MOA4I2
GSI, Darmstadt, Germany
WEA1C2
TEMF, TU Darmstadt, Darmstadt, Germany
GSI, Darmstadt, Germany
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MOA4I2 |
Space-charge Limits and Possible Mitigation Approaches in the FAIR Synchrotrons | |
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| To fully exploit the potential of the new Facility for Antiproton and Ion Research (FAIR), the key synchrotrons SIS18 and SIS100 should be operated at the "space charge limit" for light- and heavy-ion beams at a tolerable low beam loss of a few percent per cycle. A detailed 3D tracking model with collective effects (space charge and impedance) has been established including a realistic magnet field error model and the Landau Damping octupoles. The error model for SIS100 is based on precise bench measurements of the main magnets, the one for SIS18 on a novel data-driven beam-based approach named Deep Lie Map Network. Simulations of the full one-second SIS100 accumulation plateau determine the maximum achievable bunch intensity and the corresponding low-loss working point region. Several mitigation approaches have been scrutinised for their impact on the space charge limit: beta-beat correction to suppress the half-integer resonance, bunch flattening via double harmonic RF, and pulsed electron lenses (e-lenses). An optimum configuration for pulsed e-lens operation has been determined, options for additional coherent stabilisation as a Landau damping e-lens are currently studied. | ||
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Slides MOA4I2 [3.697 MB] | |
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WEA1C2 |
Design of a Proof-of-Principle Experiment for the DLMN Method to Identify Magnetic Field Errors | |
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| Magnetic field errors limit the beam intensity in synchrotrons as they excite nonsystematic resonances, reduce dynamic aperture, and may result in beam loss due to space charge induced resonance crossing. Methods to establish a field error model from beam-based measurements are therefore a valuable tool for realistic limitation and improvement studies. We report on the implementation of a proof-of-principle experiment in the GSI synchrotron SIS18 to identify both linear and non-linear field errors. The goal is to demonstrate the Deep Lie Map Network (DLMN) technique, a proposed data-driven approach based on (unstructured) turn-by-turn BPM data. Established identification procedures in the literature are based on orbit or tune response matrices, or resonance driving terms. While they sequentially build a field error model for subsequent accelerator sections, the DLMN approach could save valuable beam time by detecting field errors in parallel. We underline the potential of the DLMN method via detailed simulation studies to infer gradient and sextupole errors. The outline of a proof-of-principle experiment is discussed upon first experimental experience. | ||
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Slides WEA1C2 [1.439 MB] | |
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