IBIC2017 - List of Authors (Singh, R.)

Paper	Title	Page
MO2AB1	Beam Measurements Using Schottky Signal Analysis
	P. Forck, P. Kowina, R. Singh GSI, Darmstadt, Germany M. Wendt CERN, Geneva, Switzerland
	Schottky signal analysis is a non-invasive beam measurement method based on the observation of the electromagnetic properties of individual beam particles. It allows the determination of important parameters such as momentum spread, synchrotron tune, coherent and incoherent betatron tune, and chromaticity for coasting and bunched beams at hadron synchrotrons. It is a popular diagnostic at low energy ion storage rings as well as implemented for bunched beams in high energy synchrotrons such as LHC. In this tutorial, the underlying physics for the observables will be described together with the basic mathematics. Recent results for high intensity beam will be discussed. The detector technology, based on capacitive pick-ups, traveling wave structures, or cavities is addressed, as well as the associated rf electronics to extract this weak, beam induced Schottky signal. Applications ranging from the daily operational usage up to dedicated machine physics investigations on a very wide range of beam parameters will be discussed.
	Slides MO2AB1 [13.493 MB]
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WEPCC06	Simulation Supported Profile Reconstruction With Machine Learning	350
	R. Singh, M. Sapinski, D.M. Vilsmeier GSI, Darmstadt, Germany
	Measured IPM profiles can be significantly distorted due to displacement of residual ions or electrons by interaction with beam fields for high intensity or high energy beams. It is thus difficult to deduce the characteristics of the actual beam profile from the measurements. Neural network with multilayer perceptron (MLP)architecture is applied to reconstruct the actual beam profile from the measurement data. The MLP is trained using the IPM simulation tool developed under the IPMSim collaboration. The first results are presented in this contribution.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IBIC2017-WEPCC06
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Paper

Title

Page

MO2AB1

Beam Measurements Using Schottky Signal Analysis

P. Forck, P. Kowina, R. Singh
GSI, Darmstadt, Germany
M. Wendt
CERN, Geneva, Switzerland

Schottky signal analysis is a non-invasive beam measurement method based on the observation of the electromagnetic properties of individual beam particles. It allows the determination of important parameters such as momentum spread, synchrotron tune, coherent and incoherent betatron tune, and chromaticity for coasting and bunched beams at hadron synchrotrons. It is a popular diagnostic at low energy ion storage rings as well as implemented for bunched beams in high energy synchrotrons such as LHC. In this tutorial, the underlying physics for the observables will be described together with the basic mathematics. Recent results for high intensity beam will be discussed. The detector technology, based on capacitive pick-ups, traveling wave structures, or cavities is addressed, as well as the associated rf electronics to extract this weak, beam induced Schottky signal. Applications ranging from the daily operational usage up to dedicated machine physics investigations on a very wide range of beam parameters will be discussed.

Slides MO2AB1 [13.493 MB]

Export •

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

WEPCC06

Simulation Supported Profile Reconstruction With Machine Learning

350

R. Singh, M. Sapinski, D.M. Vilsmeier
GSI, Darmstadt, Germany

Measured IPM profiles can be significantly distorted due to displacement of residual ions or electrons by interaction with beam fields for high intensity or high energy beams. It is thus difficult to deduce the characteristics of the actual beam profile from the measurements. Neural network with multilayer perceptron (MLP)architecture is applied to reconstruct the actual beam profile from the measurement data. The MLP is trained using the IPM simulation tool developed under the IPMSim collaboration. The first results are presented in this contribution.

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-IBIC2017-WEPCC06

Export •

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