pyecloud code and simulations g. iadarola, g. rumolo ice meeting 9 april 2012

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PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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Page 1: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

PyEcloud code and simulationsG. Iadarola, G. Rumolo

ICE meeting 9 April 2012

Page 2: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Outline

• A few basic concepts on e-cloud build-up

• PyEcloud: How do we simulate the e-cloud build-up

o Flow-chart

o MP size management

o Convergence and performances

• Overview of e-cloud studies for CERN accelerators:

o e-cloud studies for the PS and SPS

o e-cloud studies for the LHC

25ns observation benchmarking for the arcs

e-cloud build-up in in 800mm common pipe near IP2

Page 3: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Outline

• A few basic concepts on e-cloud build-up

• PyEcloud: How do we simulate the e-cloud build-up

o Flow-chart

o MP size management

o Convergence and performances

• Overview of e-cloud studies for CERN accelerators:

o e-cloud studies for the PS and SPS

o e-cloud studies for the LHC

25ns observation benchmarking for the arcs

e-cloud build-up in in 800mm common pipe near IP2

Page 4: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Secondary electron emission

e-

Page 5: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Secondary electron emission

e-

Page 6: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Secondary electron emission

Page 7: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Secondary electron emission

Page 8: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Secondary electron emission

Page 9: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Secondary electron emission

Page 10: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Secondary electron emission

Page 11: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Secondary electron emission

Page 12: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Secondary electron emission

The Secondary Electron Yield of the chamber’s surface is basically the ratio between

emitted and impacting electrons and is function of the energy of the primary

electron.

0 200 400 600 800 10000.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

Primary e- energy [eV]S

ec

on

da

ry E

lec

tro

n Y

ield

[S

EY

]

Page 13: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Secondary electron emission

The Secondary Electron Yield of the chamber’s surface is basically the ratio between

emitted and impacting electrons and is function of the energy of the primary

electron.

0 200 400 600 800 10000.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

Primary e- energy [eV]S

ec

on

da

ry E

lec

tro

n Y

ield

[S

EY

]

e- absorber

e- emitter

Page 14: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Seed mechanisms

• In proton accelerators the electron cloud is typically triggered by ionization of

residual gas that is present in the beam pipe.

• In the LHC (for E>1TeV) there are many electrons coming from photoelectric

emission due to synchrotron radiation

Page 15: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Electron cloud build-up

Beam pipe transverse cut

0 10 20 30 405

5.5

6

6.5

7

7.5

8

8.5

9x 10

9

Time [ns]N

um

ber

of

e- [

m-1

]

Page 16: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Beam pipe transverse cut

0 10 20 30 405

5.5

6

6.5

7

7.5

8

8.5

9x 10

9

Time [ns]N

um

ber

of

e- [

m-1

]

• During the bunch passage the electrons are accelerated by the beam “pinched”

at the center of the beam pipe

Electron cloud build-up

Page 17: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Beam pipe transverse cut

0 10 20 30 405

5.5

6

6.5

7

7.5

8

8.5

9x 10

9

Time [ns]N

um

ber

of

e- [

m-1

]

Electron cloud build-up

• During the bunch passage the electrons are accelerated by the beam “pinched”

at the center of the beam pipe

Page 18: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Beam pipe transverse cut

0 10 20 30 405

5.5

6

6.5

7

7.5

8

8.5

9x 10

9

Time [ns]N

um

ber

of

e- [

m-1

]

Electron cloud build-up

• During the bunch passage the electrons are accelerated by the beam “pinched”

at the center of the beam pipe

Page 19: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Beam pipe transverse cut

0 10 20 30 405

5.5

6

6.5

7

7.5

8

8.5

9x 10

9

Time [ns]N

um

ber

of

e- [

m-1

]

Electron cloud build-up

• During the bunch passage the electrons are accelerated by the beam “pinched”

at the center of the beam pipe

Page 20: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Beam pipe transverse cut

0 10 20 30 405

5.5

6

6.5

7

7.5

8

8.5

9x 10

9

Time [ns]N

um

ber

of

e- [

m-1

]

Electron cloud build-up

• After the bunch passage the electrons hit the chamber’s wall (with E~100eV)

• If the Secondary Electron Yield (SEY) of the surface is large enough, secondary

electrons can be generated and growth of the total number of electrons is

observed

Page 21: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Beam pipe transverse cut

0 10 20 30 405

5.5

6

6.5

7

7.5

8

8.5

9x 10

9

Time [ns]N

um

ber

of

e- [

m-1

]

Electron cloud build-up

• After the bunch passage the electrons hit the chamber’s wall (with E~100eV)

• If the Secondary Electron Yield (SEY) of the surface is large enough, secondary

electrons can be generated and growth of the total number of electrons is

observed

Page 22: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Beam pipe transverse cut

0 10 20 30 405

5.5

6

6.5

7

7.5

8

8.5

9x 10

9

Time [ns]N

um

ber

of

e- [

m-1

]

• After the bunch passage the electrons hit the chamber’s wall (with E~100eV)

• If the Secondary Electron Yield (SEY) of the surface is large enough, secondary

electrons can be generated and growth of the total number of electrons is

observed

Electron cloud build-up

Page 23: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Beam pipe transverse cut

0 10 20 30 405

5.5

6

6.5

7

7.5

8

8.5

9x 10

9

Time [ns]N

um

ber

of

e- [

m-1

]

Electron cloud build-up

• After the bunch passage the electrons hit the chamber’s wall (with E~100eV)

• If the Secondary Electron Yield (SEY) of the surface is large enough, secondary

electrons can be generated and growth of the total number of electrons is

observed

Page 24: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Beam pipe transverse cut

0 10 20 30 405

5.5

6

6.5

7

7.5

8

8.5

9x 10

9

Time [ns]N

um

ber

of

e- [

m-1

]

Electron cloud build-up

• After the bunch passage the electrons hit the chamber’s wall (with E~100eV)

• If the Secondary Electron Yield (SEY) of the surface is large enough, secondary

electrons can be generated and growth of the total number of electrons is

observed

Page 25: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Beam pipe transverse cut

0 10 20 30 405

5.5

6

6.5

7

7.5

8

8.5

9x 10

9

Time [ns]N

um

ber

of

e- [

m-1

]

Electron cloud build-up

• After the bunch passage the electrons hit the chamber’s wall (with E~100eV)

• If the Secondary Electron Yield (SEY) of the surface is large enough, secondary

electrons can be generated and growth of the total number of electrons is

observed

Page 26: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Beam pipe transverse cut

0 10 20 30 405

5.5

6

6.5

7

7.5

8

8.5

9x 10

9

Time [ns]N

um

ber

of

e- [

m-1

]

Electron cloud build-up

• After the bunch passage the electrons hit the chamber’s wall (with E~100eV)

• If the Secondary Electron Yield (SEY) of the surface is large enough, secondary

electrons can be generated and growth of the total number of electrons is

observed

Page 27: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Beam pipe transverse cut

0 10 20 30 405

5.5

6

6.5

7

7.5

8

8.5

9x 10

9

Time [ns]N

um

ber

of

e- [

m-1

]

Electron cloud build-up

• After the bunch passage the electrons hit the chamber’s wall (with E~100eV)

• If the Secondary Electron Yield (SEY) of the surface is large enough, secondary

electrons can be generated and growth of the total number of electrons is

observed

Page 28: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Beam pipe transverse cut

0 10 20 30 405

5.5

6

6.5

7

7.5

8

8.5

9x 10

9

Time [ns]N

um

ber

of

e- [

m-1

]

Electron cloud build-up

• After the bunch passage the electrons hit the chamber’s wall (with E~100eV)

• If the Secondary Electron Yield (SEY) of the surface is large enough, secondary

electrons can be generated and growth of the total number of electrons is

observed

Page 29: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Beam pipe transverse cut

0 10 20 30 405

5.5

6

6.5

7

7.5

8

8.5

9x 10

9

Time [ns]N

um

ber

of

e- [

m-1

]

Electron cloud build-up

• After the bunch passage the electrons hit the chamber’s wall (with E~100eV)

