HB2016 - List of Authors (Oeftiger, A.)

Paper	Title	Page
MOPR025	Space Charge Modules for PyHEADTAIL	124
	A. Oeftiger CERN, Geneva, Switzerland S. Hegglin ETH, Zurich, Switzerland
	Funding: CERN, Doctoral Studentship and EPFL, Doctorate PyHEADTAIL is a 6D tracking tool developed at CERN to simulate collective effects. We present recent developments of the direct space charge suite, which is available for both the CPU and GPU. A new 3D particle-in-cell solver with open boundary conditions has been implemented. For the transverse plane, there is a semi-analytical Bassetti-Erskine model as well as 2D self-consistent particle-in-cell solvers with both open and closed boundary conditions. For the longitudinal plane, PyHEADTAIL offers line density derivative models. Simulations with these models are benchmarked with experiments at the injection plateau of CERN's Super Proton Synchrotron.
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MOPR026	Space Charge Mitigation With Longitudinally Hollow Bunches	130
	A. Oeftiger, S. Hancock, G. Rumolo CERN, Geneva, Switzerland
	Funding: CERN, Doctoral Studentship and EPFL, Doctorate Hollow longitudinal phase space distributions have a flat profile and hence reduce the impact of transverse space charge. Dipolar parametric excitation with the phase loop feedback systems provides such hollow distributions under reproducible conditions. We present a procedure to create hollow bunches during the acceleration ramp of CERN's PS Booster machine with minimal changes to the operational cycle. The improvements during the injection plateau of the downstream Proton Synchrotron are assessed in comparison to standard parabolic bunches.
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WEAM1X01	Code Bench-Marking for Long-Term Tracking and Adaptive Algorithms	357
	F. Schmidt, H. Bartosik, A. Huschauer, A. Oeftiger, M. Titze CERN, Geneva, Switzerland Y.I. Alexahin, J.F. Amundson, V.V. Kapin, E.G. Stern Fermilab, Batavia, Illinois, USA G. Franchetti GSI, Darmstadt, Germany J.A. Holmes ORNL, Oak Ridge, Tennessee, USA
	At CERN we have ramped up a program to investigate space charge effects in the LHC pre-injectors with high brightness beams and long storage times. This in view of the LIU upgrade project for these accelerators. These studies require massive simulation over large number of turns. To this end we have been looking at all available codes and started collaborations on code development with several laboratories: pyORBIT from SNS, SYNERGIA from Fermilab, MICROMAP from GSI and our in-house MAD-X code with an space charge upgrade. We have agreed with our collaborators to bench-mark all these codes in the framework of the GSI bench-marking suite, in particular the main types of frozen space charge and PIC codes are being tested. We also include a study on the subclass of purely frozen and the adaptive frozen modes both part of MAD-X in comparison with the purely frozen MICROMAP code. Last, we will report on CERN's code development effort to understand and eventually overcome the noise issue in PIC codes. J. Coupard et al., ‘‘LHC Injectors Upgrade, Technical Design Report, Vol. I: Protons'', LIU Technical Design Report (TDR), CERN-ACC-2014-0337.
	Slides WEAM1X01 [2.348 MB]
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WEAM3X01	Code Development for Collective Effects	362
	K.S.B. Li, H. Bartosik, G. Iadarola, A. Oeftiger, A. Passarelli, A. Romano, G. Rumolo, M. Schenk CERN, Geneva, Switzerland S. Hegglin ETH, Zurich, Switzerland A. Oeftiger, M. Schenk EPFL, Lausanne, Switzerland
	The presentation will cover approaches and strategies of modeling and implementing collective effects in modern simulation codes. We will review some of the general approaches to numerically model collective beam dynamics in circular accelerators. We will then look into modern ways of implementing collective effects with a focus on plainness, modularity and flexibility, using the example of the PyHEADTAIL framework, and highlight some of the advantages and drawbacks emerging from this method. To ameliorate one of the main drawbacks, namely a potential loss of performance compared to the classical fully compiled codes, several options for speed improvements will be mentioned and discussed. Finally some examples and application will be shown together with future plans and perspectives.
	Slides WEAM3X01 [65.643 MB]
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Paper

