be input to GPT.

31. Matlab Interpolation (5)
Real data

32. Preliminary Results
Closest match to measured data using ISIS / functions with a quadratic particle distribution, 50% space charge.
Tracking measured data backwards gives reasonable match even though distributions are different - need to input real data, not approximate distributions.
More difficult to find match with Mafia data - initial beam much smaller than others.
New Matlab analysis functions match results from GPT.

33. Still to do…
Re-run measured data simulations using actual data, not GPT particle distributions.
Create custom particle distributions to read into GPT for a better match to measured data.