1. Search for physics beyond the Standard Electroweak model with the WITCH experiment
Simon Van Gorp
PhD defense
28th of February, Leuven
Promotor: Prof. Dr. Nathal Severijns

2. Outline The WITCH experiment Motivation Status Overview
Simbuca, a Penning trap simulation package
Graphics card to calculate Coulomb interaction between the ions
Usage by other groups
First determination of a with the WITCH experiment
Data set
Reconstruction of the data
Results
Non-neutral plasma
Boundary with single particle regime
Energy distribution
Mass selectivity due to presence of an ion plasma
Summary and outlook
Simon Van Gorp
Thesis defense
28th of February, /30

3. Physics motivation Experimental limits [1]: |CS/CV| < 0.07
|CT/CA| < 0.09
=>Search for Scalar (or Tensor) Interactions
Prime candidate for WITCH is 35Ar
Low energy (several 100 eV)!
Need for scattering free source
[1]: Severijns, N., Beck, M., & Naviliat-Cuncic, O. (2006).Rev. Mod. Phys., 78(3), 991
Simon Van Gorp
Thesis defense
28th of February, /30

4. Overview of the WITCH setup
~7m
Simon Van Gorp
Thesis defense
28th of February, /30

5. Experimental setup Penning traps:
Cooler trap (He buffer gas 10-3 – 10-4 mbar)
excitations
Decay trap
Scattering free source
Retardation spectrometer [2] to measure the energy
Conversion of radial to axial energy
[2]: Lobashev, V. & Spivak, P. (1985). NIM A 240(2), 305 – 310
Simon Van Gorp
Thesis defense
28th of February, /30

6. Time situation PhD October 2007
35Cl contamination in the ISOLDE beam (ratio 25:1)
Charge-exchange in REXTRAP (t1/2=70 ms) and WITCH (t1/2=8 ms)
Unwanted electric discharges
November 2009
Still a remaining ionization that was not noticed before was solved by installation of a wire
Not covered in my thesis but in PhD thesis of Michael Tandecki
The goal is in sight
Measure a
Prepare the tools for analysis of a
Simon Van Gorp
Thesis defense
28th of February, /30

7. Outline The WITCH experiment Motivation Status Overview
Simbuca, a Penning trap simulation package
Graphics card to calculate Coulomb interaction between the ions
Usage by other groups
First determination of a with the WITCH experiment
Data set
Reconstruction of the data
Results
Non-neutral plasma
Boundary with single particle regime
Energy distribution
Mass selectivity due to presence of an ion plasma
Summary and outlook
Simon Van Gorp
Thesis defense
28th of February, /30

8. Simbuca
104 – 106 ions / trap cycle stored up to a few seconds in the decay trap.
Simulation time scales with O(N2) with N being the number of particles
Tree codes O(N log(N))
Scaled Coulomb approach
Novel approach by using a graphics card (GPU) instead of conventional CPU.
Simbuca code was build around this idea [3]
Complete, modular, simulation package
Different buffer gas routines and integrators
Importing realistic field maps
Made available for free [4]
[3]: Van Gorp et al. 2011) NIM A
[4]:
Simon Van Gorp
Thesis defense
28th of February, /30

9. Why a GPU? High parallelism due to parallel stream processors
SIMD structure (pipelining!)
Very fast floating point calculations
CUDA programming language
8 x 16 stream processors
≈ each comparable to one CPU
= Comparable with a factory assembly line with threads being the workers
Geforce 8800 GTX
Simon Van Gorp
Thesis defense
28th of February, /30

10. Chamomile scheme
Calculating gravitational interactions on a Graphics Card via the Chamomile scheme from Hamada and Iitaka (in 2007) [5].
i-particles piece available for each ‘assembly line’
j-particles piece presents itself sequentially to each line
force is the output of each line
[5]: T. Hamada and T. Iitaka, arXiv.org:astro-ph/ , 2007
Simon Van Gorp
Thesis defense
28th of February, /30

11. GPU vs CPU
GPU blows the CPU away. The effect becomes more visible with even more
particles simulated.
Simulated is a quadrupole excitation for 100 ms with buffer gas. This takes 3 days
with a GPU compared to 3-4 years with a CPU!
GPU improvement factor
CPU and GPU simulation time
Simon Van Gorp
Thesis defense
28th of February, /30

12. Simbuca: usage by other groups
WITCH
Behavior of large ion clouds
Energy and position distribution
Smiletrap (Stockholm)
Highly charged ions
Cooling processes
ISOLTRAP (CERN)
In-trap decay [6]
Investigate the influence of Coulomb repulsion between ions in a Penning trap
ISOLTRAP (Greifswald)
isobaric buncher, mass separation and negative mass effect [7]
CLIC accelerator (CERN)
Simulate bunches of the beam
Piperade (Orsay and MPI Heidelberg)
Simulate mass separation of ion clouds
[6]: A. Herlert, S. Van Gorp et al. Recoil-ion trapping for precision mass measurements, to be published
[7]: Wolf, R et al. (2011). Hyperfine Interactions, 199, 115–122
Simon Van Gorp
Thesis defense
28th of February, /30