• If the Secondary Electron Yield (SEY) of the surface is large enough, secondary

electrons can be generated and growth of the total number of electrons is

observed

Page 30: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Beam pipe transverse cut

0 10 20 30 405

5.5

6

6.5

7

7.5

8

8.5

9x 10

9

Time [ns]N

um

ber

of

e- [

m-1

]

Electron cloud build-up

• After the bunch passage the electrons hit the chamber’s wall (with E~100eV)

• If the Secondary Electron Yield (SEY) of the surface is large enough, secondary

electrons can be generated and growth of the total number of electrons is

observed

Page 31: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Beam pipe transverse cut

0 10 20 30 405

5.5

6

6.5

7

7.5

8

8.5

9x 10

9

Time [ns]N

um

ber

of

e- [

m-1

]

Electron cloud build-up

• Secondary electrons are emitted with smaller energies (E~1eV) and, if they hit

the wall before the following bunch passage, they are absorbed without

generation of further secondaries

• Decay of the total number of electrons can be observed in this stage

Page 32: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Beam pipe transverse cut

0 10 20 30 405

5.5

6

6.5

7

7.5

8

8.5

9x 10

9

Time [ns]N

um

ber

of

e- [

m-1

]

Electron cloud build-up

• Secondary electrons are emitted with smaller energies (E~1eV) and, if they hit

the wall before the following bunch passage, they are absorbed without

generation of further secondaries

• Decay of the total number of electrons can be observed in this stage

Page 33: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Beam pipe transverse cut

0 10 20 30 405

5.5

6

6.5

7

7.5

8

8.5

9x 10

9

Time [ns]N

um

ber

of

e- [

m-1

]

Electron cloud build-up

• Secondary electrons are emitted with smaller energies (E~1eV) and, if they hit

the wall before the following bunch passage, they are absorbed without

generation of further secondaries

• Decay of the total number of electrons can be observed in this stage

Page 34: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Beam pipe transverse cut

0 10 20 30 405

5.5

6

6.5

7

7.5

8

8.5

9x 10

9

Time [ns]N

um

ber

of

e- [

m-1

]

Electron cloud build-up

• Secondary electrons are emitted with smaller energies (E~1eV) and, if they hit

the wall before the following bunch passage, they are absorbed without

generation of further secondaries

• Decay of the total number of electrons can be observed in this stage

Page 35: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Beam pipe transverse cut

0 10 20 30 405

5.5

6

6.5

7

7.5

8

8.5

9x 10

9

Time [ns]N

um

ber

of

e- [

m-1

]

Electron cloud build-up

• Secondary electrons are emitted with smaller energies (E~1eV) and, if they hit

the wall before the following bunch passage, they are absorbed without

generation of further secondaries

• Decay of the total number of electrons can be observed in this stage

Page 36: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Beam pipe transverse cut

0 10 20 30 405

5.5

6

6.5

7

7.5

8

8.5

9x 10

9

Time [ns]N

um

ber

of

e- [

m-1

]

Electron cloud build-up

• Secondary electrons are emitted with smaller energies (E~1eV) and, if they hit

the wall before the following bunch passage, they are absorbed without

generation of further secondaries

• Decay of the total number of electrons can be observed in this stage

Page 37: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Beam pipe transverse cut

0 10 20 30 405

5.5

6

6.5

7

7.5

8

8.5

9x 10

9

Time [ns]N

um

ber

of

e- [

m-1

]

Electron cloud build-up

• Secondary electrons are emitted with smaller energies (E~1eV) and, if they hit

the wall before the following bunch passage, they are absorbed without

generation of further secondaries

• Decay of the total number of electrons can be observed in this stage

Page 38: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Beam pipe transverse cut

0 10 20 30 405

5.5

6

6.5

7

7.5

8

8.5

9x 10

9

Time [ns]N

um

ber

of

e- [

m-1

]

• Another bunch passage can interrupt the decay before reaching the initial value

• In these cases avalanche multiplication is observed between bunch passages,

and an exponential growth of the number of electrons happens during the

bunch train passage

Electron cloud build-up

Page 39: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Beam pipe transverse cut

0 10 20 30 405

5.5

6

6.5

7

7.5

8

8.5

9x 10

9

Time [ns]N

um

ber

of

e- [

m-1

]

• Another bunch passage can interrupt the decay before reaching the initial value

• In these cases avalanche multiplication is observed between bunch passages,

and an exponential growth of the number of electrons happens during the

bunch train passage

Electron cloud build-up

Page 40: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Beam pipe transverse cut

0 10 20 30 405

5.5

6

6.5

7

7.5

8

8.5

9x 10

9

Time [ns]N

um

ber

of

e- [

m-1

]

Electron cloud effect is strongly dependent on bunch spacing!

bunch spac.

Electron cloud build-up

Page 41: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

The electron cloud buildup

Page 42: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

The electron cloud buildup

Page 43: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

The electron cloud buildup

0 1 2 3 4 5 6 7 8 9

x 10-6

104

106

108

time [s]Nu

mb

er

of e

- per

un

it le

ng

th [m

-1]

0 1 2 3 4 5 6 7 8 9

x 10-6

0

2

4

6

8x 10

11

time [s]Accu

m. n

um

ber

of scru

bb

. e- [

m-1

]

Page 44: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

The electron cloud buildup

0 1 2 3 4 5 6 7 8 9

x 10-6

104

106

108

time [s]Nu

mb

er

of e

- per

un

it le

ng

th [m

-1]

0 1 2 3 4 5 6 7 8 9

x 10-6

0

2

4

6

8x 10

11

time [s]Accu

m. n

um

ber

of scru

bb

. e- [

m-1

]

Page 45: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

The electron cloud buildup

0 1 2 3 4 5 6 7 8 9

x 10-6

104

106

108

time [s]Nu

mb

er

of e

- per

un

it le

ng

th [m

-1]

0 1 2 3 4 5 6 7 8 9

x 10-6

0

2

4

6

8x 10

11

time [s]Accu

m. n

um

ber

of scru

bb

. e- [

m-1

]

Page 46: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

The electron cloud buildup

0 1 2 3 4 5 6 7 8 9

x 10-6

104

106

108

time [s]Nu

mb

er

of e

- per

un

it le

ng

th [m

-1]

0 1 2 3 4 5 6 7 8 9

x 10-6

0

2

4

6

8x 10

11

time [s]Accu

m. n

um

ber

of scru

bb

. e- [

m-1

]

The passage of the first bunches of the train provokes an exponential rise of the number of electron in the chamber (multipacting).

Page 47: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

The electron cloud buildup

0 1 2 3 4 5 6 7 8 9

x 10-6

104

106

108

time [s]Nu

mb

er

of e

- per

un

it le

ng

th [m

-1]

0 1 2 3 4 5 6 7 8 9

x 10-6

0

2

4

6

8x 10

11

time [s]Accu

m. n

um

ber

of scru

bb

. e- [

m-1

]

The number of e- tends to saturate to a certain value because of the space charge field generated by the electron themselves.

