SLAC, Menlo Park, California
CERN, Geneva
Radio Frequency (RF) accelerating system noise and non-idealities can have detrimental impact on the LHC performance through longitudinal motion and longitudinal emittance growth. A theoretical formalism has been developed to relate the beam and RF loop dynamics with the bunch length growth [1]. Measurements were conducted at LHC to validate the formalism, determine the performance limiting RF components, and provide the foundation for beam diffusion estimates for higher energies and intensities. A brief summary of these results is presented in this work.
[1] T. Mastorides et. al., "RF system models for the LHC with Application to
Longitudinal Dynamics", prepared for submission to Physical Review ST-AB.
SLAC, Menlo Park, California
CERN, Geneva
The LHC Low Level RF system (LLRF) is a complex multi-loop system used to regulate the superconductive cavity gap voltage as well as to reduce the impedance presented by RF stations to the beam. The RF system can have a profound impact on the stability of the beam; a mis-configured RF system has the potential of causing longitudinal instabilities, beam diffusion and beam loss. To configure the RF station for operation, a set of parameters in the LLRF multi-loop system have to be defined. Initial system commissioning as well as ongoing operation requires a consistent method of computer based remote measurement and model-based design of each RF station feedback system. This paper describes the suite of Matlab tools used for configuring the LHC RF system during the start up in Nov2009-Feb2010. We present a brief overview of the tool, examples of commissioning results, and basics of the model-based design algorithms. This work complements our previous presentation [1], where the algorithms and methodology followed in the tools were described.
[1] D. Van Winkle et. al. 'Feedback Configuration Tools for LHC Low Level RF System,' PAC'09, Vancouver, Canada, May 2009, THZCH03, p. 249 (2009); http://www. JACoW.org.
LBNL, Berkeley, California
SLAC, Menlo Park, California
Electron clouds impose limitations on current accelerators that may be more severe for future machines, unless adequate measures of mitigation are taken. Recently, it has been proposed to use feedback systems operating at high frequency (in the GHz range) to damp single-bunch transverse coherent oscillations that may otherwise be amplified during the interaction of the beam with ambient electron clouds. We have used the simulation package WARP-POSINST to study the growth rate and frequency patterns in space-time of the electron cloud driven transverse instability in the CERN SPS accelerator with, or without, an idealized feedback model for damping the instability. We will present our latest simulation results, contrast them with actual measurements and discuss the implications for the design of the actual feedback system.
SLAC, Menlo Park, California
LBNL, Berkeley, California
BNL, Upton, Long Island, New York
CERN, Geneva
The SPS at high intensities exhibits transverse single-bunch instabilities with signatures consistent with an Ecloud driven instability. We present recent MD data from the SPS, details of the instrument technique and spectral analysis methods which help reveal complex vertical motion that develops within a subset of the injected bunch trains. The beam motion is detected via wide-band exponential taper striplines and delta-σ hybrids. The raw sum and difference data is sampled at 50 GHz with 1.8 GHz bandwidth. Sliding window FFT techniques and RMS motion techniques show the development of large vertical tune shifts on portions of the bunch of nearly 0.025 from the base tune of 0.185. Results are presented via spectrograms and rms bunch slice trajectories to illustrate development of the unstable beam and time scale of development along the injected bunch train. The study shows that the growing unstable motion occupies a very broad frequency band of 1.2 GHz. These measurements are compared to numerical simulation results, and the system parameter implications for an Ecloud feedback system are outlined.