Using Tune Shifts to Evaluate
Electron Cloud Effects on Beam
Dynamics at CesrTA
Jennifer Chu
Mentors: Dr. David Kreinick and Dr. Gerry Dugan
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Outline
• Review of Electron Clouds and Tune Shifts
• Simulations of New Data
• Varying the Simulation Parameters
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Electron Clouds
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ILC will collide electrons and positrons
Accelerating charges radiate
Photons knock electrons off walls of beampipe
Photoelectrons are accelerated by beam and
knock off more electrons, forming a cloud
• Electrons in the cloud are attracted to positive
beams
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Tune Shifts
• Beams are displaced
from nominal path
• Tune (Q): number of
oscillations of a particle
about nominal path, per
turn around the ring
• Tune shift (ΔQ):
difference in tune
caused by electric field
of electron cloud
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Qy = 9.52
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Taking Data
• CesrTA is used to
measure tune shifts
• Beams are set into
oscillation
• BPMs measure the
position for 2048 turns
• Fourier transform is
used to calculate tune
shifts
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POSINST
• POSINST is a simulation code used to model
the electron cloud effects
• Simulations are run for different values for
each of five parameters which describe the
physics of electron cloud generation
• Simulations are compared to data to test
accuracy of the model
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Comparing Data to Simulations
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Goals
• We want to find the optimal set of parameters
that most accurately models electron clouds
• The simulation can then be used to predict
the behavior of electron clouds in damping
rings of future linear colliders
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Submitting Jobs to the Queue
• Simulations were
run on Cornell’s
batch nodes
• Each job is only
allowed 48 hours
I monopolized the queues for the summer:
of CPU time
87 data sets
• I wrote code to
x 5 simulation parameters
parallel process the
x 2 for x, y tune shifts
simulations to get
x 6 jobs per submission
----------------------------------more statistics
> 5000 total jobs
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Calculating Tune Shifts
• I used Mathematica to post-process the
results of POSINST to calculate the tune shifts
• I superimposed the tune shifts from multiple
simulations onto plots of the data for
comparison
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June 2011 Coherent Tune Shift Data
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2.085 GeV e+: 20 x 0.5 mA
2.085 GeV e+: 45 x 0.5, 1.0, 1.5, 2.0 mA
4.00 GeV e+: 20 x 0.2, 0.4, 0.6, 0.8, 1.0, 1.2, 1.4, 1.6, 1.8, 2.0 mA
4.00 GeV e+: 45 x 0.2, 0.4, 0.6, 0.8, 1.0, 1.2 mA
5.3 GeV e+: 20 x 0.5, 1.0, 2.0 mA
5.3 GeV e-: 20 x 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 mA
5.3 GeV e+: 45 x 0.2, 0.4, 0.6, 0.8, 1.0, 1.2 mA
5.3 GeV e-: 45 x 0.2, 0.4, 0.6, 0.8, 1.0, 1.2, 1.4, 1.6, 1.8, 2.0, 2.2, 2.4, 2.6 mA
Bunch spacing studies:
• 2.085 GeV e-: 30 x 0.2, 0.4, 0.6, 0.8, 1.0, 1.2 mA for 12, 16, 20 ns spacing
• 2.085 GeV e-: 45 x 0.2, 0.4, 0.6, 0.8, 1.0, 1.2 mA for 4, 8, 12 ns spacing
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2.1 GeV
4.0 GeV
5.3 GeV
0.50 mA/bunch
0.40 mA/bunch
0.50 mA/bunch
1.00 mA/bunch
1.00 mA/bunch
1.00 mA/bunch
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Simulation Parameters
• Parameters describe the physics of electron
cloud generation
• When a radiated photon from the beam
knocks into the wall of the beampipe,
photoelectrons are generated
• (1) Quantum Efficiency: number of electrons
generated for every photon
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Secondary Emission
• Photoelectrons are
accelerated by the electric
field of the beam and
continue to produce more
electrons
• (2) Secondary Emission
Yield (SEY): number of
secondary electrons
generated for every
primary electron
• (3) Energy at the SEY Peak
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Types of Secondary Electrons
• When a photoelectron hits
a wall of the vacuum
chamber, it can:
1. Bounce off (elastic)
2. Interact with material
(rediffused)
3. Knock off electrons in
material (true)
• (4) Fraction of Secondaries
that are Rediffused
• (5) Fraction of Secondaries
that are Elastic
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Sketch of the currents that are used
to define the different components
of secondary emission.
Figure taken from M. Furman and G.
Lambertson, “The electron-cloud
instability in the arcs of the PEP-II
positron ring”
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Varying the Simulation Parameters
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Summary
• Tune shifts are used to study electron clouds
• Simulations were run and compared to data
for all five parameters and all 77 new data sets
• Model seems to work reasonably well for a
variety of beam energies and bunch currents
• Finding the optimal parameters will allow the
model to be used for future linear colliders
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