Page 48: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

The electron cloud buildup

0 1 2 3 4 5 6 7 8 9

x 10-6

104

106

108

time [s]Nu

mb

er

of e

- per

un

it le

ng

th [m

-1]

0 1 2 3 4 5 6 7 8 9

x 10-6

0

2

4

6

8x 10

11

time [s]Accu

m. n

um

ber

of scru

bb

. e- [

m-1

]

Page 49: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

The electron cloud buildup

0 1 2 3 4 5 6 7 8 9

x 10-6

104

106

108

time [s]Nu

mb

er

of e

- per

un

it le

ng

th [m

-1]

0 1 2 3 4 5 6 7 8 9

x 10-6

0

2

4

6

8x 10

11

time [s]Accu

m. n

um

ber

of scru

bb

. e- [

m-1

]

The e-cloud is partially lost in the gaps between batches and a short build-up is observed at the beginning of each batch passage

Page 50: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

The electron cloud buildup

0 1 2 3 4 5 6 7 8 9

x 10-6

104

106

108

time [s]Nu

mb

er

of e

- per

un

it le

ng

th [m

-1]

0 1 2 3 4 5 6 7 8 9

x 10-6

0

2

4

6

8x 10

11

time [s]Accu

m. n

um

ber

of scru

bb

. e- [

m-1

]

Page 51: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

The electron cloud buildup

0 1 2 3 4 5 6 7 8 9

x 10-6

104

106

108

time [s]Nu

mb

er

of e

- per

un

it le

ng

th [m

-1]

0 1 2 3 4 5 6 7 8 9

x 10-6

0

2

4

6

8x 10

11

time [s]Accu

m. n

um

ber

of scru

bb

. e- [

m-1

]

Page 52: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

The electron cloud buildup

0 1 2 3 4 5 6 7 8 9

x 10-6

104

106

108

time [s]Nu

mb

er

of e

- per

un

it le

ng

th [m

-1]

0 1 2 3 4 5 6 7 8 9

x 10-6

0

2

4

6

8x 10

11

time [s]Accu

m. n

um

ber

of scru

bb

. e- [

m-1

]

Page 53: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

The electron cloud buildup

0 1 2 3 4 5 6 7 8 9

x 10-6

104

106

108

time [s]Nu

mb

er

of e

- per

un

it le

ng

th [m

-1]

0 1 2 3 4 5 6 7 8 9

x 10-6

0

2

4

6

8x 10

11

time [s]Accu

m. n

um

ber

of scru

bb

. e- [

m-1

]

Page 54: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

The electron cloud buildup

0 1 2 3 4 5 6 7 8 9

x 10-6

104

106

108

time [s]Nu

mb

er

of e

- per

un

it le

ng

th [m

-1]

0 1 2 3 4 5 6 7 8 9

x 10-6

0

2

4

6

8x 10

11

time [s]Accu

m. n

um

ber

of scru

bb

. e- [

m-1

]

Page 55: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

The electron cloud buildup

0 1 2 3 4 5 6 7 8 9

x 10-6

104

106

108

time [s]Nu

mb

er

of e

- per

un

it le

ng

th [m

-1]

0 1 2 3 4 5 6 7 8 9

x 10-6

0

2

4

6

8x 10

11

time [s]Accu

m. n

um

ber

of scru

bb

. e- [

m-1

]

After the passage of the train the e-cloud decays

Page 56: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

The electron cloud buildup

Page 57: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

The electron cloud buildup

Page 58: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

The electron cloud buildup

0 0.5 1 1.5 2 2.5 3

x 10-5

104

106

108

1010

t [s]

Nu

mb

er

of

e- p

er

un

it le

ng

th [

m-1

]

0 0.5 1 1.5 2 2.5 3

x 10-5

104

106

108

1010

t [s]

Nu

mb

er

of

e- p

er

un

it le

ng

th [

m-1

]

The decay can be fast enough that no memory effect is observed between turns

1st turn 2nd turn

Page 59: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

0 0.5 1 1.5 2 2.5 3

x 10-5

104

106

108

1010

t [s]

Nu

mb

er

of

e- p

er

un

it le

ng

th [

m-1

]

0 0.5 1 1.5 2 2.5 3

x 10-5

104

106

108

1010

t [s]

Nu

mb

er

of

e- p

er

un

it le

ng

th [

m-1

]

The electron cloud buildup

If the decay is slow enough or other memory effects are present a multi-turn regime can be observed

5% uncaptured beam present in the machine

1st turn 2nd turn

Page 60: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Electron cloud distribution in a bending magnet

-0.50

0.5

-0.50

0.51

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

P

Rc

B

In a strong dipolar magnetic field, electrons perform helicoidal

trajectories around the field lines.

Page 61: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Electron cloud distribution in a bending magnet

-0.50

0.5

-0.50

0.51

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

P

Rc

B

In a strong dipolar magnetic field, electrons perform helicoidal

trajectories around the field lines.

<1ns

<1mm

e- are confined to move along B field lines

Page 62: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Electron cloud distribution in a bending magnet

e-

0 200 400 600 800 10000.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

Primary e- energy [eV]

Se

co

nd

ary

Ele

ctr

on

Yie

ld [

SE

Y]

Page 63: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Electron cloud distribution in a bending magnet

e-

0 200 400 600 800 10000.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

Primary e- energy [eV]

Se

co

nd

ary

Ele

ctr

on

Yie

ld [

SE

Y]

Page 64: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Electron cloud distribution in a bending magnet

e-

0 200 400 600 800 10000.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

Primary e- energy [eV]

Se

co

nd

ary

Ele

ctr

on

Yie

ld [

SE

Y]

Page 65: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Electron cloud distribution in a bending magnet

e-

0 200 400 600 800 10000.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

Primary e- energy [eV]

Se

co

nd

ary

Ele

ctr

on

Yie

ld [

SE

Y]

Page 66: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Electron cloud distribution in a bending magnet

This gives the two stripes distribution that typical for the e-

cloud in a bending magnet

Page 67: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Outline

• A few basic concepts on e-cloud build-up

• PyEcloud: How do we simulate the e-cloud build-up

o Flow-chart

o MP size management

o Convergence and performances

• Overview of e-cloud studies for CERN accelerators:

o e-cloud studies for the PS and SPS

o e-cloud studies for the LHC

25ns observation benchmarking for the arcs

e-cloud build-up in in 800mm common pipe near IP2

Page 68: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

ECLOUD

• Analysis and prediction on the e-cloud buildup strongly relies on numerical

simulations that are typically performed with simulation tools developed ad-

hoc.

• Most of the work done at CERN in the last years has employed the ECLOUD

code (developed at CERN since 1998, mainly by G. Bellodi, O. Bruning, G.

Rumolo, D. Schulte, F. Zimmermann).

• At the very beginning our idea was to reorganize ECLOUD in order to make it

easier to develop new features, to identify and correct present and future

bugs, to access a larger amount of information about our simulations

• However…

Page 69: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

PyECLOUD

We have decided to write a new fully reorganized build-up code, in a newer and

more powerful language, considering that the initial effort would be compensated

by a significantly increased efficiency in future development and debugging.

The employed programming language is Python:

• Interpreted language (open source), allowing incremental and

interactive development of the code, encouraging an highly

modular structure

• Libraries for scientific computation (e.g Numpy, Scipy, Pylab)

• Extensible with C/C++ or FORTRAN compiled modules for

computationally intensive parts

Thanks to R. De Maria and K. Li

Page 70: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Thanks to C. Bhat, O. Dominguez, H. Maury Cuna, F. Zimmermann

PyECLOUD

Writing PyECLOUD has required a detailed analysis of ECLOUD algorithm and

implementation, looking also at the related long experience in electron cloud simulations.

Attention has been devoted to the identification of ECLOUD limitations, in particular in

terms of its convergence properties with respect to the electron distribution in bending

magnets (how many stripes…)

As a result, several features have been significantly modified in order to improve the

code’s performances in terms:

• Reliability & Accuracy

• Efficiency

• Flexibility

Page 71: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Macroparticles

The simulation of the dynamics of the entire number of electrons (≈1010 per meter)

is extremely heavy (practically unaffordable)

Since the dynamics equation of the electron depends only on the q/m ratio of the

electron a macroparticle (MP) method can be used:

The MP size can be seen as the “resolution” our electron gas simulation

Page 72: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Outline

• A few basic concepts on e-cloud build-up

• PyEcloud: How do we simulate the e-cloud build-up

o Flow-chart

o MP size management

o Convergence and performances

• Overview of e-cloud studies for CERN accelerators:

o e-cloud studies for the PS and SPS

o e-cloud studies for the LHC

25ns observation benchmarking for the arcs

e-cloud build-up in in 800mm common pipe near IP2

Page 73: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

t=t+Δt

Evaluate the electric field of beam at each MP location

Generate seed e-

Compute MP motion (t->t+Δt)

Detect impacts and generate secondaries

PyEcloud flowchart

Evaluate the e- space charge electric field

Page 74: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

t=t+Δt

Evaluate the electric field of beam at each MP location

Generate seed e-

Compute MP motion (t->t+Δt)

Detect impacts and generate secondaries

PyEcloud flowchart

Evaluate the e- space charge electric field

Evaluate the number of seed e- which are

generated during the current time step and

generate the corresponding MP:

• Residual gas ionization and

photoemission are implemented

• Theoretical/empirical models are used to

determine MP space and energy

distributions

Page 75: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

x [mm]

y [

mm

]

Charge density [m-1]

-60 -40 -20 0 20 40 60

-20

-10

0

10

20

0

1

2

x 104t=t+Δt

Evaluate the electric field of beam at each MP location

Generate seed e-

Compute MP motion (t->t+Δt)

Detect impacts and generate secondaries

Evaluate the e- space charge electric field

• The field map for the relevant chamber

geometry and beam shape is pre-computed

on a suitable rectangular grid and loaded

from file in the initialization stage

• When the field at a certain location is

needed a linear (4 points) interpolation

algorithm is employed

PyEcloud flowchart

Page 76: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

x [mm]

y [

mm

]

E log(normalizad magnitude) - with image charges

-60 -40 -20 0 20 40 60

-20

-10

0

10

20

-4

-3

-2

-1

t=t+Δt

Evaluate the electric field of beam at each MP location

Generate seed e-

Compute MP motion (t->t+Δt)

Detect impacts and generate secondaries

Evaluate the e- space charge electric field

• The field map for the relevant chamber

geometry and beam shape is pre-computed

on a suitable rectangular grid and loaded

from file in the initialization stage

• When the field at a certain location is

needed a linear (4 points) interpolation

algorithm is employed

PyEcloud flowchart

Page 77: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

t=t+Δt

Evaluate the electric field of beam at each MP location

Generate seed e-

Compute MP motion (t->t+Δt)

Detect impacts and generate secondaries

Evaluate the e- space charge electric field

• The field map for the relevant chamber

geometry and beam shape is pre-computed

on a suitable rectangular grid and loaded

from file in the initialization stage

• When the field at a certain location is

needed a linear (4 points) interpolation

algorithm is employed

PyEcloud flowchart

Page 78: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

t=t+Δt

Evaluate the electric field of beam at each MP location

Generate seed e-

Compute MP motion (t->t+Δt)

Detect impacts and generate secondaries

Evaluate the e- space charge electric field

x [m]

y [

m]

(x,y) [C/m2]

-0.06 -0.04 -0.02 0 0.02 0.04 0.06

-0.02

-0.01

0

0.01

0.02

-2.5

-2

-1.5

-1

-0.5

0x 10

-5

• To compute the e- space charge electric

field we employ a classical Particle In Cell

(PIC) algorithm

PyEcloud flowchart

Page 79: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

t=t+Δt

Evaluate the electric field of beam at each MP location

Generate seed e-

Compute MP motion (t->t+Δt)

Detect impacts and generate secondaries

Evaluate the e- space charge electric field

x [m]

y [

m]

(x,y) [C/m2]

-0.06 -0.04 -0.02 0 0.02 0.04 0.06

-0.02

-0.01

0

0.01

0.02

-2.5

-2

-1.5

-1

-0.5

0x 10

-5

Poisson equation:

with on the boundary

The electric field is given by:

Electrostatic potential e- charge density

PyEcloud flowchart

Page 80: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

t=t+Δt

Evaluate the electric field of beam at each MP location

Generate seed e-

Compute MP motion (t->t+Δt)

Detect impacts and generate secondaries

Evaluate the e- space charge electric field The electron charge density distribution

ρ(x,y) is computed on a uniform square grid

by distributing the charge of each MP to

the nearest 4 nodes:

PyEcloud flowchart

Page 81: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

t=t+Δt

Evaluate the electric field of beam at each MP location

Generate seed e-

Compute MP motion (t->t+Δt)

Detect impacts and generate secondaries

Evaluate the e- space charge electric field

Finite differencesmethod

PyEcloud flowchart

Page 82: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

t=t+Δt

Evaluate the electric field of beam at each MP location

Generate seed e-

Compute MP motion (t->t+Δt)

Detect impacts and generate secondaries

Evaluate the e- space charge electric field

Finite differencesmethod

Sparse matrix depending only on the geometry (can be computed in the initialization stage and reused for all the space-charge evaluations).

PyEcloud flowchart

Page 83: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

t=t+Δt

Evaluate the electric field of beam at each MP location

Generate seed e-

Compute MP motion (t->t+Δt)

Detect impacts and generate secondaries

Evaluate the e- space charge electric field

Central difference formulas are used to

retrieve the electric field on the nodes:

PyEcloud flowchart

Page 84: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

t=t+Δt

Evaluate the electric field of beam at each MP location

Generate seed e-

Compute MP motion (t->t+Δt)

Detect impacts and generate secondaries

Evaluate the e- space charge electric field

• When the field at a certain location is

needed a linear (4 points) interpolation

algorithm is employed

PyEcloud flowchart

Page 85: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

x [m]

y [

m]

(x,y) [C/m2]

-0.06 -0.04 -0.02 0 0.02 0.04 0.06

-0.02

-0.01

0

0.01

0.02

-2.5

-2

-1.5

-1

-0.5

0x 10

-5

x [m]

y [

m]

(x,y) [V]

-0.06 -0.04 -0.02 0 0.02 0.04 0.06

-0.02

-0.01

0

0.01

0.02

-200

-150

-100

-50

0

x [m]

y [

m]

|E(x,y)| [V/m]

-0.06 -0.04 -0.02 0 0.02 0.04 0.06

-0.02

-0.01

0

0.01

0.02

0

5000

10000

15000

t=t+Δt

Evaluate the electric field of beam at each MP location

Generate seed e-

Compute MP motion (t->t+Δt)

Detect impacts and generate secondaries

Evaluate the e- space charge electric field

PyEcloud flowchart

Page 86: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

t=t+Δt

Evaluate the electric field of beam at each MP location

Generate seed e-

Compute MP motion (t->t+Δt)

Detect impacts and generate secondaries

Evaluate the e- space charge electric field

When possible, “strong B condition” is

exploited in order to speed-up the

computation (D. Schulte)

The dynamics equation is integrated in order

to update MP position and momentum:

PyEcloud flowchart

Page 87: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

t=t+Δt

Evaluate the electric field of beam at each MP location

Generate seed e-

Compute MP motion (t->t+Δt)

Detect impacts and generate secondaries

Evaluate the e- space charge electric field

• When a MP hits the wall

theoretical/empirical models are

employed to generate charge, energy

and angle of the emitted charge

• According to the number of emitted

electrons, MPs can be simply rescaled or

new MP can be generated.

PyEcloud flowchart

Page 88: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Outline

• A few basic concepts on e-cloud build-up

• PyEcloud: How do we simulate the e-cloud build-up

o Flow-chart

o MP size management

o Convergence and performances

• Overview of e-cloud studies for CERN accelerators:

o e-cloud studies for the PS and SPS

o e-cloud studies for the LHC

25ns observation benchmarking for the arcs

e-cloud build-up in in 800mm common pipe near IP2

Page 89: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Macroparticle size management

0 1 2 3 4 5 6 7 8 9

x 10-6

104

106

108

time [s]Nu

mb

er

of e

- per

un

it le

ng

th [m

-1]

0 1 2 3 4 5 6 7 8 9

x 10-6

0

2

4

6

8x 10

11

time [s]Accu

m. n

um

ber

of scru

bb

. e- [

m-1

]

In an electron-cloud buildup, due to the multipacting process, the electron

number spreads several orders of magnitude:

It is practically impossible to choose a MP size that is suitable for the entire

simulation (allowing a satisfactory description of the phenomenon and a

computationally affordable number of MPs)

Page 90: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

We define a target average size of the MPs Nref which is adaptively changed

during the simulation and is used for:

1) Seed MP generation: the generated

MPs have size Nref

2) Secondary MP emission: additional

true secondary MPs are emitted if the

total emitted charge is >1.5Nref

3) MP cleaning: at each bunch passage a

clean function is called that eliminates

all the MPs with charge <10-4Nref

x

Macroparticle size management

Page 91: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

When the number of MPs becomes larger than a certain threshold (≈105) that

means that the computational burden is becoming too high, we change MP target

size (Nref ) and perform a regeneration of the MPs system:

Macroparticle size management

Page 92: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

a. Each macroparticle is assigned to a cell of a uniform grid in the 5-D space

(x,y,vx,vy,vz) obtaining an approximation of the phase space distribution

Macroparticle size management

When the number of MPs becomes larger than a certain threshold (≈105) that

means that the computational burden is becoming too high, we change MP target

size (Nref ) and perform a regeneration of the MPs system:

x [m]

y [

m]

-0.02 -0.01 0 0.01 0.02

-0.015

-0.01

-0.005

0

0.005

0.01

0.015

x [m]

vx [

m/s

]

-0.02 -0.015 -0.01 -0.005 0 0.005 0.01 0.015 0.02

-4

-3

-2

-1

0

1

2

3

4

x 106

Page 93: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

a. Each macroparticle is assigned to a cell of a uniform grid in the 5-D space

(x,y,vx,vy,vz) obtaining an approximation of the phase space distribution

Macroparticle size management

When the number of MPs becomes larger than a certain threshold (≈105) that

means that the computational burden is becoming too high, we change MP target

size (Nref ) and perform a regeneration of the MPs system:

x [m]

y [

m]

-0.02 -0.01 0 0.01 0.02

-0.015

-0.01

-0.005

0

0.005

0.01

0.015

x [m]

vx [

m/s

]

-0.02 -0.015 -0.01 -0.005 0 0.005 0.01 0.015 0.02

-4

-3

-2

-1

0

1

2

3

4

x 106

Page 94: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

y [m]

vy [

m/s

]

-0.015 -0.01 -0.005 0 0.005 0.01 0.015

-4

-3

-2

-1

0

1

2

3

4

x 106

vx [m/s]

vz [

m/s

]

-2 -1.5 -1 -0.5 0 0.5 1 1.5 2

x 106

-2

-1.5

-1

-0.5

0

0.5

1

1.5

2x 10

6

Macroparticle size management

a. Each macroparticle is assigned to a cell of a uniform grid in the 5-D space

(x,y,vx,vy,vz) obtaining an approximation of the phase space distribution

When the number of MPs becomes larger than a certain threshold (≈105) that

means that the computational burden is becoming too high, we change MP target

size (Nref ) and perform a regeneration of the MPs system:

Page 95: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Macroparticle size management

a. Each macroparticle is assigned to a cell of a uniform grid in the 5-D space

(x,y,vx,vy,vz) obtaining an approximation of the phase space distribution

b. The new target MP size is chosen so that:

When the number of MPs becomes larger than a certain threshold (≈105) that

means that the computational burden is becoming too high, we change MP target

size (Nref ) and perform a regeneration of the MPs system:

c. A new MPs set, having the new reference size, is generated according to

the computed distribution.

Page 96: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Macroparticle size management

a. Each macroparticle is assigned to a cell of a uniform grid in the 5-D space

(x,y,vx,vy,vz) obtaining an approximation of the phase space distribution

b. The new target MP size is chosen so that:

When the number of MPs becomes larger than a certain threshold (≈105) that

means that the computational burden is becoming too high, we change MP target

size (Nref ) and perform a regeneration of the MPs system:

c. A new MPs set, having the new reference size, is generated according to

the computed distribution.

All moments related to position and velocity (e.g. energy distrib. , charge distrib.)

are preserved. The error on total charge and total energy does not go beyond 1-2%

Page 97: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Outline

• A few basic concepts on e-cloud build-up

• PyEcloud: How do we simulate the e-cloud build-up

o Flow-chart

o MP size management

o Convergence and performances

• Overview of e-cloud studies for CERN accelerators:

o e-cloud studies for the PS and SPS

o e-cloud studies for the LHC

25ns observation benchmarking for the arcs

e-cloud build-up in in 800mm common pipe near IP2

Page 98: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Convergence study - Number of electrons

0 0.5 1 1.5 2 2.5 3 3.5 4

x 10-6

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

x 109

t [s]

Nu

mb

er

of

e- p

er

un

it le

ng

th [

m-1

]

0.2ns0.1ns0.05ns0.025ns0.012ns

0 1 2 3 4 5

x 10-6

0

0.5

1

1.5

2

2.5

3x 10

9

t [s]

Nu

mb

er

of

e- p

er

un

it le

ng

th [

m-1

]

0.2ns0.1ns0.05ns0.025ns0.012ns

ECLOUD PyECLOUD

Page 99: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

20 40 60 80 100 120 140 1600

0.5

1

1.5

2

2.5

3

3.5

4

4.5

Bunch passage

En

erg

y d

ep

os

itio

n [

W/m

]

0.2ns0.1ns0.05ns0.025ns0.012ns

20 40 60 80 100 120 140 160 180

0.5

1

1.5

2

2.5

3

3.5

Bunch passage

En

erg

y d

ep

os

itio

n [

W/m

]

0.2ns0.1ns0.05ns0.025ns

Convergence study – Heat load

ECLOUD PyECLOUD

Page 100: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

0 0.01 0.02 0.03 0.04 0.05 0.06

10-10

10-5

100

x [m]

Av

. e- c

ha

rge

hit

tin

g t

he

wa

ll [A

m-2

]

0.2ns0.1ns0.05ns0.025ns0.012ns

0 0.01 0.02 0.03 0.04 0.05 0.06

10-10

10-5

100

x [m]

Av

. e- c

ha

rge

hit

tin

g t

he

wa

ll [A

m-2

]

0.2ns0.1ns0.05ns0.025ns

Convergence study – Electrons ditribution

ECLOUD PyECLOUD

Page 101: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

0

2000

4000

6000

8000

10000

12000

14000

16000

0.200ns 0.100ns 0.050ns 0.025ns 0.012ns

ECLOUD

PYECLOUD

Timestep ECLOUD PYECLOUD

0.2 ns 29 min 12 min

0.1 ns 1h 27 min 13 min

0.05 ns 1h 45 min 24 min

0.025ns 3h 7 min 40 min

0.012ns 4h 15 min 1h 6 min

Processing time

Page 102: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Outline

• A few basic concepts on e-cloud build-up

• PyEcloud: How do we simulate the e-cloud build-up

o Flow-chart

o MP size management

o Convergence and performances

• Overview of e-cloud studies for CERN accelerators:

o e-cloud studies for the PS and SPS

o e-cloud studies for the LHC

25ns observation benchmarking for the arcs

e-cloud build-up in in 800mm common pipe near IP2

Page 103: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

0 0.5 1 1.5 20

0.01

0.02

0.03

time [us]

e-c

lou

d s

ign

al [

a.u

. ]

Av. intensity = 1.57*1011ppb Bunch length = 15.0ns

0 0.5 1 1.5 20

2

4

6

time [us]

Pic

k-u

p s

ign

al [

a.u

.]

In the PS, the e-cloud appears only in the last stages of the RF gymnastics. A dedicated

e-cloud experiment, with a shielded pickup, is available.

E-cloud studies for the PS

Measurements with 50ns beam

Thanks to F. Caspers, S. Gilardoni, E. Mahner, C. Y. Vallgren

Page 104: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

0 0.5 1 1.5 20

0.01

0.02

0.03

time [us]

e-c

lou

d s

ign

al [

a.u

. ]

Av. intensity = 1.49*1011ppb Bunch length = 6.5ns

0 0.5 1 1.5 20

2

4

6

time [us]

Pic

k-u

p s

ign

al [

a.u

.]

In the PS, the e-cloud appears only in the last stages of the RF gymnastics. A dedicated

e-cloud experiment, with a shielded pickup, is available.

E-cloud studies for the PS

Measurements with 50ns beam

Thanks to F. Caspers, S. Gilardoni, E. Mahner, C. Y. Vallgren

Page 105: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

0 0.5 1 1.5 20

0.01

0.02

0.03

time [us]

e-c

lou

d s

ign

al [

a.u

. ]

Av. intensity = 1.47*1011ppb Bunch length = 4.0ns

0 0.5 1 1.5 20

2

4

6

time [us]

Pic

k-u

p s

ign

al [

a.u

.]

