Beam Current Monitors for FAIR

The FAIR (Facility for Antiproton and Ion Research) accelerator facility presently under construction at GSIwill supply a wide range of beam intensities for physicsexperiments. Design beam intensities range from 2.5×1013protons/cycle to be delivered to the pBar-target andseparator for production of antiprotons, to beams of e.g.109 ions/s in the case of slowly extracted beams. Thelarge intensity range demands for dedicated beam currentmonitors for precise, non-destructive beam intensitymeasurements in the synchrotrons, transport lines andstorage rings of the FAIR facility. This report describesGSI developments of purpose-built beam currentmonitors for the SIS100 synchrotron and high-energybeam transport lines (HEBT) of FAIR. Prototypemeasurements with a SQUID-based Cryogenic CurrentComparator and a resonant beam charge transformer arepresented, and possibilities for further upgrades arediscussed

A Squid-Based Beam Current Monitor For FAIR

A Cryogenic Current Comparator (CCC) wasdeveloped for the upcoming FAIR-Project, providing anon-destructive online monitoring of the beam current inthe nA-range. The CCC was optimized for a lowestpossible noise-limited current resolution together with ahigh system bandwidth. Therefore, the low temperatureproperties of ferromagnetic core materials used in thepick-up coil were investigated and differentSuperconducting Quantum Interference Device (SQUID)-systems were tested.In this contribution we present results of the completedCryogenic Current Comparator for FAIR working in alaboratory environment, regarding the improvements inresolution and bandwidth due to the use of suitableferromagnetic core materials and optimized SQUIDsystemcomponents

Commissioning of the HITRAP Cooling Trap with Offline Ions

Highly charged heavy ions at rest offer a wide spectrum of precision measurements. The GSI Helmholtzzentrum für Schwerionenforschung GmbH is able to deliver ions up to U92+. As the production of these heavy, highly charged ions requires high kinetic energies, it is necessary to decelerate these ions for ultimate precision. The broad energy distribution, which results from the deceleration in the HITRAP linear decelerator, needs to be reduced to allow for further transportation and experiments. The HITRAP cooling trap is designed to cool, i.e., reduce, this energy spread by utilizing electron cooling. The commissioning of this trap is done with Ar16+-ions from a local EBIT ion source. By analyzing the signal of stored ions after ejection, properties such as ion lifetime, charge exchange, and ion motions can be observed. Here, we provide an overview of the recent results of the commissioning process and discuss future experiments

Quadrupole moments of odd-A ⁵³⁻⁶³Mn: Onset of collectivity towards N = 40

The spectroscopic quadrupole moments of the odd–even Mn isotopes between N=28 and N=38 have been measured using bunched-beam collinear laser spectroscopy at ISOLDE, CERN. In order to increase sensitivity to the quadrupole interaction, the measurements have been done using a transition in the ion rather than in the atom, with the additional advantage of better spectroscopic efficiency. Since the chosen transition is from a metastable state, optical pumping in ISOLDE’s cooler and buncher (ISCOOL) was used to populate this state. The extracted quadrupole moments are compared to large-scale shell model predictions using three effective interactions, GXPF1A, LNPS and modified A3DA. The inclusion of both the 1νg9/2and 2νd5/2orbitals in the model space is shown to be necessary to reproduce the observed increase in the quadrupole deformation from N=36 onwards. Specifically, the inclusion of the 2νd5/2orbital induces an increase in neutron and proton excitations across the reduced gaps at N=40and Z=28, leading to an increase in deformation above N=36

Genetic algorithms for machine optimization in the FAIR control system environment

An automated beam-setting optimization application has been implemented on top of FAIR’s control system software stack based on CERN’s LSA framework. The optimization functionality is built using the Jenetics software library implemented in Java. Tests of the software with beam have been performed at the CRYRING@ESR ion storage ring

Optimization of Heavy-Ion Synchrotrons Using Nature-Inspired Algorithms and Machine Learning

The application of machine learning and nature-inspired optimization methods, like for example genetic algorithms (GA) and particle swarm optimization (PSO) can be found in various scientific/technical areas. In recent years, those approaches are finding application in accelerator physics to a greater extent. In this report, nature-inspired optimization as well as the machine learning will be shortly introduced and their application to the accelerator facility at GSI/FAIR will be presented. For the heavy-ion synchrotron SIS18 at GSI, the multi-objective GA/PSO optimization resulted in a significant improvement of multi-turn injection performance and subsequent transmission for intense beams. An automated injection optimization with genetic algorithms at the CRYRING@ESR ion storage ring has been performed. The usage of machine learning for a beam diagnostic application, where reconstruction of space-charge distorted beam profiles from ionization profile monitors is performed, will also be shown. First results and the experience gained will be presented

Automatized Optimization of Beam Lines Using Evolutionary Algorithms

Due to the massive parallel operation modes at GSI accelerators, a lot of accelerator setup and re-adjustment has to be made by operators during a beam time. This is typically done manually using potentiometers and is very time-consuming. With the FAIR project the complexity of the accelerator facility increases further and for efficiency reasons it is recommended to establish a high level of automation for future operation. Modern Accelerator Control Systems allow a fast access to both, accelerator settings and beam diagnostics data. This provides the opportunity to implement algorithms for automated adjustment of e.g. magnet settings to maximize transmission and optimize required beam parameters. The fast-switching magnets in GSI-beamlines are an optimal basis for an automatic exploration of the parameter-space. The optimization of the parameters for the SIS18 multi-turn-injection using a genetic algorithm has already been simulated*. The first results of our automatized online parameter optimization at the CRYRING@ESR injector are presented here

Automatized optimization of beam lines using evolutionary algorithms

Due to the massive parallel operation modes at GSI accelerators, a lot of accelerator setup and re-adjustment has to be made by operators during a beam time. This is typically done manually using potentiometers and is very time-consuming. With the FAIR project the complexity of the accelerator facility increases further and for efficiency reasons it is recommended to establish a high level of automation for future operation. Modern Accelerator Control Systems allow a fast access to both, accelerator settings and beam diagnostics data. This provides the opportunity to implement algorithms for automated adjustment of e.g. magnet settings to maximize transmission and optimize required beam parameters. The fast-switching magnets in GSI-beamlines are an optimal basis for an automatic exploration of the parameter-space. The optimization of the parameters for the SIS18 multi-turn-injection using a genetic algorithm has already been simulated*. The first results of our automatized online parameter optimization at the CRYRING@ESR injector are presented here