13. Outline The WITCH experiment Motivation Status Overview
Simbuca, a Penning trap simulation package
Graphics card to calculate Coulomb interaction between the ions
Usage by other groups
First determination of a with the WITCH experiment
Data set
Reconstruction of the data
Results
Non-neutral plasma
Boundary with single particle regime
Energy distribution
Mass selectivity due to presence of an ion plasma
Summary and outlook
Simon Van Gorp
Thesis defense
28th of February, /30

14. Data analysis: 3 steps
1. reconstruct the experimentally obtained spectrum from the data
2. Simulate the experimentally obtained spectrum, taking into account the experimental conditions
3. Fit the two spectra to extract the b-n angular correlation coefficient a
Simon Van Gorp
Thesis defense
28th of February, /30

15. Experimental conditions June 2011
ISOLDE target broke few days before the actual run. Replaced with used target => low 35Ar yield (5.105 compared to in yield book)
HV electrode could not be operated as intended. Non-optimal focus of the electrodes caused a loss off 40%
Losses in the decay-trap
The red curve (better settings)
shows a more constant behavior
-> A low statistics experiment
(~2600 ions/trap load).
Simon Van Gorp
Thesis defense
28th of February, /30

16. Measurements Reconstruction via: Subtraction Regression analysis
Overshoot peak
Fitting the data
0.5 s in the cooler trap. Afterwards transfer to the decay-trap.
Simon Van Gorp
Thesis defense
28th of February, /30

17. Normalization via regression analysis
Scale factor f =3.540(3)
Difference of measurements with and without retardation voltage applied.
Correct the data for 35Ar half-life and losses in the decay-trap.
Simon Van Gorp
Thesis defense
28th of February, /30

18. Simulations:
Compare obtained spectra with simulated spectra. Therefore:
1. Simbuca simulates the ion cloud in the decay-trap.
2. Ion-cloud parameters are fed to a tracking simulation (SimWITCH).
Comsol multiphysics program is used to extract electric field maps given the electrode voltages
Magnetic field maps from the magnet manufacturer
Buffer gas collisions and excitations are handled by Simbuca
Simon Van Gorp
Thesis defense
28th of February, /30

19. Simulations: Simbuca
Due to limited time the traps could not be fully optimized:
The transfer time was set to 32.5 us instead of (ideal) 38.5 us
mean energy of 4.5 eV (instead of 0.2 eV)
ions positions in the decay-trap is 15 mm lower than the center
Simon Van Gorp
Thesis defense
28th of February, /30

20. Simulations: SimWITCH (1)
Simulations for
All retardation voltages (0V, 150V, 250V, 350V, 600V)
All charge states (1+,2+,3+,4+,5+)
1+ : 75(1)%
2+ : 17.3(4)%
3+ : 5.7(2)%
4+ : 1.7(2)%
5+ : < 1 %
As measured with LPC trap [8]
-> Fit the data with a linear combination of a=1 and a=-1 to obtain the final result for the beta-neutrino angular correlation factor a.
[8] C. Couratin et al. , to be published
Simon Van Gorp
Thesis defense
28th of February, /30

21. Simulations: SimWITCH (2)
Ions are not properly focused on the MCP, due to the lower HV settings
applied. The applied voltages are not high enough to pull the ions of the
magnetic field lines.
Input spectra 2+ 1+
Ions are lost on SPDRIF01 electrode.
The higher the charge-state of the daughter ion the better the focus.
Simon Van Gorp
Thesis defense
28th of February, /30

22. Extracting a
a=-1
a=1
The preliminary result from the analysis yields a = 1.12 (33)stat c2/n= 0.64
SM value of a = (16).
Not including actual experimental conditions yields a = 2.62 (42) !! =>
This stresses the importance of simulations!!
Simon Van Gorp
Thesis defense
28th of February, /30

23. Error budget Systematic error estimated to be maximum 10%
Possible improvements on the statistics:
Possible to reduce the statistical error from 30 % to below 0.5 %
Effect
Improvement factor
ISOLDE target eff. 10
Measurement time 50
Measurement cycle 2
Electrode focus eff.
Tuning in B-field 4
Total:
8000
Simon Van Gorp
Thesis defense
28th of February, /30

24. Outline The WITCH experiment Motivation Status Overview
Simbuca, a Penning trap simulation package
Graphics card to calculate Coulomb interaction between the ions
Usage by other groups
First determination of a with the WITCH experiment
Data set
Reconstruction of the data
Results
Non-neutral plasma
Boundary with single particle regime
Energy distribution
Mass selectivity due to presence of an ion plasma
Summary and outlook
Simon Van Gorp
Thesis defense
28th of February, /30

25. Non-neutral plasmas
When trapping a large amount of ions, the cloud’s own electric field will create an E x B drift force for the ions with
Indications that around 104 ions the ion motion behaves like a non-neutral plasma
Simon Van Gorp
Thesis defense
28th of February, /30