In the PS, the e-cloud appears only in the last stages of the RF gymnastics. A dedicated

e-cloud experiment, with a shielded pickup, is available.

E-cloud studies for the PS

Measurements with 50ns beam

Thanks to F. Caspers, S. Gilardoni, E. Mahner, C. Y. Vallgren

Page 106: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

0 0.5 1 1.5 20

0.05

0.1

time [us]

e-c

lou

d s

ign

al [

a.u

. ]

Av. intensity = 1.15*1011ppb Bunch length = 15.0ns

0 0.5 1 1.5 20

2

4

time [us]

Pic

k-u

p s

ign

al [

a.u

.]

E-cloud studies for the PS

In the PS, the e-cloud appears only in the last stages of the RF gymnastics. A dedicated

e-cloud experiment, with a shielded pickup, is available.

Measurements with 25ns beam

Thanks to F. Caspers, S. Gilardoni, E. Mahner, C. Y. Vallgren

Page 107: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

0 0.5 1 1.5 20

0.05

0.1

time [us]

e-c

lou

d s

ign

al [

a.u

. ]

Av. intensity = 1.15*1011ppb Bunch length = 6.5ns

0 0.5 1 1.5 20

2

4

time [us]

Pic

k-u

p s

ign

al [

a.u

.]

In the PS, the e-cloud appears only in the last stages of the RF gymnastics. A dedicated

e-cloud experiment, with a shielded pickup, is available.

Measurements with 25ns beam

E-cloud studies for the PS

Thanks to F. Caspers, S. Gilardoni, E. Mahner, C. Y. Vallgren

Page 108: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

0 0.5 1 1.5 20

0.05

0.1

time [us]

e-c

lou

d s

ign

al [

a.u

. ]

Av. intensity = 1.15*1011ppb Bunch length = 4.0ns

0 0.5 1 1.5 20

2

4

time [us]

Pic

k-u

p s

ign

al [

a.u

.]

In the PS, the e-cloud appears only in the last stages of the RF gymnastics. A dedicated

e-cloud experiment, with a shielded pickup, is available.

Measurements with 25ns beam

E-cloud studies for the PS

Thanks to F. Caspers, S. Gilardoni, E. Mahner, C. Y. Vallgren

Page 109: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

0 0.5 1 1.5 20

0.2

0.4

0.6

0.8

1

Time [us]

Ele

ctr

on

clo

ud

ind

ica

tor

[a.u

]

PyECLOUD simulation0 0.5 1 1.5 2

0

0.2

0.4

0.6

0.8

1

Time [us]

e-c

lou

d s

ign

al [

a.u

.]

Measurement

In the PS, the e-cloud appears only in the last stages of the RF gymnastics. A dedicated

e-cloud experiment, with a shielded pickup, is available.

Benchmarking of these data with simulations is ongoing:

E-cloud studies for the PS

Page 110: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

E-cloud studies for the SPS

• Clear indications of e-cloud activity along the ring with 25ns beam (basically

pressure rise)

• E-cloud mitigation is considered necessary to improve the machine performances

(LIU) -> aC coating is the baseline

• Simulation and machine studies are ongoing to identify which parts of the machine

need to be coated and to optimize the scrubbing process for the other components

Thanks to:H. Bartosik, F. Caspers, M. Driss Mensi, B. Goddard, H. Neupert, M. Taborrelli,E. Shaposhnikova

Page 111: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

E-cloud studies for the SPS

1.5 2 2.5 3 3.51

1.2

1.4

1.6

1.8

2M

ulti

pa

cti

ng

th

res

ho

ld ( m

ax)

Beam intensity [ppb]

50ns - 26GeV50ns - 450GeV25ns - 26GeV25ns - 450GeV

1.5 2 2.5 3 3.51

1.2

1.4

1.6

1.8

2

Mu

ltip

ac

tin

g t

hre

sh

old

( m

ax)

Beam intensity [ppb]

50ns - 26GeV50ns - 450GeV

25ns - 26GeV25ns - 450GeV

1.5 2 2.5 3 3.51

1.2

1.4

1.6

1.8

2

Mu

ltip

ac

tin

g t

hre

sh

old

( m

ax)

Beam intensity [ppb]

50ns - 26GeV50ns - 450GeV

25ns - 26GeV25ns - 450GeV

1.5 2 2.5 3 3.51

1.2

1.4

1.6

1.8

2

Mu

ltip

ac

tin

g t

hre

sh

old

( m

ax)

Beam intensity [ppb]

50ns - 26GeV50ns - 450GeV25ns - 26GeV25ns - 450GeV

Page 112: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

E-cloud studies for the SPS

Different e-cloud experiments are available (Strip detectors, shielded pickup, aC coated

magnets and straight sections). Much data collected during 2012 Scrubbing Run and

MD session. Analysis and simulation benchmarking is ongoing.

0 1 2 3 4 5 6 7

-0.01

0

0.01

Be

am

sig

na

l

Time [s]

0 1 2 3 4 5 6 7

-0.2

0

0.2

0.4

e-c

lou

d s

ign

al

Time [s]

Example of shielded pickup measurement

Page 113: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

E-cloud studies for the SPS

Different e-cloud experiments are available (Strip detectors, shielded pickup, aC coated

magnets and straight sections). Much data collected during 2012 Scrubbing Run and

MD session. Analysis and simulation benchmarking is ongoing.

Strip-detector measurements on MBA profile

Page 114: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Outline

• A few basic concepts on e-cloud build-up

• PyEcloud: How do we simulate the e-cloud build-up

o Flow-chart

o MP size management

o Convergence and performances

• Overview of e-cloud studies for CERN accelerators:

o e-cloud studies for the PS and SPS

o e-cloud studies for the LHC

25ns observation benchmarking for the arcs

e-cloud build-up in in 800mm common pipe near IP2

Page 115: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

25ns tests in the LHC

0 5 10 15 20 25 30 35 40 45 50 550

5

10

15

20x 10

13

Inte

nsi

ty

Time [h]

0 5 10 15 20 25 30 35 40 45 50 55

0

10

20

30

40

Time [h]

Hea

t lo

ad [

W/h

cell

]

S12S23S34S45S56S67S78S81

DATE SHORT DESCRIPTION

29 June Injections of 9 x 24b trains per beam with different spacings between them

26 August Two attempts to inject a 48b train with damper on and off: fast instability dumps the beam within 500 turns in both cases (SBI and CBI)

7 October High chromaticity (Q’x,y ≈15): Injection tests with trains of 72-144-216-288 bunches from the SPS + ramp to 3.5 TeV & 5h store with 60b (12+24+24) per beam

14 October High chromaticity: injection of up to 1020 bunches per beam in 72b trains (decreasing spacings between trains at each fill: 6.3–3.2–1 ms)

24-25 October Injection of up to 2100 bunches in Beam 1 and 1020 in Beam 2 (1ms train spacing)

Scrubbing

29/06 07/10 24-25/1014/10

Beam 1 Beam 2 Energy

Page 116: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

0 10 20 30 40 50 60 70 800

5

10

x 1010

Bunch position [us]

Bu

nch

inte

nsity [p

pb

]

0 10 20 30 40 50 60 70 800

1

2

Bunch position [us]

Bu

nch

len

gth

[n

s]

0 10 20 30 40 50 60 70 800

1

2

x 109

Time [us]

e- p

er

un

it le

ng

th [m

-1]

Simulation approach

• The entire beam with measured bunch intensities and bunch lengths has been simulated:

From FBCT

From BQM

Page 117: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

0 10 20 30 40 50 60 70 800

5

10

x 1010

Bunch position [us]

Bu

nch

inte

nsity [p

pb

]

0 10 20 30 40 50 60 70 800

1

2

Bunch position [us]

Bu

nch

len

gth

[n

s]

0 10 20 30 40 50 60 70 800

1

2

x 109

Time [us]

e- p

er

un

it le

ng

th [m

-1]

Simulation approach

• The entire beam with measured bunch intensities and bunch lengths has been simulated:

From FBCT

From BQM

Page 118: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

0 10 20 30 40 50 60 70 800

5

10

x 1010

Bunch position [us]