Title

Page

Space Charge Modules for PyHEADTAIL

124

A. Oeftiger
CERN, Geneva, Switzerland
S. Hegglin
ETH, Zurich, Switzerland

Funding: CERN, Doctoral Studentship and EPFL, Doctorate
PyHEADTAIL is a 6D tracking tool developed at CERN to simulate collective effects. We present recent developments of the direct space charge suite, which is available for both the CPU and GPU. A new 3D particle-in-cell solver with open boundary conditions has been implemented. For the transverse plane, there is a semi-analytical Bassetti-Erskine model as well as 2D self-consistent particle-in-cell solvers with both open and closed boundary conditions. For the longitudinal plane, PyHEADTAIL offers line density derivative models. Simulations with these models are benchmarked with experiments at the injection plateau of CERN's Super Proton Synchrotron.

Export •

reference for this paper to ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

MOPR026

Space Charge Mitigation With Longitudinally Hollow Bunches

130

A. Oeftiger, S. Hancock, G. Rumolo
CERN, Geneva, Switzerland

Funding: CERN, Doctoral Studentship and EPFL, Doctorate
Hollow longitudinal phase space distributions have a flat profile and hence reduce the impact of transverse space charge. Dipolar parametric excitation with the phase loop feedback systems provides such hollow distributions under reproducible conditions. We present a procedure to create hollow bunches during the acceleration ramp of CERN's PS Booster machine with minimal changes to the operational cycle. The improvements during the injection plateau of the downstream Proton Synchrotron are assessed in comparison to standard parabolic bunches.

Export •

reference for this paper to ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

WEAM1X01

Code Bench-Marking for Long-Term Tracking and Adaptive Algorithms

357

F. Schmidt, H. Bartosik, A. Huschauer, A. Oeftiger, M. Titze
CERN, Geneva, Switzerland
Y.I. Alexahin, J.F. Amundson, V.V. Kapin, E.G. Stern
Fermilab, Batavia, Illinois, USA
G. Franchetti
GSI, Darmstadt, Germany
J.A. Holmes
ORNL, Oak Ridge, Tennessee, USA

At CERN we have ramped up a program to investigate space charge effects in the LHC pre-injectors with high brightness beams and long storage times. This in view of the LIU upgrade project for these accelerators. These studies require massive simulation over large number of turns. To this end we have been looking at all available codes and started collaborations on code development with several laboratories: pyORBIT from SNS, SYNERGIA from Fermilab, MICROMAP from GSI and our in-house MAD-X code with an space charge upgrade. We have agreed with our collaborators to bench-mark all these codes in the framework of the GSI bench-marking suite, in particular the main types of frozen space charge and PIC codes are being tested. We also include a study on the subclass of purely frozen and the adaptive frozen modes both part of MAD-X in comparison with the purely frozen MICROMAP code. Last, we will report on CERN's code development effort to understand and eventually overcome the noise issue in PIC codes.
J. Coupard et al., ‘‘LHC Injectors Upgrade,
Technical Design Report, Vol. I: Protons'', LIU Technical Design
Report (TDR), CERN-ACC-2014-0337.

Slides WEAM1X01 [2.348 MB]

Export •

reference for this paper to ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

WEAM3X01

Code Development for Collective Effects

362

K.S.B. Li, H. Bartosik, G. Iadarola, A. Oeftiger, A. Passarelli, A. Romano, G. Rumolo, M. Schenk
CERN, Geneva, Switzerland
S. Hegglin
ETH, Zurich, Switzerland
A. Oeftiger, M. Schenk
EPFL, Lausanne, Switzerland

The presentation will cover approaches and strategies of modeling and implementing collective effects in modern simulation codes. We will review some of the general approaches to numerically model collective beam dynamics in circular accelerators. We will then look into modern ways of implementing collective effects with a focus on plainness, modularity and flexibility, using the example of the PyHEADTAIL framework, and highlight some of the advantages and drawbacks emerging from this method. To ameliorate one of the main drawbacks, namely a potential loss of performance compared to the classical fully compiled codes, several options for speed improvements will be mentioned and discussed. Finally some examples and application will be shown together with future plans and perspectives.

Slides WEAM3X01 [65.643 MB]

Export •

reference for this paper to ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)