26. Boundary plasma regime
single particle
Single particle regime
Non-neutral plasma regime
non-neutral plasma
When storing around 5000 and ions they start to behave as a non-neutral plasma (in good agreement with [9])
Energy broadening due to Coulomb repulsion
Resistance to excitations due to electric field of the ion cloud
Simon Van Gorp
[9]: Nikolaev et al. (2007). RCM, 21(22), 3527–3546
Thesis defense
28th of February, /30

27. Energy distribution due to Coulomb repulsion
1 accumulation accumulations
experiment
Comparison between simulations and experiments
Energy increase due to mutual Coulomb repulsion between the ions
Large influence in any recoil energy distribution measurement
simulations
Simon Van Gorp
Thesis defense
28th of February, /30

28. Multiple ion species trapped
90% 85Rb
10% 87Rb
25 ms Dipole excitation -> de center all ions
75 ms Quadrupole excitation -> mass selective centering
wc-10 Hz wc wc+10 Hz
When multiple ion species are trapped a more negative excitation frequency is favored [10,11]
There is a large resistance to the applied excitation due to shielding of Ecloud No
Coulomb
With
#Particles x2
[10]: Herlert, A., et al. (2011). Hyp. Int., 199, 211–220
[11]: Mitchell, D. W. & Smith, R. D. (1995). Phys. Rev. E, 52, 4366–4386
Simon Van Gorp
Thesis defense
28th of February, /30

29. Summary and Outlook Summary
The versatile Penning trap simulation package, Simbuca, is the first application that uses a GPU to calculate the Coulomb interaction between ions in the Penning trap.
An ion cloud in a Penning trap of more than 104 ions behaves like a non-neutral plasma which has effect on the measured recoil energy distribution
First analysis and determination of a on the decay of 35Ar with WITCH
Statistical precision of 0.5% is possible
Outlook
Simbuca will continue to be used by WITCH
and other experiments
GPU simulations is a new field that is gaining interest
Investigate the properties of the non-neutral plasma
in the WITCH Penning traps
New experiments in October and November were taken with enough statistics for a determination of a with a statistical precision below 5%
=> New phase for WITCH: i.e. extensive investigation of systematic effects
Simon Van Gorp
Thesis defense
28th of February, /30

30. Thank you for your attention

31. Simon Van Gorp – WITCH collaboration meeting – 21 February 2012
Simulation validity
Due to the low amount of ions the position distribution is not comparable but the radial distribution is being used.
Simon Van Gorp – WITCH collaboration meeting – 21 February 2012

32. Chamomile scheme: practical usage
Function provided by Hamada and Iitaka [2]:
Gravitational force ≈ Coulomb Force
Conversion coefficient:
Needed: bit linux
- NVIDIA Graphics Card that supports CUDA
- CUDA environment v3.x
Not needed: - CUDA knowledge
- …
[2]: , 2007
32/21
Simon Van Gorp - Scientific meeting

33. Simon Van Gorp - Scientific meeting - 16.02.2011
GPU vs CPU
GPU blows the CPU away. The effect becomes more visible with even more
particles simulated.
Simulating 4000 ions with a quadrupole excitation for 100ms with buffer gas. Takes 3 days
with a GPU compared to 3-4 years with a CPU!
GPU improvement factor
CPU and GPU simulation time
33/21
Simon Van Gorp - Scientific meeting

34. Simon Van Gorp - Scientific meeting - 16.02.2011
Simbuca overview
Simbuca is a modular Penning Trap simulation package that can be applied to simulate:
Charged particles (+/- /N charges)
Under the influence of B and E fields
With realistic buffer gas collisions
Coulomb interaction included
Can run on GPU and CPU
Simulation of Ion Motion in a Penning trap with realistic BUffer gas collisions and Coulomb interaction using A Graphics Card.
34/21
Simon Van Gorp - Scientific meeting

35. Proof of recoil ions
Guassian bell shape indicates the observation of recoil ions
Position distribution shows the presence
of recoil ions and missing counts along the Y-axis.

36. Data analysis: 3 steps
1. reconstruct the experimentally obtained spectrum from the data
2. Simulate the experimentally obtained spectrum, taking into account the experimental conditions
(3.) verify simulations with experimental observations
The observed beam spot
The energy distribution of the ions in the trap
Ratio b`s/ions from the PhD
4. Fit the two spectra to extract the b-n angular correlation coefficient a

37. (less good) normalizations (2,3)
Data set 2: normalization on the overshoot peak
Data set 3: normalization via a fit function of the data
Simon Van Gorp – WITCH collaboration meeting – 21 February 2012

38. Single ion species trapped
Plot centered 133Cs ions vs. duration of the quadrupole excitation
Losses due to Coulomb effects
Resonant excitation frequency tends to be more positive (as in Ref. [x])
Simon Van Gorp
[x]: F. Ames et al. (2005). NIM A, 538, 17–32
Thesis defense