Bu

nch

inte

nsity [p

pb

]

0 10 20 30 40 50 60 70 800

1

2

Bunch position [us]

Bu

nch

len

gth

[n

s]

0 10 20 30 40 50 60 70 800

1

2

x 109

Time [us]

e- p

er

un

it le

ng

th [m

-1]

Simulation approach

• The entire beam with measured bunch intensities and bunch lengths has been simulated:

From FBCT

From BQM

Page 119: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

0 5 10 15 20 25 30 35 40 45 50 550

5

10

15

20x 10

13

Inte

nsi

ty

Time [h]

0 5 10 15 20 25 30 35 40 45 50 55

0

10

20

30

40

Time [h]

Hea

t lo

ad [

W/h

cell

]

S12S23S34S45S56S67S78S81

Heat load

29/06 07/10 24-25/1014/10

Beam 1 Beam 2 Energy

0 5 10 15 20 25 30 35 40 45 50 550

5

10

15

20x 10

13

Inte

nsi

ty

Time [h]

0 5 10 15 20 25 30 35 40 45 50 55

0

10

20

30

40

Time [h]

Hea

t lo

ad [

W/h

cell

]

S12S23S34S45S56S67S78S81

29/06 07/10 24-25/1014/10

Thanks to S. Clodet, L. Tavian

Page 120: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

0 5 10 15 20 25 30 35 40 45 50 550

5

10

15

20x 10

13

Inte

nsi

ty

Time [h]

0 5 10 15 20 25 30 35 40 45 50 55

0

10

20

30

40

Time [h]

Hea

t lo

ad [

W/h

cell

]

S12S23S34S45S56S67S78S81

Heat load

29/06 07/10 24-25/1014/10

Beam 1 Beam 2 Energy

0 5 10 15 20 25 30 35 40 45 50 550

5

10

15

20x 10

13

Inte

nsi

ty

Time [h]

0 5 10 15 20 25 30 35 40 45 50 55

0

10

20

30

40

Time [h]

Hea

t lo

ad [

W/h

cell

]

S12S23S34S45S56S67S78S81

29/06 07/10 24-25/1014/10

Six snapshots from the 25ns MDs to reproduce the measured heat load by simulations!

Page 121: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Heat load

0 10 20 30 40 500

5

10

15

20x 10

13

Inte

nsi

ty

Time [h]

0 10 20 30 40 50

1.4

1.6

1.8

2

2.2

max

Time [h] 121

dmax has decreased from the initial 2.1 to 1.52 in the arcs !

25ns threshold @450 GeV

25ns threshold @3.5 TeV

29/06 07/10 24-25/1014/10

50ns

2011 scrubbing history of LHC arcs

Page 122: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

0 500 1000 1500 2000 2500 3000 35000

0.5

1

1.5

2

2.5

Bu

nch

en

erg

y lo

ss [

mJ/

Tu

rn]

25ns bucket number

SimulatedMeasured

Bunch energy loss

Simulations dmax fixed to 1.5(added 2e9p+/m uncapt. beam)

Measurements the energy loss per bunch is obtained from the stable phase shift

Beam 1

ZOOM

Thanks to J. E. Muller, E. Shaposhnikova

Page 123: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

3060 3080 3100 3120 3140 31600

0.5

1

1.5

2

2.5

3

Bu

nch

en

erg

y lo

ss [

mJ/

Tu

rn]

25ns bucket number

SimulatedMeasured

1860 1880 1900 1920 1940 1960 19800

0.5

1

1.5

2

Bu

nch

en

erg

y lo

ss [

mJ/

Tu

rn]

25ns bucket number

SimulatedMeasured

1550 1600 16500

0.5

1

1.5

2B

un

ch e

ner

gy

loss

[m

J/T

urn

]

25ns bucket number

SimulatedMeasured

Bunch energy loss

2420 2440 2460 2480 25000

0.5

1

1.5

2

Bu

nch

en

erg

y lo

ss [

mJ/

Tu

rn]

25ns bucket number

SimulatedMeasured

Thanks to J. E. Muller, E. Shaposhnikova

Page 124: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Outline

• A few basic concepts on e-cloud build-up

• PyEcloud: How do we simulate the e-cloud build-up

o Flow-chart

o MP size management

o Convergence and performances

• Overview of e-cloud studies for CERN accelerators:

o e-cloud studies for the PS and SPS

o e-cloud studies for the LHC

25ns observation benchmarking for the arcs

e-cloud build-up in in 800mm common pipe near IP2

Page 125: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

800mm vacuum chamber @ IP2

Vacuum team has reported pressure rise in 800mm common vacuum chambers

on both sides of ALICE, with significant impact on background

Ø 20cm

Ø 80cm

27m

Page 126: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Vacuum observations

Pressure measurements in the 800mm chambers on both sides of ALICE

1092 1380Number of bunches per beam1236

ALICE polarity flip seems to cause further worsening of vacuum quality followed by a slow conditioning

Thanks to O. Dominguez, V. Baglin

Page 127: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Fill 1960 19-20/07/2011

Ramp

Vacuum observations

Thanks to O. Dominguez, V. Baglin

Page 128: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Fill 1960 19-20/07/2011

To check if our model of e-cloud can explain the observed behavior of

pressure rise, we have simulated the electron cloud build up in the

800mm chamber before and after the last two injections

Simulated conditions

800mm chamber – two beams simulations

Page 129: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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2/61

2nd turn1st turn LSS2

Before the last two injections (144 bunches per injection) about 1/4 of each ring is still empty

800mm chamber – two beams simulations

Page 130: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

0 20 40 60 80 100 120 140 1600

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2nd turn1st turn LSS2

Before the last two injections (144 bunches per injection) about 1/4 of each ring is still empty

800mm chamber – two beams simulations

Page 131: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

0 20 40 60 80 100 120 140 1600

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Before the last two injections (144 bunches per injection) about 1/4 of each ring is still empty

800mm chamber – two beams simulations

Page 132: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

0 20 40 60 80 100 120 140 1600

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Before the last two injections (144 bunches per injection) about 1/4 of each ring is still empty

800mm chamber – two beams simulations

Page 133: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

0 20 40 60 80 100 120 140 1600

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2nd turn1st turn LSS2

Before the last two injections (144 bunches per injection) about 1/4 of each ring is still empty

800mm chamber – two beams simulations

Page 134: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

0 20 40 60 80 100 120 140 1600

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800mm chamber – two beams simulations

Page 135: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

0 20 40 60 80 100 120 140 1600

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Before the last two injections (144 bunches per injection) about 1/4 of each ring is still empty

800mm chamber – two beams simulations

Page 136: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

0 20 40 60 80 100 120 140 1600

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Before the last two injections (144 bunches per injection) about 1/4 of each ring is still empty

800mm chamber – two beams simulations

Page 137: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

0 20 40 60 80 100 120 140 1600

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e-cloud buildup is observed when both beams are passing in the 800mm chamber

800mm chamber – two beams simulations

Page 138: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

2nd turn1st turn LSS2

e-cloud buildup is observed when both beams are passing in the 800mm chamber

800mm chamber – two beams simulations

Page 139: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

0 20 40 60 80 100 120 140 1600

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e-cloud buildup is observed when both beams are passing in the 800mm chamber

800mm chamber – two beams simulations

Page 140: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

0 20 40 60 80 100 120 140 1600

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e-cloud buildup is observed when both beams are passing in the 800mm chamber

800mm chamber – two beams simulations

Page 141: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

0 20 40 60 80 100 120 140 1600

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e-cloud buildup is observed when both beams are passing in the 800mm chamber

800mm chamber – two beams simulations

Page 142: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

0 20 40 60 80 100 120 140 1600

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e-cloud buildup is observed when both beams are passing in the 800mm chamber

800mm chamber – two beams simulations

Page 143: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

0 20 40 60 80 100 120 140 1600

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e-cloud buildup is observed when both beams are passing in the 800mm chamber

800mm chamber – two beams simulations

Page 144: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

0 20 40 60 80 100 120 140 1600

0.2

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A slow decay of the e-cloud is observed when only one 50ns beam is passing in the 800mm chamber

800mm chamber – two beams simulations

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A slow decay of the e-cloud is observed when only one 50ns beam is passing in the 800mm chamber

800mm chamber – two beams simulations

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A slow decay of the e-cloud is observed when only one 50ns beam is passing in the 800mm chamber

800mm chamber – two beams simulations

Page 147: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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A slow decay of the e-cloud is observed when only one 50ns beam is passing in the 800mm chamber

800mm chamber – two beams simulations

Page 148: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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A slow decay of the e-cloud is observed when only one 50ns beam is passing in the 800mm chamber

800mm chamber – two beams simulations

Page 149: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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A slow decay of the e-cloud is observed when only one 50ns beam is passing in the 800mm chamber

800mm chamber – two beams simulations

Page 150: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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A slow decay of the e-cloud is observed when only one 50ns beam is passing in the 800mm chamber

800mm chamber – two beams simulations

Page 151: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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A slow decay of the e-cloud is observed when only one 50ns beam is passing in the 800mm chamber

800mm chamber – two beams simulations

Page 152: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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A slow decay of the e-cloud is observed when only one 50ns beam is passing in the 800mm chamber

800mm chamber – two beams simulations

Page 153: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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2nd turn1st turn LSS2

A slow decay of the e-cloud is observed when only one 50ns beam is passing in the 800mm chamber

800mm chamber – two beams simulations

Page 154: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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2nd turn1st turn LSS2

A slow decay of the e-cloud is observed when only one 50ns beam is passing in the 800mm chamber

800mm chamber – two beams simulations

Page 155: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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A slow decay of the e-cloud is observed when only one 50ns beam is passing in the 800mm chamber

800mm chamber – two beams simulations

Page 156: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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2nd turn1st turn LSS2

A slow decay of the e-cloud is observed when only one 50ns beam is passing in the 800mm chamber

800mm chamber – two beams simulations

Page 157: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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2nd turn1st turn LSS2

A slow decay of the e-cloud is observed when only one 50ns beam is passing in the 800mm chamber

800mm chamber – two beams simulations

Page 158: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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2nd turn1st turn LSS2

A slow decay of the e-cloud is observed when only one 50ns beam is passing in the 800mm chamber

800mm chamber – two beams simulations

Page 159: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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2nd turn1st turn LSS2

No memory effect between following turns is observed

800mm chamber – two beams simulations

Page 160: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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2nd turn1st turn LSS2

No memory effect between following turns is observed

800mm chamber – two beams simulations

Page 161: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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2nd turn1st turn LSS2

No memory effect between following turns is observed

800mm chamber – two beams simulations

Page 162: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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2nd turn1st turn LSS2

No memory effect between following turns is observed

800mm chamber – two beams simulations

Page 163: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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2nd turn1st turn LSS2

No memory effect between following turns is observed

800mm chamber – two beams simulations

Page 164: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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2nd turn1st turn LSS2

No memory effect between following turns is observed

800mm chamber – two beams simulations

Page 165: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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2nd turn1st turn LSS2

No memory effect between following turns is observed

800mm chamber – two beams simulations

Page 166: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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2nd turn1st turn LSS2

No memory effect between following turns is observed

800mm chamber – two beams simulations

Page 167: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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2nd turn1st turn LSS2

No memory effect between following turns is observed

800mm chamber – two beams simulations

Page 168: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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2nd turn1st turn LSS2

No memory effect between following turns is observed

800mm chamber – two beams simulations

Page 169: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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2nd turn1st turn LSS2

No memory effect between following turns is observed

800mm chamber – two beams simulations

Page 170: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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2nd turn1st turn LSS2

No memory effect between following turns is observed

800mm chamber – two beams simulations

Page 171: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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2nd turn1st turn LSS2

No memory effect between following turns is observed

800mm chamber – two beams simulations

Page 172: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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2nd turn1st turn LSS2

No memory effect between following turns is observed

800mm chamber – two beams simulations

Page 173: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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2nd turn1st turn LSS2

No memory effect between following turns is observed

800mm chamber – two beams simulations

Page 174: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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2nd turn1st turn LSS2

No memory effect between following turns is observed

800mm chamber – two beams simulations

Page 175: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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2nd turn1st turn LSS2

No memory effect between following turns is observed

800mm chamber – two beams simulations

Page 176: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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2nd turn1st turn LSS2

No memory effect between following turns is observed

800mm chamber – two beams simulations

Page 177: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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2nd turn1st turn LSS2

No memory effect between following turns is observed

800mm chamber – two beams simulations

Page 178: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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2nd turn1st turn LSS2

No memory effect between following turns is observed

800mm chamber – two beams simulations

Page 179: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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2nd turn1st turn LSS2

No memory effect between following turns is observed

800mm chamber – two beams simulations

Page 180: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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2nd turn1st turn LSS2

No memory effect between following turns is observed

800mm chamber – two beams simulations

Page 181: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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2nd turn1st turn LSS2

No memory effect between following turns is observed

800mm chamber – two beams simulations

Page 182: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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2nd turn1st turn LSS2

No memory effect between following turns is observed

800mm chamber – two beams simulations

Page 183: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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2nd turn1st turn LSS2

No memory effect between following turns is observed

800mm chamber – two beams simulations

Page 184: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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2nd turn1st turn LSS2

No memory effect between following turns is observed

800mm chamber – two beams simulations

Page 185: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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2nd turn1st turn LSS2

No memory effect between following turns is observed

800mm chamber – two beams simulations

Page 186: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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2nd turn1st turn LSS2

No memory effect between following turns is observed

800mm chamber – two beams simulations

Page 187: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Fill 1960 19-20/07/2011

To check if our model of e-cloud can explain the observed behavior of

pressure rise, we have simulated the electron cloud build up in the

800mm chamber before and after the last two injections

Simulated conditions

800mm chamber – two beams simulations

Page 188: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

Page 189: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

Page 190: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

Page 191: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

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Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

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Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

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Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

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Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

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Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

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Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

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Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

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Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

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Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

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Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

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Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

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Complete 1380 b. fill. scheme

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2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

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Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

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Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

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Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

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Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

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Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

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Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

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Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

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Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

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Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

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Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

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Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

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Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

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Time [s]

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Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

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Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

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Time [s]

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Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

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Time [s]

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Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

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Time [s]

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Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

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Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

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Time [s]

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Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

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Time [s]

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Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

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Time [s]

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Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

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Time [s]

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Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

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Time [s]

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Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

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Time [s]

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Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

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Time [s]

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Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

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Time [s]

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Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

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Time [s]

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Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

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Time [s]

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44/61

Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

Page 232: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

Page 233: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

Page 234: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

Page 235: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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48/61

Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

Page 236: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

Page 237: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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50/61

Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

Page 238: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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51/61

Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

Page 239: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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52/61

Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

Page 240: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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53/61

Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

Page 241: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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54/61

Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

Page 242: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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55/61

Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

Page 243: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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56/61

Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

Page 244: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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57/61

Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

Page 245: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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58/61

Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

Page 246: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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59/61

Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

Page 247: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

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Last 2 inj. missing

Complete 1380 b. fill. scheme

2nd turn1st turn LSS2

At the end of injection the two rings look quite completely filled, the largest holes being the two abort gaps

800mm chamber – two beams simulations

Page 248: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

2nd turn

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Last 2 inj. missingComplete 1380 b. fill. scheme

1st turn

Memory effect is observed between turns, which can strongly enhance the electron cloud

800mm chamber – two beams simulations

LSS2

Page 249: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Future work / Wish list

• Arbitrary externally assigned magnetic/electric field maps (quadrupole,

combined function magnet, clearing electrode)

• Non elliptical boundary condition on chamber’s wall

• Non uniform secondary electron yield (including EC detector simulation)

• Integration with the HEADTAIL code for a self consistent model

• Benchmarking with machine observations and measurements (collected

and to be collected)

• Parallelization (GPU?)

x [mm]

y [

mm

]

Charge density [m-1]

-60 -40 -20 0 20 40 60

-20

-10

0

10

20

0

1

2

x 104

PyEcloud

HEADTAIL

Page 250: PyEcloud code and simulations G. Iadarola, G. Rumolo ICE meeting 9 April 2012

Thanks for your attention!